Share Logs

API Name: Kira2

Model: gpt-4o-mini-2024-07-182025-06-26 07:35:28

Context:

[
  {
    "role": "system",
    "content": "You are an assistant who is good at conversation. You need to summarize the user's conversation into a title of 10 characters or less. It should be in the format of \"Action - Title\". Some examples:\n1. Learn - Bitcoin 2. Code - Web Server 3. Write - An Article"
  },
  {
    "role": "user",
    "content": "User: chrome有什么好用的ai插件可以支持基于网页内容回答问题的吗\nAssistant: # Chrome 支持基于网页内容回答问题的AI插件\n\n以下是几款优秀的Chrome AI插件，可以帮助你基于网页内容回答问题：\n\n1. **WebChatGPT** - 允许ChatGPT访问网页内容，能够根据当前浏览的网页提供回答\n\n2. **Merlin** - 可以在任何网页上调用AI助手，支持基于当前页面内容回答问题\n\n3. **ChatGPT for Google** - 在搜索结果旁边显示ChatGPT回答，能够分析网页内容\n\n4. **HARPA AI** - 强大的网页内容分析工具，可以总结网页、回答相关问题\n\n5. **Glasp** - 网页高亮和笔记工具，集成AI可以基于高亮内容回答问题\n\n6. **Sider AI** - 侧边栏AI助手，可以基于当前浏览的网页内容提供回答\n\n7. **Monica** - 网页内容分析助手，可以回答关于网页内容的问题\n\n这些插件大多数都是免费的或提供免费版本，可以在Chrome网上应用店搜索并安装。"
  }
]

Response:

Explore - AI插件

Model: claude-3-7-sonnet-202502192025-06-26 07:35:27

Context:

[
  {
    "role": "user",
    "content": "chrome有什么好用的ai插件可以支持基于网页内容回答问题的吗"
  }
]

Response:

# Chrome 支持基于网页内容回答问题的AI插件以下是几款优秀的Chrome AI插件，可以帮助你基于网页内容回答问题： 1. **WebChatGPT** - 允许ChatGPT访问网页内容，能够根据当前浏览的网页提供回答 2. **Merlin** - 可以在任何网页上调用AI助手，支持基于当前页面内容回答问题 3. **ChatGPT for Google** - 在搜索结果旁边显示ChatGPT回答，能够分析网页内容 4. **HARPA AI** - 强大的网页内容分析工具，可以总结网页、回答相关问题 5. **Glasp** - 网页高亮和笔记工具，集成AI可以基于高亮内容回答问题 6. **Sider AI** - 侧边栏AI助手，可以基于当前浏览的网页内容提供回答 7. **Monica** - 网页内容分析助手，可以回答关于网页内容的问题这些插件大多数都是免费的或提供免费版本，可以在Chrome网上应用店搜索并安装。

Model: gpt-4o-mini-2024-07-182025-06-26 05:03:01

Context:

[
  {
    "role": "system",
    "content": "You are an assistant who is good at conversation. You need to summarize the user's conversation into a title of 10 characters or less. It should be in the format of \"Action - Title\". Some examples:\n1. Learn - Bitcoin 2. Code - Web Server 3. Write - An Article"
  },
  {
    "role": "user",
    "content": "User: 翻译成英文：不受控的代码管理\nAssistant: Translation to English: Uncontrolled Code Management"
  }
]

Response:

Translate - Code Mngmt

Model: claude-3-7-sonnet-202502192025-06-26 05:03:00

Context:

[
  {
    "role": "user",
    "content": "翻译成英文：不受控的代码管理"
  }
]

Response:

Translation to English: Uncontrolled Code Management

Model: claude-3-7-sonnet-202502192025-06-26 02:46:33

Context:

[
  {
    "role": "user",
    "content": "AI论文这么多 怎么筛选出最有价值的一些文章来阅读"
  },
  {
    "role": "assistant",
    "content": "# 如何筛选有价值的AI论文\n\n在AI领域论文数量爆炸式增长的今天，高效筛选有价值的论文确实是一个挑战。以下是一些实用策略：\n\n## 关注权威来源\n- **顶级会议论文**：CVPR, ICLR, NeurIPS, ICML, ACL等顶会论文通常质量较高\n- **知名实验室/公司**：关注Google DeepMind, OpenAI, Microsoft Research等机构发布的论文\n- **高引用论文**：使用Google Scholar查看引用次数较高的论文\n\n## 利用聚合工具\n- **Papers with Code**：展示附带代码实现的论文，且按任务分类\n- **arXiv Sanity Preserver**：提供个性化推荐和论文筛选\n- **Semantic Scholar**：利用AI帮助查找影响力高的论文\n\n## 关注综述性文章\n- 领域综述论文通常会总结近期重要进展\n- 年度技术回顾类文章可以快速了解重要突破\n\n## 建立个人筛选系统\n- **明确你的研究兴趣**：聚焦特定子领域而非泛泛阅读\n- **关注方法创新**：寻找提出新方法而非仅做小改进的论文\n- **实验验证充分**：检查论文是否有扎实的实验设计和充分的对比\n\n## 利用专家观点\n- 关注领域专家在Twitter/X、知乎等平台的推荐\n- 订阅AI领域的高质量通讯，如\"The Batch\"、\"Import AI\"等\n- 参与学术社区讨论，了解同行认为重要的工作\n\n记住，阅读策略应随着你的研究深入而调整，逐渐建立自己判断论文价值的标准。\n\n希望这些建议对你有所帮助！"
  },
  {
    "role": "user",
    "content": "怎么快速筛选顶会中近2-3年的高引论文"
  }
]

Response:

# 如何快速筛选顶会近2-3年的高引论文要高效筛选AI顶级会议中近2-3年的高引用论文，可以采用以下系统性方法： ## 利用学术搜索引擎 ### Google Scholar 1. 使用高级搜索功能，设置时间范围为2021-2023年 2. 搜索特定会议名称（如"CVPR"、"NeurIPS"等） 3. 按引用次数排序 4. 使用关键词进一步缩小范围（如"transformer"、"diffusion model"等） ### Semantic Scholar 1. 提供更精确的筛选功能 2. 可按会议名称、年份和引用次数排序 3. 提供"Influential Citations"指标，帮助识别真正有影响力的论文 ### Microsoft Academic/Connected Papers - 可视化展示论文间的引用关系，发现高影响力工作 ## 直接访问会议网站 ### 会议论文库 1. 访问CVPR、ICLR、NeurIPS等会议官方网站 2. 大多数会议提供"Best Paper"和"Outstanding Paper"列表 3. 部分会议提供按主题分类的论文列表 ### OpenReview平台 - 对于ICLR等使用开放评审的会议，可查看评审分数和讨论 ## 使用专业工具 ### Papers With Code 1. 按任务领域浏览（如计算机视觉、NLP等） 2. 查看各任务的SOTA（最先进技术）论文 3. 筛选特定年份和会议的论文 ### arXiv Sanity Preserver - 提供个性化推荐和高级筛选功能 ## 跟踪引用指标 1. 计算相对引用率：考虑论文发表时间长短的引用数量 2. 关注短期内引用增长快的论文 3. 设置引用阈值（如同期论文中引用数排名前10%） ## 实用技巧 - **创建自动提醒**：设置Google Scholar提醒，追踪特定会议的高引论文 - **关注研究机构**：DeepMind、OpenAI等机构在顶会发表的论文通常影响力较大 - **利用AI工具**：使用Connected Papers等工具生成论文关系图，识别关键节点论文通过综合运用这些方法，你可以快速定位到近2-3年内最有影响力的顶会论文，提高文献筛选效率。

Model: gpt-4o-mini-2024-07-182025-06-26 02:45:31

Context:

[
  {
    "role": "system",
    "content": "You are an assistant who is good at conversation. You need to summarize the user's conversation into a title of 10 characters or less. It should be in the format of \"Action - Title\". Some examples:\n1. Learn - Bitcoin 2. Code - Web Server 3. Write - An Article"
  },
  {
    "role": "user",
    "content": "[{\"role\":\"user\",\"mainText\":\"AI论文这么多 怎么筛选出最有价值的一些文章来阅读\"},{\"role\":\"assistant\",\"mainText\":\"# 如何筛选有价值的AI论文\\n\\n在AI领域论文数量爆炸式增长的今天，高效筛选有价值的论文确实是一个挑战。以下是一些实用策略：\\n\\n## 关注权威来源\\n- **顶级会议论文**：CVPR, ICLR, NeurIPS, ICML, ACL等顶会论文通常质量较高\\n- **知名实验室/公司**：关注Google DeepMind, OpenAI, Microsoft Research等机构发布的论文\\n- **高引用论文**：使用Google Scholar查看引用次数较高的论文\\n\\n## 利用聚合工具\\n- **Papers with Code**：展示附带代码实现的论文，且按任务分类\\n- **arXiv Sanity Preserver**：提供个性化推荐和论文筛选\\n- **Semantic Scholar**：利用AI帮助查找影响力高的论文\\n\\n## 关注综述性文章\\n- 领域综述论文通常会总结近期重要进展\\n- 年度技术回顾类文章可以快速了解重要突破\\n\\n## 建立个人筛选系统\\n- **明确你的研究兴趣**：聚焦特定子领域而非泛泛阅读\\n- **关注方法创新**：寻找提出新方法而非仅做小改进的论文\\n- **实验验证充分**：检查论文是否有扎实的实验设计和充分的对比\\n\\n## 利用专家观点\\n- 关注领域专家在Twitter/X、知乎等平台的推荐\\n- 订阅AI领域的高质量通讯，如\\\"The Batch\\\"、\\\"Import AI\\\"等\\n- 参与学术社区讨论，了解同行认为重要的工作\\n\\n记住，阅读策略应随着你的研究深入而调整，逐渐建立自己判断论文价值的标准。\\n\\n希望这些建议对你有所帮助！\"}]"
  }
]

Response:

Filter - AI文献

Model: claude-3-7-sonnet-202502192025-06-26 02:45:30

Context:

[
  {
    "role": "user",
    "content": "AI论文这么多 怎么筛选出最有价值的一些文章来阅读"
  }
]

Response:

# 如何筛选有价值的AI论文在AI领域论文数量爆炸式增长的今天，高效筛选有价值的论文确实是一个挑战。以下是一些实用策略： ## 关注权威来源 - **顶级会议论文**：CVPR, ICLR, NeurIPS, ICML, ACL等顶会论文通常质量较高 - **知名实验室/公司**：关注Google DeepMind, OpenAI, Microsoft Research等机构发布的论文 - **高引用论文**：使用Google Scholar查看引用次数较高的论文 ## 利用聚合工具 - **Papers with Code**：展示附带代码实现的论文，且按任务分类 - **arXiv Sanity Preserver**：提供个性化推荐和论文筛选 - **Semantic Scholar**：利用AI帮助查找影响力高的论文 ## 关注综述性文章 - 领域综述论文通常会总结近期重要进展 - 年度技术回顾类文章可以快速了解重要突破 ## 建立个人筛选系统 - **明确你的研究兴趣**：聚焦特定子领域而非泛泛阅读 - **关注方法创新**：寻找提出新方法而非仅做小改进的论文 - **实验验证充分**：检查论文是否有扎实的实验设计和充分的对比 ## 利用专家观点 - 关注领域专家在Twitter/X、知乎等平台的推荐 - 订阅AI领域的高质量通讯，如"The Batch"、"Import AI"等 - 参与学术社区讨论，了解同行认为重要的工作记住，阅读策略应随着你的研究深入而调整，逐渐建立自己判断论文价值的标准。希望这些建议对你有所帮助！

Model: claude-3-7-sonnet-202502192025-06-25 13:20:45

Context:

[
  {
    "role": "user",
    "content": [
      {
        "type": "text",
        "text": "Help me fill in the follow template given the project whitepaper and README file.\n\nFor fields with not enough info, leave it \"[blank]\".\n\n```\nProject Proposal Template\n\nGeneral Information\n1.1. Name of Project\n1.2. Project Description (what it does, why it is valuable, origin and history)\n1.3. How does this project align with the Consortium's Mission Statement\n1.4. Project website URL\n1.5. Social media accounts\n\nLegal Information\n2.1. Project Logo URL or attachment (Vector Graphic: SVG, EPS).\n2.2. Project license. We recommend an OSI-approved license, so if the license is not one on the list, explain why.\n2.3. Existing financial sponsorship.\n2.4. Trademark status.\n\nTechnical Information\n3.1. High level assessment of project synergy with existing projects under the CCC, including how the project compliments/overlaps with existing projects, and potential ways to harmonize over time. Responses may be included both inline and/or in accompanying documentation.\n3.2. Describe the Trusted Computing Base (TCB) of the project. If the project supports multiple environments please describe each TCB. Also identify if dependencies of other project (both CCC or non-CCC) TCBs are taken.\n3.3. Project Code of Conduct URL. We recommend a Contributor Covenant v2.0 based Code of Conduct, so if the Code of Conduct is not based on that, explain why.\n3.4. Source control URL\n3.5. Issue tracker URL\n3.6. External dependencies (including licenses, and indicate whether each is a build time or runtime dependency)\n3.7. Standards implemented by the project, if any. Include links to any such standards.\n3.8. Release methodology and mechanics\n3.9. Names of initial committers, if different from those submitting proposal\n3.10. List of project's official communication channels (slack, irc, mailing lists)\n3.11. Project Security Response Policy\n3.12. Preferred maturity level (Incubation, Graduation, or Emeritus) 3.13. Any additional information the TAC and Board should take into consideration when reviewing your proposal.\n```"
      },
      {
        "type": "text",
        "text": "README.md\n# Dstack\n\n[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/Dstack-TEE/dstack)\n\nDstack is a **developer friendly** and **security first** SDK to simplify the deployment of arbitrary containerized apps into TEE.\n\nMain features:\n\n- 🔒 Deploy containerized apps securely in TEE in minutes\n- 🛠️ Use familiar tools - just write a docker-compose.yaml\n- 🔑 Safely manage secrets and sensitive data\n- 📡 Expose services via built-in TLS termination\n\nDstack is community driven. Open sourced and built by [Kevin Wang](https://github.com/kvinwang) and many others from [Phala Network](https://github.com/Phala-Network), inspired by [Andrew Miller](https://github.com/amiller) (Flashbots & Teleport), and contributed by [Nethermind](https://github.com/NethermindEth/nethermind) and [many others](#contributors).\n\n![Alt](https://repobeats.axiom.co/api/embed/0a001cc3c1f387fae08172a9e116b0ec367b8971.svg \"Repobeats analytics image\")\n\n# Overview\n\nComponents in Dstack:\n\n- `dstack-vmm`: A service running in bare TDX host to manage CVMs\n- `dstack-gateway`: A reverse proxy to forward TLS connections to CVMs\n- `dstack-kms`: A KMS server to generate keys for CVMs\n- `dstack-guest-agent`: A service running in CVM to serve containers' key derivation and attestation requests\n- `meta-dstack`: A Yocto meta layer to build CVM guest images\n\nThe overall architecture is shown below:\n![arch](./docs/assets/arch.png)\n\n# Directory structure\n\n```text\ndstack/\n    kms/                         A prototype KMS server\n    guest-agent/                 A service running in CVM to serve containers' key derivation and attestation requests.\n    dstack-util/                 A CLI tool in the guest setting up the system, getting TDX quote, extending RTMR, generating cert for RA-TLS, etc.\n    vmm/                         A service running in bare TDX host to manage CVMs\n    gateway/                     A reverse proxy to forward TLS connections to CVMs\n    certbot/                     A tool to automatically obtain and renew TLS certificates for dstack-gateway\n    ra-rpc/                      RA-TLS support for pRPC\n    ra-tls/                      RA-TLS support library\n    tdx-attest/                  Guest library for getting TDX quote and extending RTMR\n```\n\n# Build and play locally\n\n## Prerequisites\n\n- A bare metal TDX server setup following [canonical/tdx](https://github.com/canonical/tdx)\n- Public IPv4 address assigned to the machine\n- At least 16GB RAM, 100GB free disk space.\n- A domain with DNS access if you want to set up `dstack-gateway` for Zero Trust HTTPS\n\n> [!NOTE]\n>\n> This doc assumes you have access to a compatible Intel TDX Server ready to be configured with Dstack. Check the [Hardware Requirements](https://docs.phala.network/dstack/hardware-requirements) for more information on buying a bare metal server or renting a server from OVH. To start learning about Dstack check out the [docs](https://docs.phala.network/dstack/overview).\n>\n> If you are looking to deploy a CVM in minutes, go to the docs to learn how to [sign-up for a Phala Cloud Account](https://docs.phala.network/phala-cloud/getting-started/sign-up-for-cloud-account) and [deploy your first CVM on Dstack]((https://docs.phala.network/phala-cloud/getting-started/start-from-cloud-ui)).\n\n## Install dependencies\n\n```bash\n# for Ubuntu 24.04\nsudo apt install -y build-essential chrpath diffstat lz4 wireguard-tools xorriso\n# install rust\ncurl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh\n```\n\n## Build and run for local development\n\n### Build the artifacts\n```bash\ngit clone https://github.com/Dstack-TEE/meta-dstack.git --recursive\ncd meta-dstack/\n\nmkdir build\ncd build\n../build.sh hostcfg\n# This outputs the following message:\n# Config file ../build-config.sh created, please edit it to configure the build\n\nvim ./build-config.sh\n```\n\nReview and customize the `build-config.sh` configuration file according to your environment requirements. The file contains network ports, domain settings, and other important parameters. Once configured, run the build script again to generate the necessary artifacts:\n\n```bash\n../build.sh hostcfg\n\n# If everything is okay, you should see the built artifacts in the `build` directory.\n$ ls\ncerts  images  dstack-kms  kms.toml  run  dstack-vmm  vmm.toml  dstack-gateway  gateway.toml\n```\n\n### Download guest image or build guest image from source\n\n```bash\n# This will download the guest image from the release page.\n../build.sh dl 0.5.2\n```\n\nOr build guest image from source:\n\n```bash\n# This will build the guest image from source using the yocto meta layer. This will take a while.\n../build.sh guest\n```\n\n> **Note on Reproducible Builds**: The build command above does not guarantee reproducibility. For reproducible builds across different build environments, please refer to the [reproducible build instructions](https://github.com/Dstack-TEE/meta-dstack?tab=readme-ov-file#reproducible-build-the-guest-image) in the meta-dstack repository.\n\n### Run components\nNow you can open 3 terminals to start the components:\n\n1. Run `./dstack-kms -c kms.toml`\n2. Run `sudo ./dstack-gateway -c gateway.toml`\n3. Run `./dstack-vmm -c vmm.toml`\n\n⚠️ *Warning: this is for local development, and the kms is not secure, so you should not use it in production.*\nFor production, you should follow the [deployment guide](./docs/deployment.md) and read the [security guide](./docs/security-guide/security-guide.md).\n\n## Deploy an App\nOpen the dstack-vmm webpage [http://localhost:9080](http://localhost:9080)(change the port according to your configuration) on your local machine to deploy a `docker-compose.yaml` file:\n\n![vmm](./docs/assets/vmm.png)\n\nAfter the container deployed, it should need some time to start the CVM and the containers. Time would be vary depending on your workload.\n\n- Click the [Logs] button to see the logs of the CVM, you can see if the container is finished starting there.\n\n- Once the container is running, you can click the [Dashboard] button to see some information of the container. And the logs of the containers can be seen in the [Dashboard] page.\n\n    ![dstack-guest-agent](./docs/assets/guest-agent.png)\n\n- You can open dstack-gateway's dashboard at [https://localhost:9070](https://localhost:9070) to see the CVM's wireguard ip address, as shown below:\n\n![dstack-gateway](./docs/assets/gateway.png)\n\n## Pass Secrets to Apps\nWhen deploying a new App, you can pass private data via Encrypted Environment Variables. These variables can be referenced in the docker-compose.yaml file as shown below:\n\n![secret](./docs/assets/secret.png)\n\nThe environment variables will be encrypted in the client-side and decrypted in the CVM before being passed to the containers.\n\n## Access the App\n\nOnce the app is deployed and listening on an HTTP port, you can access the HTTP service via dstack-gateway's public domain. The ingress mapping rules are:\n\n- `<id>[s].<base_domain>` maps to port `80` or `443` if with `s` in the CVM.\n- `<id>-<port>[s].<base_domain>` maps to port `<port>` in the CVM.\n\nFor example, `3327603e03f5bd1f830812ca4a789277fc31f577-8080.app.kvin.wang` maps to port `8080` in the CVM.\n\nWhere the `<id>` can be either the app id or the instance id. If the app id is used, one of the instances will be selected by the load balancer.\nIf the `id-port` part ends with `s`, it means the TLS connection will be passthrough to the app rather than terminating at dstack-gateway.\n\nYou can also ssh into the CVM to inspect more information, if your deployment uses the image `dstack-x.x.x-dev`:\n\n```bash\n# The IP address of the CVM can be found in the dstack-gateway dashboard.\nssh [email protected]\n```\n\n## Getting TDX quote in docker container\n\nTo get a TDX quote within app containers:\n\n1. Mount `/var/run/dstack.sock` to the target container in `docker-compose.yaml`\n\n    ```yaml\n    version: '3'\n    services:\n    nginx:\n        image: nginx:latest\n        volumes:\n        - /var/run/dstack.sock:/var/run/dstack.sock\n        ports:\n        - \"8080:80\"\n        restart: always\n    ```\n\n2. Execute the quote request command in the container.\n\n    ```bash\n    # The argument report_data accepts binary data encoding in hex string.\n    # The actual report_data passing the to the underlying TDX driver is sha2_256(report_data).\n    curl --unix-socket /var/run/dstack.sock http://localhost/GetQuote?report_data=0x1234deadbeef | jq .  \n    ```\n\n## Container logs\n\nContainer logs can be obtained from the CVM's `dashboard` page or by curl:\n\n```bash\ncurl 'http://<appid>.app.kvin.wang:9090/logs/<container name>?since=0&until=0&follow=true&text=true&timestamps=true&bare=true'\n```\n\nReplace `<appid>` and `<container name>` with actual values. Available parameters:\n\n- since=0: Starting Unix timestamp for log retrieval\n- until=0: Ending Unix timestamp for log retrieval\n- follow: Enables continuous log streaming\n- text: Returns human-readable text instead of base64 encoding\n- timestamps: Adds timestamps to each log line\n- bare: Returns the raw log lines without json format\n\nThe response of the RPC looks like:\n```\n$ curl 'http://0.0.0.0:9190/logs/zk-provider-server?text&timestamps'\n{\"channel\":\"stdout\",\"message\":\"2024-09-29T03:05:45.209507046Z Initializing Rust backend...\\n\"}\n{\"channel\":\"stdout\",\"message\":\"2024-09-29T03:05:45.209543047Z Calling Rust function: init\\n\"}\n{\"channel\":\"stdout\",\"message\":\"2024-09-29T03:05:45.209544957Z [2024-09-29T03:05:44Z INFO  rust_prover] Initializing...\\n\"}\n{\"channel\":\"stdout\",\"message\":\"2024-09-29T03:05:45.209546381Z [2024-09-29T03:05:44Z INFO  rust_prover::groth16] Starting setup process\\n\"}\n```\n\n## TLS Passthrough with Custom Domain\n\ndstack-gateway supports TLS passthrough for custom domains.\n\nSee the example [here](https://github.com/Dstack-TEE/dstack-examples/tree/main/custom-domain/dstack-ingress) for more details.\n\n## Upgrade an App\n\nGot to the dstack-vmm webpage, click the [Upgrade] button, select or paste the compose file you want to upgrade to, and click the [Upgrade] button again.\nThe app id does not change after the upgrade. Stop and start the app to apply the upgrade.\n\n## HTTPS Certificate Transparency\n\nIn the tutorial above, we used a TLS certificate with a private key external to the TEE. To establish trust, we need to generate and maintain the certificate's private key within the TEE and provide evidence that all TLS certificates for the domain were originate solely from dstack-gateway CVM.\n\nBy combining Certificate Transparency Logs and CAA DNS records, we can make best effort to minimize security risks. Here's our approach:\n\n- Set CAA records to allow only the account created in dstack-gateway CVM to request Certificates.\n- Launch a program to monitor Certificate Transparency Log and give alarm once any certificate issued to a pubkey that isn’t generated by dstack-gateway CVM.\n\n### Configurations\n\nTo launch Certbot, you need to own a domain hosted on Cloudflare. Obtain an API token with DNS operation permissions from the Cloudflare dashboard. Configure it in the `build-config.sh`:\n\n```bash\n# The directory to store the auto obtained TLS certificate and key\nGATEWAY_CERT=${CERBOT_WORKDIR}/live/cert.pem\nGATEWAY_KEY=${CERBOT_WORKDIR}/live/key.pem\n\n# for certbot\nCF_ZONE_ID=cc0a40...\nCF_API_TOKEN=g-DwMH...\n# ACME_URL=https://acme-v02.api.letsencrypt.org/directory\nACME_URL=https://acme-staging-v02.api.letsencrypt.org/directory\n```\n\nThen re-run the ../build.sh:\n\n```bash\n../build.sh\n```\n\n### Launch certbot\n\nThen run the certbot in the `build/` and you will see the following log:\n```text\n$ RUST_LOG=info,certbot=debug ./certbot renew -c certbot.toml\n2024-10-25T07:41:00.682990Z  INFO certbot::bot: creating new ACME account\n2024-10-25T07:41:00.869246Z  INFO certbot::bot: created new ACME account: https://acme-staging-v02.api.letsencrypt.org/acme/acct/168601853\n2024-10-25T07:41:00.869270Z  INFO certbot::bot: setting CAA records\n2024-10-25T07:41:00.869276Z DEBUG certbot::acme_client: setting guard CAA records for app.kvin.wang\n2024-10-25T07:41:01.740767Z DEBUG certbot::acme_client: removing existing CAA record app.kvin.wang 0 issuewild \"letsencrypt.org;validationmethods=dns-01;accounturi=https://acme-staging-v02.api.letsencrypt.org/acme/acct/168578683\"\n2024-10-25T07:41:01.991298Z DEBUG certbot::acme_client: removing existing CAA record app.kvin.wang 0 issue \"letsencrypt.org;validationmethods=dns-01;accounturi=https://acme-staging-v02.api.letsencrypt.org/acme/acct/168578683\"\n2024-10-25T07:41:02.216751Z DEBUG certbot::acme_client: setting CAA records for app.kvin.wang, 0 issue \"letsencrypt.org;validationmethods=dns-01;accounturi=https://acme-staging-v02.api.letsencrypt.org/acme/acct/168601853\"\n2024-10-25T07:41:02.424217Z DEBUG certbot::acme_client: setting CAA records for app.kvin.wang, 0 issuewild \"letsencrypt.org;validationmethods=dns-01;accounturi=https://acme-staging-v02.api.letsencrypt.org/acme/acct/168601853\"\n2024-10-25T07:41:02.663824Z DEBUG certbot::acme_client: removing guard CAA records for app.kvin.wang\n2024-10-25T07:41:03.095564Z DEBUG certbot::acme_client: generating new cert key pair\n2024-10-25T07:41:03.095678Z DEBUG certbot::acme_client: requesting new certificates for *.app.kvin.wang\n2024-10-25T07:41:03.095699Z DEBUG certbot::acme_client: creating new order\n2024-10-25T07:41:03.250382Z DEBUG certbot::acme_client: order is pending, waiting for authorization\n2024-10-25T07:41:03.283600Z DEBUG certbot::acme_client: creating dns record for app.kvin.wang\n2024-10-25T07:41:04.027882Z DEBUG certbot::acme_client: challenge not found, waiting 500ms tries=2 domain=\"_acme-challenge.app.kvin.wang\"\n2024-10-25T07:41:04.600711Z DEBUG certbot::acme_client: challenge not found, waiting 1s tries=3 domain=\"_acme-challenge.app.kvin.wang\"\n2024-10-25T07:41:05.642300Z DEBUG certbot::acme_client: challenge not found, waiting 2s tries=4 domain=\"_acme-challenge.app.kvin.wang\"\n2024-10-25T07:41:07.715947Z DEBUG certbot::acme_client: challenge not found, waiting 4s tries=5 domain=\"_acme-challenge.app.kvin.wang\"\n2024-10-25T07:41:11.724831Z DEBUG certbot::acme_client: challenge not found, waiting 8s tries=6 domain=\"_acme-challenge.app.kvin.wang\"\n2024-10-25T07:41:19.815990Z DEBUG certbot::acme_client: challenge not found, waiting 16s tries=7 domain=\"_acme-challenge.app.kvin.wang\"\n2024-10-25T07:41:35.852790Z DEBUG certbot::acme_client: setting challenge ready for https://acme-staging-v02.api.letsencrypt.org/acme/chall-v3/14584884443/mQ-I2A\n2024-10-25T07:41:35.934425Z DEBUG certbot::acme_client: challenges are ready, waiting for order to be ready\n2024-10-25T07:41:37.972434Z DEBUG certbot::acme_client: order is ready, uploading csr\n2024-10-25T07:41:38.052901Z DEBUG certbot::acme_client: order is processing, waiting for challenge to be accepted\n2024-10-25T07:41:40.088190Z DEBUG certbot::acme_client: order is valid, getting certificate\n2024-10-25T07:41:40.125988Z DEBUG certbot::acme_client: removing dns record 6ab5724e8fa7e3e8f14e93333a98866a\n2024-10-25T07:41:40.377379Z DEBUG certbot::acme_client: stored new cert in /home/kvin/codes/meta-dstack/dstack/build/run/certbot/backup/2024-10-25T07:41:40.377174477Z\n2024-10-25T07:41:40.377472Z  INFO certbot::bot: checking if certificate needs to be renewed\n2024-10-25T07:41:40.377719Z DEBUG certbot::acme_client: will expire in Duration { seconds: 7772486, nanoseconds: 622281542 }\n2024-10-25T07:41:40.377752Z  INFO certbot::bot: certificate /home/kvin/codes/meta-dstack/dstack/build/run/certbot/live/cert.pem is up to date\n```\n\nWhere the command did are:\n\n- Registered to letsencrypt and got a new account `https://acme-staging-v02.api.letsencrypt.org/acme/acct/168601853`\n- Auto set CAA records for the domain on cloudflare, you can open the CF dashboard to see the record:\n\n    ![certbot-caa](./docs/assets/certbot-caa.png)\n\n- Auto requested a new certificate from Let's Encrypt. Automatically renews the certificate to maintain its validity\n\n### Launch dstack-gateway\n\nExecute dstack-gateway with `sudo ./dstack-gateway -c gateway.toml`, then access the web portal to check the dstack-gateway CVM managed Let's Encrypt account. The account's private key remains securely sealed within the TEE.\n\n![gateway-accountid](./docs/assets/gateway-accountid.png)\n\n## Certificate transparency log monitor\n\nTo enhance security, we've limited TLS certificate issuance to dstack-gateway via CAA records. However, since these records can be modified through Cloudflare's domain management, we need to implement global CA certificate monitoring to maintain security oversight.\n\n`ct_monitor` tracks Certificate Transparency logs via [https://crt.sh](https://crt.sh/?q=app.kvin.wang), comparing their public key with the ones got from dstack-gateway RPC. It immediately alerts when detecting unauthorized certificates not issued through dstack-gateway:\n\n```text\n$ ./ct_monitor -t https://localhost:9010/prpc -d app.kvin.wang\n2024-10-25T08:12:11.366463Z  INFO ct_monitor: monitoring app.kvin.wang...\n2024-10-25T08:12:11.366488Z  INFO ct_monitor: fetching known public keys from https://localhost:9010/prpc\n2024-10-25T08:12:11.566222Z  INFO ct_monitor: got 2 known public keys\n2024-10-25T08:12:13.142122Z  INFO ct_monitor: ✅ checked log id=14705660685\n2024-10-25T08:12:13.802573Z  INFO ct_monitor: ✅ checked log id=14705656674\n2024-10-25T08:12:14.494944Z ERROR ct_monitor: ❌ error in CTLog { id: 14666084839, issuer_ca_id: 295815, issuer_name: \"C=US, O=Let's Encrypt, CN=R11\", common_name: \"kvin.wang\", name_value: \"*.app.kvin.wang\", not_before: \"2024-09-24T02:23:15\", not_after: \"2024-12-23T02:23:14\", serial_number: \"03ae796f56a933c8ff7e32c7c0d662a253d4\", result_count: 1, entry_timestamp: \"2024-09-24T03:21:45.825\" }\n2024-10-25T08:12:14.494998Z ERROR ct_monitor: error: certificate has issued to unknown pubkey: 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\n```\n\n# Troubleshooting\n\n### Error from dstack-vmm: qemu-system-x86_64: -device vhost-vsock-pci,guest-cid=<id>: vhost-vsock: unable to set guest cid: Address already in use\n\n`dstack-vmm` may throw this error when creating a new VM if the [Unix Socket CID](https://man7.org/linux/man-pages/man7/vsock.7.html) is occupied. To solve the problem, first, you should list the occupied CID:\n\n```bash\nps aux | grep 'guest-cid='\n```\n\nThen choose a new range of the CID not conflicting with the CID in use. You can change `build/vmm.toml` file and restart `dstack-vmm`. This error should disappear. For example, you may find 33000-34000 free to use:\n\n```toml\n[cvm]\ncid_start = 33000\ncid_pool_size = 1000\n```\n\nWhen building the dstack from scratch, you should change the CID configs in `build-config.sh` instead, because `vmm.toml` file is generated by `build.sh`. Its content is derived from `build-config.sh`.\n\nYou may encounter this problem when upgrading from an older version of dstack, because CID was introduced in `build-config.sh` in later versions. In such case, please follow the docs to add the missing entries in `build-config.sh` and rebuild dstack.\n\n### Error: Operation not permitted when building guest image\n\nWhen running `../build.sh guest`, you might encounter this error:\n\n```\nTraceback (most recent call last):\n  File \"/meta-dstack/poky/bitbake/bin/bitbake-worker\", line 278, in child\n    bb.utils.disable_network(uid, gid)\n  File \"/meta-dstack/poky/bitbake/lib/bb/utils.py\", line 1696, in disable_network\n    with open(\"/proc/self/uid_map\", \"w\") as f:\nPermissionError: [Errno 1] Operation not permitted\n```\n\nThis error occurs because Ubuntu 23.10 and later versions restrict unprivileged user namespaces by default. To fix this, run:\n\n```bash\nsudo sysctl kernel.apparmor_restrict_unprivileged_userns=0\n```\n\nThen try building again. For more information about this restriction, see the [Ubuntu discourse post](https://discourse.ubuntu.com/t/spec-unprivileged-user-namespace-restrictions-via-apparmor-in-ubuntu-23-10/37626).\n\n\n# Contributors\n\nDstack is proudly built by open source and Pi-rateship contributors:\n\n- Phala Network: [Kevin Wang](https://github.com/kvinwang), [Shelven Zhou](https://github.com/shelvenzhou), [Leechael](https://github.com/leechael)\n- Teleport: [Andrew Miller](https://github.com/amiller), [Sxy Sun](https://github.com/sxysun)\n- Flashbots: [Tina](https://github.com/CarboClanC), [Mateusz](https://github.com/Ruteri), [Dmarz](https://github.com/dmarzzz), [Moe](https://github.com/MoeMahhouk)\n- Ithaca: [Georgios](https://github.com/gakonst)\n- Fabric: [@gaoist](https://x.com/gaoist)\n- And many more...\n\nThe inspiration for this work stems from [Andrew Miller](https://github.com/amiller)’s pioneering concept of a [Docker-based P2P TEE SDK](https://collective.flashbots.net/t/dstack-speedrunning-a-p2p-confidential-vm/3876).\n\nThis project cannot be built without standing on the shoulders of giants:\n\n- [konvera/meta-confidential-compute](https://github.com/konvera/meta-confidential-compute)\n\nSpecial acknowledgment to [Flashbots](https://github.com/flashbots) for building a community around TEE. The TEE Hacker House initiative, organized by [Flashbots](https://github.com/flashbots) and led by [Tina](https://github.com/CarboClanC), has brought together TEE builders to develop tools for TEE-Web3 integration. This collaborative journey has generated invaluable insights for advancing secure, confidential environments within Web3.\n\nTogether, we’re shaping the future of TEE in Web3, paving the way for more secure and developer-accessible confidential computing!\n\nFor a full list of the direct contributors to this repo, see [Contributors](https://github.com/Dstack-TEE/dstack/contributors) on GitHub.\n\n\n# License\n\nCopyright 2024 Phala Network and Contributors.\n\nLicensed under the Apache License, Version 2.0 (the \"License\"); you may not use this file except in compliance with the License. You may obtain a copy of the License at\n\n[http://www.apache.org/licenses/LICENSE-2.0](http://www.apache.org/licenses/LICENSE-2.0)"
      },
      {
        "type": "text",
        "text": "main.pdf\nDstack:  A Zero Trust Framework for Confidential Containers\nJune 23, 2025\nAbstract\nWeb3 applications require execution platforms that maintain confidentiality and integrity with-\nout relying on centralized trust authorities.  While Trusted Execution Environments (TEEs) offer\npromising capabilities for confidential computing, current implementations face significant limita-\ntions in security reliability, censorship resistance, and vendor independence when applied to Web3\ncontexts.  This paper presents Dstack, a comprehensive framework that transforms raw TEE tech-\nnology  into  a  true  Zero  Trust  platform  aligned  with  Web3  principles.   We  introduce  three  key\ninnovations:  (1) Portable Confidential Containers that enable seamless workload migration across\nheterogeneous TEE environments while maintaining security guarantees, (2) Decentralized Code\nManagement that leverages smart contracts for transparent governance of TEE applications, and\n(3) Verifiable Domain Management that ensures secure and verifiable application identity without\ncentralized authorities. Through these innovations, implemented via Dstack-OS, Dstack-KMS, and\nDstack-Gateway components, we demonstrate how to achieve both the performance advantages of\nVM-level TEE solutions and the trustless guarantees required by Web3 applications.  Our evalu-\nation shows that Dstack provides comprehensive security guarantees while maintaining practical\nusability for real-world applications.\n1    Introduction\nThe Web3 ecosystem represents a paradigm shift in digital trust models, fundamentally transforming\nthe relationship between users and application developers.  Unlike traditional systems, Web3 empowers\nusers with unprecedented control over their data through the principle of ”Code is Law” - once deployed,\ncode  operates  autonomously  and  independently  of  external  control.   This  transformation  demands\nrobust execution platforms that maintain confidentiality and integrity without relying on centralized\ntrust authorities.\nFigure 1:  The evolution of trust models from Web2 to Web3, highlighting the shift from centralized control\nto decentralized governance and execution.\nThe contrast between Web2 and Web3 architectures in Figure 1 illustrates this fundamental shift.\nIn Web2 systems, developers maintain complete control through proprietary applications and central-\nized servers, retaining administrative privileges to access and modify user data at will.  Web3’s smart\n1\ncontracts,  however,  represent  the  first  significant  step  toward  true  trustlessness  by  executing  pro-\ngrams on decentralized platforms (blockchains).  Once deployed, administrators cannot influence pro-\ngram execution, and lifecycle management (e.g., code updates) follows predefined agreements through\ndemocratic governance mechanisms like multi-signature wallets and Decentralized Autonomous Orga-\nnizations (DAOs).  This emerging trust model extends beyond basic applications to mission-critical\nscenarios such as AI model training, where data providers and model developers often have competing\ninterests,  and  autonomous  AI  agents  designed  to  operate  independently  of  human  intervention.   In\nthese  contexts,  Zero  Trust  platforms  become  essential  to  host  applications  and  enforce  verification\nmechanisms that appropriately constrain developer authority.\nA Zero Trust platform must enforce the following key principles:\n•  Code is Law: This manifests in two dimensions: (1) the application logic, once deployed, cannot\nbe  changed  unexpectedly;  and  (2)  the  lifecycle  management  of  code—including  deployment,\nupgrades, and deletion—follows predefined governance rules.\n•  Censorship Resistance:  User data remains beyond the control of any single entity, with data\navailability protected against Denial-of-Service attacks.\n•  Full Chain-of-Trust:  When users interact with applications on a Zero Trust platform,  they\nmust be able to verify all aspects of that application, including network setup, application identity\nand code logic, underlying hardware, and execution environment.\n•  Assume Breach:  The platform operates under the assumption that compromises will occur,\nimplementing  mechanisms  for  damage  containment,  rapid  recovery,  and  minimization  of  data\nexposure during security incidents.\nConfidential Computing, particularly through Trusted Execution Environments (TEEs), has emerged\nas a promising foundation for extending blockchain capabilities to support complex computational tasks\nwith confidentiality guarantees.  Recent advances in VM-level TEE solutions, including Intel TDX and\nAMD SEV, have demonstrated substantial performance improvements and developer-friendly inter-\nfaces,  making  them  compelling  candidates  for  Web3  deployment.   The  integration  of  GPUs  within\nTEEs [?] now enables verifiable execution of both Large Language Models and AI agents, providing\ncryptographic guarantees of computational integrity.\nHowever, a significant gap exists between raw TEE technology and the requirements of a true Zero\nTrust platform.  Current TEE implementations face several critical limitations when applied to Web3\ncontexts:\n•  Security Reliability:  Recent vulnerability discoveries in TEE systems have raised significant con-\ncerns  about  their  effectiveness  as  trust  anchors.   The  persistence  of  side-channel  attacks  and\nmicro-architectural vulnerabilities undermines confidence in TEE security guarantees, particu-\nlarly for high-value Web3 applications where a single compromise could lead to catastrophic data\nexposure.\n•  Censorship Vulnerability:  Conventional TEE encryption schemes bind encryption keys to spe-\ncific  hardware  instances,  creating  single  points  of  failure  that  contradict  Web3’s  requirement\nfor censorship resistance.  This architectural limitation means that data availability cannot be\nguaranteed if specific hardware instances are compromised or become unavailable.\n•  Vendor Dependencies:  Current trust models heavily rely on centralized hardware manufacturers\nand verification processes, introducing risks of vendor lock-in and potential censorship vectors.\nThis centralization contradicts Web3’s core principles of decentralization and trustlessness.\n•  Incomplete Verifiability:  While TEEs provide Remote Attestation capabilities to verify applica-\ntion and hardware identity, they fail to deliver the comprehensive chain of trust required in Zero\nTrust environments.  Users need guarantees that programs will process their data as expected\nand cannot be modified without proper authorization—capabilities beyond current attestation\nmechanisms.\nTo bridge this gap between raw TEE technology and Zero Trust requirements, we present Dstack,\na comprehensive framework for confidential containers that introduces three key innovations:\n2\n•  Portable Confidential Container: Our architecture enables seamless migration of confidential\nworkloads across different TEE instances and hardware vendors,  significantly reducing vendor\nlock-in risks while maintaining robust security guarantees.  This innovation directly addresses the\ncensorship vulnerability and vendor dependency limitations by providing hardware abstraction\nand state continuity across heterogeneous TEE environments.\n•  Decentralized Code Management:  We implement a comprehensive governance framework\nthat leverages smart contracts for transparent and decentralized management of TEE applica-\ntions.  This  system ensures verifiable deployment  and upgrade processes,  enforcing the  “Code\nis Law” principle by binding application lifecycles to on-chain governance decisions.  This inno-\nvation addresses the incomplete verifiability limitation by creating an immutable audit trail of\napplication changes.\n•  Verifiable Domain Management: Our novel approach to certificate management ensures that\nconfidential containers can exclusively control domains and provide native HTTPS support to\nTEE applications without relying on centralized authorities.  This system serves as a middleware\nbetween TEE applications and existing TLS-based networks, enabling users to establish end-to-\nend encrypted channels to TEE applications without modifications to client software.\nThese innovations are implemented through a cohesive system architecture comprising three core\ncomponents:\n•  Dstack-OS: A hardware abstraction layer with a minimized operating system image that elimi-\nnates differences in underlying TEE hardware while reducing the attack surface.  This component\nprovides a consistent, secure runtime environment across diverse TEE implementations.\n•  Dstack-KMS:  A  blockchain-controlled  key  management  service  that  replaces  hardware-based\nencryption schemas with an independent service for generating and managing secret keys.  This\ncomponent  enables  secure  data  migration  across  TEE  instances  and  supports  key  rotation  to\nprovide forward and backward data secrecy, mitigating the impact of potential TEE compromises.\n•  Dstack-Ingress and Dstack-Gateway: Complementary systems providing TEE-controlled domain\nmanagement through different approaches—Dstack-Ingress enables applications to specify cus-\ntom domains with minimal integration requirements, while Dstack-Gateway offers pre-registered\nwildcard domains requiring no application code changes.\nBy addressing the critical limitations of current TEE implementations, Dstack establishes a compre-\nhensive framework that transforms raw TEE technology into a true Zero Trust platform aligned with\nWeb3’s fundamental principles.  Our approach not only enhances the security and reliability of confi-\ndential computing but also provides a practical path toward truly decentralized, censorship-resistant\ninfrastructure for next-generation applications.\nThe remainder of this paper details the technical design of Dstack, evaluates its performance and\nsecurity characteristics, and demonstrates how our innovations collectively create a Zero Trust platform\nthat maintains the performance advantages of VM-level TEE solutions while addressing their inherent\nlimitations in Web3 contexts.\n2    System Design\n2.1    Portable Confidential Container\nContainerization has transformed cloud-native application deployment by providing unparalleled porta-\nbility and scalability through effective data separation.  These capabilities are particularly critical for\nTrusted Execution Environment (TEE) applications, as they directly address the inherent limitations\noutlined in Section 1:\n•  Security Reliability:  Containerized applications can be efficiently transferred from compro-\nmised TEE hardware to secure instances,  preserving code integrity.  Together with our secure\ndata migration mechanism that ensures both forward and backward secrecy, this approach sig-\nnificantly limits privacy leakage risks even when individual TEE instances are compromised.\n3\nFigure 2:  The architecture of Dstack, including Dstack-OS and Dstack-KMS. Dstack-OS provides a hardware\nabstraction layer with a minimized operating system image, while Dstack-KMS replaces the hardware-based\ndata encryption keys with a blockchain-controlled key management service.  TODO: redraw this to put the\ncomponents into solutions.\n•  Censorship Resistance: The architecture’s inherent scalability provides robust defense against\nDenial-of-Service attacks. Additionally, by decoupling data storage from execution environments,\nestablished  data  availability  solutions  can  be  readily  integrated  to  ensure  persistent  access  to\napplication data.\n•  Vendor  Independence:   Our  hardware  abstraction  layer  enables  confidential  containers  to\noperate across diverse TEE hardware platforms without modification, eliminating vendor lock-in\nwhile facilitating rapid adoption of emerging TEE technologies as they become available.\nHowever, implementing truly portable confidential containers presents substantial technical chal-\nlenges that differentiate them from conventional containerization.  Two fundamental obstacles must be\novercome:\nFirst, existing TEE implementations generate data sealing keys derived from hardware-bound root\nkeys unique to each TEE instance.  This architectural design creates an inherent barrier to portability\n— data encrypted by one TEE instance cannot be decrypted by any other, even when running identical\napplication code.  Prior research has largely circumvented this limitation by restricting TEEs to state-\nless applications, but this approach severely constrains their utility in complex real-world scenarios.\nSecond,  TEE implementations from different vendors impose disparate specifications for deploy-\nable programs.  This fragmentation forces developers to create and maintain multiple artifacts across\nplatforms, each requiring separate (and expensive) code reviews to verify functional equivalence — a\nprocess that undermines the trust guarantees central to Web3 applications.\nTo address these challenges comprehensively, we introduce two complementary components: Dstack-\nKMS and Dstack-OS.\n2.1.1    Dstack-KMS: Blockchain-Controlled Secret Derivation\nDstack-KMS  is  a  secret  derivation  service  that  fundamentally  transforms  how  encryption  keys  are\nmanaged in confidential computing environments.  Its primary function is to generate a unique and\nstable secret (the Root Key ) for each application based on its code and configurations.  This root key\n4\nserves as the foundation for deriving additional application-specific secrets used for data encryption\nand verifiable random number generation.\nUnlike hardware-based encryption approaches, Dstack-KMS deliberately decouples key generation\nfrom specific TEE hardware instances.  This architectural decision enables the critical capability of\nencrypted  data  migration  between  different  TEE  instances,  with  decryption  possible  after\nproper authorization.  This feature is essential for achieving true censorship resistance.\nGiven  its  position  as  the  root-of-trust  for  the  entire  system,  the  verifiability  and  availability  of\nDstack-KMS are paramount.  Unlike previous approaches [?] that assume TEE infallibility, our threat\nmodel explicitly acknowledges that TEEs can be compromised.  To address this reality, Dstack-\nKMS  implements  comprehensive  key  rotation  capabilities  that  provide  both  backward  and  forward\nsecrecy for application data. This ensures that even if a specific TEE hardware instance is compromised,\napplications can be migrated with limited data exposure.\nFigure 3:  The key derivation hierarchy of Intel SGX illustrates how conventional TEE implementations bind\nencryption keys to hardware.\nTo understand the limitations of conventional approaches, Figure 3 illustrates the key derivation\nhierarchy in Intel SGX. This design uses a hardware-bound key to both identify the TEE instance (for\nRemote Attestation) and generate encryption keys for data sealing.  While this approach effectively\nestablishes hardware identity, it fundamentally undermines censorship resistance:\n•  The root key cannot be updated, meaning a compromised TEE with a leaked root key remains\npermanently vulnerable even after patching the underlying vulnerability.\n•  Encrypted data becomes intrinsically bound to specific TEE hardware instances, creating single\npoints of failure that contradict Web3’s censorship resistance requirements.\nOur  Dstack-KMS  addresses  these  limitations  by  delegating  secret  generation  to  an  independent\nservice that ensures encrypted data remains portable across TEE instances.\nAs illustrated in Figure 4, Dstack-KMS comprises an on-chain governance smart contract coupled\nwith an off-chain peer-to-peer network where the actual secret derivation service operates.  To ensure\ncomprehensive verifiability of the Dstack-KMS program’s integrity and correctness, we implement a\nmulti-stage verification process:\n1.  The Dstack-KMS codebase is fully open-sourced [?], enabling thorough code and security reviews\nto verify key management logic and ensure the absence of backdoors.\n5\nFigure 4:  The architecture of Dstack-KMS combines on-chain governance through smart contracts with an\noff-chain P2P network of secret derivation service nodes.  This design ensures both verifiability and resilience\nagainst compromise.\n2.  Executable  binaries  are  produced  through  reproducible  build  processes,  allowing  verifiers  to\nconfirm that the runtime code matches the reviewed source code.\n3.  The cryptographic digest of valid executables is published through the governance smart contract,\ncreating an immutable reference for verification.\n4.  Each service node operates within its own TEE instance.  Critically, we rely on the TEE solely for\nmeasuring the executable and ensuring it matches the on-chain digest—not for the fundamental\nsecurity of the key management process.\nThis verification framework ensures that Dstack-KMS remains trustworthy to any third-party verifier\nwhile avoiding dependency on the absolute security of any single TEE instance.\nThe core logic of each Dstack-KMS service node is intentionally minimalist, focusing exclusively on\nthe generation and secure distribution of the root key, along with deriving encryption keys for TEE\napplications.  This simplicity enables the implementation of Multi-Party Computation (MPC) based\nthreshold key generation and derivation without concerning performance overhead.  We have developed\ntwo complementary implementations:\n•  Simple Duplication:  The first node in the P2P network generates a cryptographically secure\nrandom number as the root key, then shares it with other nodes after verifying their attestation\nreports.  All nodes maintain identical copies of the root key and derive consistent encryption keys\nfor  applications.   This  approach  maximizes  availability—as  long  as  at  least  one  node  remains\noperational, the root key can be recovered.\n•  MPC-Based Key Generation:  While simple duplication provides robust availability, it cre-\nates vulnerability to single-node compromises.  Our MPC implementation uses Shamir’s Secret\nSharing scheme [?] to distribute the root key across multiple nodes, ensuring that compromising\nany individual node (or even up tot− 1 nodes, wheret is the configured threshold) does not\nexpose  the  root  key.   This  approach  also  enables  advanced  features  like  key  rotation  without\nrequiring application reconfiguration.\nKey Derivation    Dstack-KMS implements a comprehensive key derivation framework to generate\napplication-specific keys from the root key:\n•  Application CA Key:  Derived from the root CA key using the application’s unique identifier\n(calculated as the hash of the application’s code and configuration).\n•  Disk Encryption Key:  Derived using a combination of the application identifier and instance\nidentifier, enabling secure storage with portability.\n6\n•  Environment Encryption Key: Derived using the application identifier alone, allowing secure\nenvironment variable management across instances.\n•  ECDSA Key:  Derived from the root ECDSA key, providing applications with consistent cryp-\ntographic identity for signing operations.\nEach derived key maintains cryptographic isolation while ensuring consistency across different TEE\ninstances running the same application.\nKey Rotation    A critical security feature of Dstack-KMS is its support for key rotation, which signif-\nicantly limits the exposure window during potential attacks while ensuring both forward and backward\nsecrecy for sealed data.  Key rotation procedures are initiated exclusively through the governance smart\ncontract, ensuring transparency and auditability.  We discuss two distinct rotation mechanisms:\n•  Root Key Share Rotation:  Our MPC-based implementation enables rotation of individual\nkey  shares  without  modifying  the  root  key  itself.   This  process  enhances  root  key  security  by\nregularly updating the distribution mechanism while remaining transparent to applications, as\nall derived application keys remain unchanged.\n•  Root Key Rotation:  In scenarios where the root key may have been compromised, we support\ncomplete root key rotation.  This process generates an entirely new root key and implements a\ncontrolled handover period during which both old and new keys remain valid.  This transition\nwindow  allows  applications  to  re-encrypt  their  data  with  keys  derived  from  the  new  root  key\nbefore the old root key is permanently destroyed, minimizing service disruption while enhancing\nsecurity.\nThrough these mechanisms, Dstack-KMS provides the foundation for truly portable confidential con-\ntainers by decoupling encryption from hardware dependencies while maintaining robust security guar-\nantees.\n2.1.2    Dstack-OS: Hardware Abstraction Layer\nDstack-OS provides a comprehensive hardware abstraction layer with a minimized operating system\nimage that bridges the gap between application containers and VM-level TEE implementations.  This\nlayer enables applications to deploy across diverse TEE environments without code modifications while\nmaintaining security integrity.  As a shared component across all TEE applications, Dstack-OS must be\nintrinsically secure and verifiable, with no administrative backdoors that could compromise program\ncode or user data.\nVM-level  TEE  solutions  typically  require  developers  to  provide  complete  system  images  encom-\npassing  bootloader,  kernel,  operating  system,  and  application  components.   This  requirement  not\nonly increases development complexity but also introduces potential security vulnerabilities through\nmisconfigured system components.  A secure and properly configured operating system environment\nfundamentally determines the security baseline for all TEE applications built upon it.\nFigure 5 illustrates how Dstack-OS establishes a secure and verifiable startup chain from the TEE\nhardware foundation through to user-provided container images.  Our modular design ensures that the\nmajority of the system can be reused across different TEE hardware implementations, substantially\nreducing the effort required for code review and security auditing.  Combined with reproducible build\nprocesses, this approach enables comprehensive verification of Dstack-OS with minimal overhead while\nsupporting multiple TEE hardware platforms.\nUsing Intel TDX as an exemplar (with similar procedures applicable to other TEE implementa-\ntions like AMD SEV), Dstack-OS consists of the following components,  presented in boot sequence\norder.  During this process, each component measures the next one and records these measurements\nin hardware registers, which are ultimately incorporated into the TEE attestation report:\n•  Hypervisor: When application deployment initiates, the underlying hypervisor (the TDX mod-\nule) loads the Open Virtual Machine Firmware (OVMF), enabling UEFI support for confidential\nvirtual  machines.   The  TDX  module  measures  the  OVMF  code  and  records  its  cryptographic\ndigest in the MRTD register, with the hypervisor’s integrity guaranteed by the TEE hardware\nitself.\n7\nFigure 5:  The architecture of Dstack-OS establishes a secure and verifiable startup chain from TEE hardware\nthrough to user applications.\n•  Open Virtual Machine Firmware (OVMF): The OVMF configures virtual machine hard-\nware  specifications  (CPU,  memory,  and  device  configurations)  and  records  the  configuration\nmeasurement  to  the  RTMR0  register.   It  then  loads  the  Linux  kernel  and  records  the  kernel\nimage measurement to the RTMR1 register.\n•  Kernel:  The kernel first loads an initial ramdisk (initrd) — a temporary in-memory filesystem\ncontaining  minimal  command-line  tools  and  disk  encryption  libraries.   The  initrd  mounts  the\nroot filesystem and records this measurement in the RTMR2 register.\n•  Root Filesystem: The root filesystem (RootFs) is a read-only environment containing essential\nsystem libraries and tools.  It manages the entire lifecycle of deployed applications, measuring\napplication images along with their associated key management system and storing these mea-\nsurements  in  the  RTMR3  register.   The  RootFs  serves  two  primary  functions:  (1)  providing\nthe runtime environment for user-level container images, and (2) managing application data en-\ncryption.   It  interfaces  with  Dstack-KMS  to  acquire  encryption  secrets  and  implements  Linux\nUnified Key Setup (LUKS) to encrypt application data in isolated volumes.  Data integrity is\nensured through dm-verity, a Merkle-tree-based block-level verification tool.  Finally, the RootFs\nconfigures network ingress for the application and initiates execution.\nRather than adapting existing system images, we built Dstack-OS from scratch to ensure only es-\nsential components are included in both the initrd and RootFs.  A comprehensive component inventory\nis provided in Appendix ?? for transparency and review.  Generally,  Dstack-OS includes only basic\nutilities (busybox), filesystem support, and container runtime components.  By implementing Docker\nsupport  while  delegating  orchestration  to  the  application  level,  we  maintain  a  minimal  base  image\nfootprint.\nTo ensure comprehensive verifiability, Dstack-OS is fully open-sourced and supports reproducible\nbuilds,  allowing  anyone  to  review  the  code  and  generate  identical  artifacts  for  verification.   This\napproach provides significant benefits for applications requiring security reviews,  as evaluators need\nonly review the application code rather than the entire system image.\nData Backup and Defense against Rollback Attacks    A critical challenge in confidential com-\nputing is ensuring data durability and integrity, particularly against rollback attacks where adversaries\nattempt to revert applications to previous states to bypass security checks or reuse expired secrets.\nOur architecture provides robust secure data backup support and implements robust anti-rollback\nmechanisms that application developers can integrate:\n•  Secure Backup:  Application data is encrypted using keys derived from Dstack-KMS and can\nbe backed up to external storage providers.  Since encryption keys are not bound to specific TEE\n8\ninstances, data can be restored on any authorized TEE, supporting true portability and disaster\nrecovery.\n•  Monotonic Counters: To prevent rollback attacks, developers can implement monotonic coun-\nters that increment with each critical data update, incorporating the counter value into the en-\ncrypted data.  During restoration, applications verify that the counter value equals or exceeds\nthe last known value, preventing replay of outdated snapshots.\nBy combining these techniques,  Dstack ensures both the recoverability and integrity of confidential\ndata across portable container migrations and backup scenarios.\nTogether, Dstack-KMS and Dstack-OS provide the foundational infrastructure for truly portable\nconfidential containers that maintain security and integrity across heterogeneous TEE environments\nwhile eliminating vendor lock-in and supporting comprehensive verifiability.\n2.2    Decentralized Code Management\nA core principle of Zero Trust platforms is the enforcement of “Code is Law”, ensuring that application\ncode  operates  as  intended  without  unexpected  modifications.   While  TEE  hardware  provides  code\nintegrity guarantees during execution, it cannot independently prevent administrators from deploying\nmalicious code or making unauthorized modifications.  Conversely, smart contracts have established\nrobust methodologies for implementing programmable governance over code lifecycle management —\nsuch as multi-signature requirements that prevent single-actor manipulation.\nOur  decentralized  code  management  framework  bridges  these  two  worlds  by  placing  TEE  ap-\nplication governance under smart contract control,  creating a transparent and auditable system for\napplication deployment and updates that aligns with Web3 principles.\nFigure 6:  The architecture of decentralized code management integrates on-chain governance contracts with\noff-chain TEE through Dstack-KMS.\nAs illustrated in Figure 6, our architecture consists of two complementary components:  on-chain\ngovernance  smart  contracts  and  off-chain  TEE  execution  environments  connected  through  Dstack-\nKMS. This design establishes the on-chain contracts as the definitive root-of-trust for the entire system.\nEvery operation — from initial deployment to code upgrades — must first be initiated and authorized\nthrough the governance contracts before off-chain TEE instances can execute these operations.\nThe governance framework implements a two-tier structure:\n•  KmsAuth Contract:  Serves as the global authority controlling Dstack-KMS operations.  This\ncontract maintains the registry of authorized applications and their governance parameters, en-\nforcing system-wide policies for TEE deployment.  By controlling whether Dstack-KMS shares\n9\napplication  secrets  with  specific  TEE  instances,  the  KmsAuth  contract  effectively  determines\nwhether applications can decrypt their data, thus controlling their complete lifecycle.\n•  AppAuth Contracts:  Individual governance contracts deployed for each application that de-\nfine  application-specific  management  rules.   These  contracts  specify  permissible  code  versions\n(through cryptographic hashes), authorized TEE instance identities, and upgrade approval re-\nquirements.  This modular approach enables customized governance models ranging from tradi-\ntional multi-signature schemes to complex DAO voting mechanisms, allowing each application\nto implement governance appropriate to its requirements.\nThe enforcement mechanism operates through Dstack-KMS, which will only provide application\nsecrets  to  TEE  instances  running  code  versions  explicitly  authorized  by  the  governance  contracts.\nThis creates a cryptographically enforced governance system where unauthorized code versions cannot\naccess application data, regardless of administrative privileges.\nTo  illustrate  this  mechanism,  consider  a  code  upgrade  process  for  an  application  using  a  multi-\nsignature AppAuth contract in Figure 6:\n1.  Developers  publish  the  new  code  version  and  submit  its  cryptographic  hash  to  the  AppAuth\ncontract.\n2.  The  contract  initiates  the  approval  process,  requiring  signatures  from  designated  key  holders\n(e.g., core developers, security auditors, and community representatives).\n3.  Each signature is recorded on-chain, creating an immutable audit trail of the approval process.\n4.  Once the required signature threshold is reached, the AppAuth contract updates its registry of\nauthorized code versions.\n5.  The  KmsAuth  contract,  monitoring  the  AppAuth  contract,  updates  its  authorization  records\naccordingly.\n6.  Dstack-KMS,  which  continuously  synchronizes  with  the  KmsAuth  contract,  begins  providing\napplication secrets to TEE instances running the newly approved code version.\n7.  TEE instances can now deploy the new code with full access to encrypted application data.\nThis process ensures that every code change follows predefined governance rules with complete trans-\nparency.  The on-chain approval records create an immutable audit trail that allows users to verify\nthe entire history of application changes, while the cryptographic enforcement through Dstack-KMS\nguarantees that only properly authorized code can access application data.\nBy combining the code integrity guarantees of TEEs with the transparent governance capabilities\nof  smart  contracts,  our  decentralized  code  management  framework  ensures  that  applications  truly\nembody the ”Code is Law” principle. Every aspect of the application lifecycle—from initial deployment\nto  version  updates  and  potential  retirement—follows  predefined,  transparent  rules  that  cannot  be\ncircumvented by any single entity, including the platform operators themselves.\n2.3    Verifiable Domain Management\nA  complete  Zero  Trust  platform  must  enable  seamless  verification  for  users  across  both  Web3  and\ntraditional  Web2  environments.   Our  Verifiable  Domain  Management  system  completes  the  chain-\nof-trust  by  allowing  standard  Web  browsers  to  cryptographically  verify  TEE  applications  without\nrequiring any client-side modifications or specialized knowledge.\nThis  capability  is  critical  for  mainstream  adoption,  as  it  allows  users  to  interact  with  confiden-\ntial applications using familiar tools while maintaining the same security guarantees provided by the\nunderlying TEE infrastructure.  We implement this through two complementary components—Dstack-\nIngress and Dstack-Gateway—both leveraging our novel Zero Trust TLS (ZT-TLS) protocol.\nThe  fundamental  innovation  in  ZT-TLS  is  establishing  cryptographic  proof  that  a  specific  TLS\ncertificate  (and  therefore  a  domain)  is  exclusively  controlled  by  a  verified  TEE  application.   This\ncreates a verification chain extending from the blockchain to standard HTTPS connections, enabling\nusers to confirm application authenticity through familiar security indicators in their browsers.\n10\nFigure  7:   The  Zero  Trust  TLS  architecture  establishes  a  cryptographically  verifiable  connection  between\nstandard web browsers and TEE applications through blockchain-anchored certificate management.\n2.3.1    Zero Trust TLS Protocol\nThe  ZT-TLS  protocol  addresses  a  critical  challenge:  how  to  cryptographically  bind  a  domain  to  a\nspecific TEE application in a way that prevents unauthorized certificate issuance or domain hijacking.\nOur solution integrates three key components:\n•  TEE-Generated Certificates:  The TEE application (specifically Dstack-Gateway) generates\nits TLS certificate using application secrets derived from Dstack-KMS. This ensures the private\nkey  never  exists  outside  the  TEE  environment  and  creates  a  cryptographic  link  between  the\non-chain governance and the TLS certificate.\n•  Certificate  Authority  Authorization  (CAA):  We  leverage  DNS  CAA  records  to  restrict\nwhich  certificate authorities can  issue certificates  for managed  domains.  By  configuring CAA\nrecords  to  only  authorize  certificates  from  specific  issuers  (which  verify  TEE  attestation),  we\nprevent unauthorized certificate issuance through alternative validation methods.\n•  Certificate Transparency (CT) Monitoring:  To protect against unauthorized DNS record\nmodifications, we implement continuous monitoring of Certificate Transparency logs.  This allows\ndetection of any unauthorized certificates and provides an immutable audit trail of certificate\nissuance history.\n2.3.2    Implementation Components\nWe provide two complementary implementations to accommodate different application requirements:\n•  Dstack-Gateway:  A fully managed reverse proxy running within a TEE that provides imme-\ndiate domain verification with zero application code changes.  Applications register with Dstack-\nGateway through a simple API call, during which Dstack-Gateway verifies the application’s re-\nmote attestation report.  Once verified, applications receive a subdomain under a pre-registered\nwildcard domain (e.g., app-id.Dstack.com), with all TLS termination and certificate manage-\nment handled automatically.\n•  Dstack-Ingress:   A  more  flexible  solution  for  applications  requiring  custom  domain  names.\nDstack-Ingress provides libraries and services that enable applications to manage their own TLS\ncertificates while maintaining the same verification guarantees.  This approach requires minimal\nintegration work while supporting application-specific domain requirements.\n11\nBoth implementations ensure that certificates are cryptographically bound to verified TEE environ-\nments, with the verification chain extending from the blockchain governance contracts through to the\nTLS certificates presented to users’ browsers.\n2.3.3    Security Guarantees and Protections\nOur Verifiable Domain Management system provides several critical security guarantees:\n•  Certificate Provenance Verification:  Users can verify that the TLS certificate presented by\nan application was issued to a legitimate TEE environment by checking the certificate against\non-chain records.\n•  Domain Binding Integrity:  The combination of CAA records and Certificate Transparency\nmonitoring ensures that domains remain bound to their designated TEE applications, preventing\nunauthorized certificate issuance.\n•  Tamper-Evident Certificate Changes:  Any unauthorized attempts to modify domain con-\nfigurations or issue alternative certificates are detected through Certificate Transparency moni-\ntoring, with alerts propagated to clients.\nWhile we cannot technically prevent all attacks against centralized DNS infrastructure, our multi-\nlayered approach creates a tamper-evident system where unauthorized changes are quickly detected\nand rejected by client verification processes.  This approach aligns with the ”Assume Breach” principle\nby implementing defense-in-depth strategies that maintain security even when individual components\nare compromised.\nBy extending the verification chain from blockchain governance through TEE attestation to stan-\ndard TLS certificates, our Verifiable Domain Management system enables seamless integration of Zero\nTrust  applications  into  existing  web  infrastructure.   This  creates  a  practical  path  for  mainstream\nadoption without requiring specialized knowledge or tools from end users, while maintaining the com-\nprehensive security guarantees that define true Zero Trust platforms.\n3    Verifying TEE Applications:  A Practical Walkthrough\nTo demonstrate how Dstack fulfills the Zero Trust principles and addresses the challenges outlined in\nSection 1,  we present a practical end-to-end verification scenario.  This walkthrough illustrates how\nthe architectural components described in Section 2 work together to provide a comprehensive chain\nof trust for real-world Web3 applications.\nTraditional  Zero  Trust  programs  like  smart  contracts  achieve  verifiability  through  transparent\nsource  code  and  inputs.   However,  extending  similar  verifiability  to  real-world  applications  presents\nunique  challenges,  particularly  in  maintaining  privacy  and  compatibility  with  existing  development\npractices.   Dstack  addresses  these  challenges  through  a  comprehensive  verification  framework  that\nrequires minimal code changes.\nThis section demonstrates Dstack’s complete chain of trust through a practical example:  verifying\nthat  a  cryptographic  key  was  genuinely  generated  within  a  TEE  environment.   This  scenario  is  es-\npecially relevant for Web3 and AI Agent applications where cryptographic keys establish application\nidentity and authority.\n3.1    Threat Model\nOur verification framework assumes the correct implementation and integrity of core Dstack compo-\nnents (Dstack-OS, Dstack-KMS, Dstack-Gateway, and governance contracts). While these components’\nsecurity guarantees are detailed in later sections, we explicitly consider developers and administrators\nas potential adversaries.\nPotential attack vectors include:\n•  Application-Level Attacks\n–  Deployment of unauthorized or malicious code through falsified Docker images\n12\n–  Introduction of malicious dependencies through supply chain attacks\n–  Unauthorized application updates that bypass governance controls\n•  Infrastructure-Level Attacks\n–  Tampering with Dstack-OS to circumvent security controls\n–  Deployment of compromised key management services\n–  Operation of unpatched or vulnerable TEE firmware\n–  Execution of applications on non-TEE hardware with spoofed attestation\n•  Network-Level Attacks\n–  DNS hijacking to redirect traffic to unauthorized applications\n–  Man-in-the-middle attacks on communication channels\nDirect attacks on TEE hardware security (e.g., exploitation of hardware vulnerabilities) are con-\nsidered out of scope for this discussion and addressed separately.\n3.2    The Reproducibility Challenge\nA  fundamental  challenge  in  TEE  attestation  lies  in  bridging  the  gap  between  source  code  and  the\nactual  artifacts  (binaries  or  container  images)  running  inside  enclaves.   While  TEE  attestation  can\nprove that a specific artifact runs within a secure environment, it cannot independently verify that the\nartifact accurately represents its claimed source code.\nThis limitation creates several security risks:\n•  Source Code Manipulation:  Developers could intentionally deploy artifacts that differ from\npublicly reviewed source code\n•  Build Process Compromise:  Supply chain attacks could inject malicious code during artifact\ncreation\n•  Toolchain  Vulnerabilities:   As  demonstrated  by  the  Ken  Thompson  Hack,  even  compiler\ntoolchains could be compromised to inject malicious behavior\nTEE  quotes  only  attest  to  measurements  (cryptographic  hashes)  of  running  artifacts.   Without\nguarantees that these artifacts accurately represent reviewed source code, users cannot fully trust ap-\nplications even when running in secure enclaves.  This challenge affects all TEE applications, including\nDstack’s core components.\nFigure 8:  Comprehensive verification chain from source code to running TEE applications\nEstablishing a complete verification chain requires three key elements:\n13\n•  Source Code Verification:  Open-source code or trusted third-party review ensuring no back-\ndoors exist\n•  Build Process Integrity:  Reproducible builds allowing independent verification of artifacts\n•  Runtime Attestation:  TEE quotes proving that verified artifacts are actually running\nTraditional reproducible builds, while ideal, often introduce significant complexity through special-\nized  toolchains  and  build  scripts.   The  following  section  introduces  an  alternative  approach, In-CC\nBuild, that achieves similar guarantees with improved practicality.\n3.3    Dstack Component Verifiability\nEach  core  Dstack  component  implements  specific  verifiability  mechanisms  anchored  in  transparent,\nimmutable records.  Table 1 summarizes these mechanisms:\nComponentSourceBuild MethodRegistryVerification\nDstack-OSOpenReproducibleKmsAuthOS Digest\nDstack-KMSOpenIn-CCKmsAuthImage Hash, Root PubKey\nDstack-GatewayOpenIn-CCAppAuthImage Hash\nTable 1:  Verifiability mechanisms and trust anchors for Dstack components\nAll components maintain open-source codebases with comprehensive documentation. Dstack-OS, as\nthe foundational component, undergoes third-party security audits and implements fully reproducible\nbuilds.\nThe governance smart contracts serve as authoritative registries, anchoring each component’s trust\nbase:\n•  Dstack-OS digests are registered in KmsAuth and managed through multi-signature governance\n•  Dstack-KMS measurements and root public keys are recorded in KmsAuth\n•  Dstack-Gateway artifacts are verified through dedicated AppAuth contracts\nIn-ConfidentialContainer Build    While reproducible builds represent the gold standard for arti-\nfact verification, they often prove impractical for complex applications.  Dstack addresses this through\nIn-CC Build,  leveraging  the  verified  Dstack-OS  as  a  trusted  foundation.   The  In-CC  Build  process\nexecutes entirely within Dstack-OS environment, encompassing code fetching, compilation, and arti-\nfact creation.  By specifying precise source references (e.g., a snapshot of the codebase), the system\nproduces verifiable artifacts with measurements attested in TEE quotes.  This approach minimizes the\ntrusted computing base while eliminating the complexity of traditional reproducible builds.\n3.4    End-to-End Verification Walkthrough\nFrom a user’s perspective, verifying a TEE application in Dstack requires validating a chain of mea-\nsurements against authoritative registries,  encompassing the user application,  runtime data,  Dstack\ncomponents, and network infrastructure.  This section walks through the verification process, demon-\nstrating how each step builds upon the previous one to create a comprehensive chain of trust.\nAs shown in Figure 9, the verification chain begins with the KmsAuth smart contract, which serves\nas the root of trust for the entire system, and concludes with the key generation application running\nin a TEE. We explain the verification steps as follows.\nFirst,  the address of the Dstack-KMS governance contract (i.e.,  KmsAuth) is publicly available.\nThe KMS governance contract serves as the authoritative registry for (1) off-chain KMS nodes and\n(2) dedicated governance contracts (i.e., AppAuth) for TEE applications.  It is worth noting that the\nDstack-Gateway can be regarded as a special TEE application that attests and forwards requests to\nother user applications while maintaining consistent verification procedures.\nThe  KmsAuth  contract  records  both  the  measurements  of  off-chain  KMS  node  programs  (KMS\ndigest, which is the hash of the docker compose file and the images used in In-CC Build) and the TDX\n14\nFigure 9:  The verification chain from authoritative registries to runtime measurements\nQuote of the first KMS node, which acts as the primary key generator.  The identities of subsequent\nKMS  nodes  must  first  be  registered  in  KmsAuth  and  verified  by  the  first  KMS  node  before  they\ncan participate in key generation.  These data, together with the open-source Dstack-KMS codebase,\nallow users to verify the integrity of the KMS nodes and their code correctness.  Subsequently,  the\noff-chain KMS nodes can be considered trusted extensions and used to verify Quotes from other TEE\napplications,  which  cannot  be  achieved  by  the  on-chain  governance  contract  alone.   The  off-chain\nKMS nodes are responsible for generating and managing cryptographic keys (i.e., the root key) and\nthe corresponding certificates (explained in Section 2.3.1), which are further used to authorize TEE\napplications after they are verified, thereby avoiding redundant verification.\nSecond, users can verify the validity of Dstack-Gateway.  By default, this is delegated to the off-\nchain  KMS  nodes  during  gateway  registration,  although  users  can  always  request  the  Quote  of  the\ngateway and check the digest of its docker compose file in its governance contract and the codebase.\nAfter the KMS nodes verify the gateway, it will generate its application root key along with a certificate\nchain ending with the root certificate.\nNext, users can access the TEE application through Dstack-Gateway forwarding.  In this case, users\neffectively delegate the verification of the key generation application to the gateway.  The deployment\nof the key generation application starts from the KmsAuth contract.  The deployer first registers it\nand stores the digest (the hash of the docker compose file and the images) on the dedicated AppAuth\ncontract.  Then, as in the previous step, the off-chain KMS nodes verify the Quote of the application\nafter  it  is  deployed  to  the  TEE  and  ensure  it  matches  the  registered  digest.   Only  after  successful\nverification will the key be generated along with the certificate chain.  To be forwarded by the gateway,\nthe application must also register with it.  In this case, the gateway verifies the application’s certificate\nchain and ensures it shares the same root certificate, indicating authorization by the same KMS.\nFinally, the user can invoke the application and request proof of the key it generated.  The applica-\ntion can generate a Quote on demand, with the generated public key included as custom data in the\nQuote.\n15\n3.5    Security Analysis:  Mitigating Threats\nOur key generation example demonstrates Dstack’s comprehensive approach to security across multiple\nattack surfaces.  At the application level, the system prevents unauthorized code deployment through\nrigorous  measurement  verification  against  the  AppAuth  registry.   The  In-CC  Build  process  ensures\nall dependencies originate from verified sources,  while any updates require new registry entries and\ncomplete re-verification.  It is important to note, however, that code audit and review processes remain\nessential for ensuring application code correctness, as the In-CC Build only guarantees the integrity of\nthe build process.\nInfrastructure security is maintained through multiple mechanisms.  TDX Quotes verify Dstack-OS\nintegrity, preventing OS-level tampering.  KMS updates require multi-signature governance approval,\nsafeguarding against unauthorized changes to key management services.  The Quote verification pro-\ncess  includes  firmware  version  validation,  ensuring  applications  run  on  up-to-date  TEE  hardware.\nHardware-backed TDX Quotes effectively prevent attestation spoofing attempts.\nNetwork-level threats are mitigated through the certificate chain validation system.  This prevents\nboth  DNS  hijacking  and  man-in-the-middle  attacks  by  ensuring  authentic  application  identity  and\nenabling end-to-end encryption with verified certificates.  The combination of these security measures\nensures that cryptographic keys maintain their integrity guarantees even when confronted with sophis-\nticated attacks targeting different system layers.\nReferences\n16"
      }
    ]
  },
  {
    "role": "assistant",
    "content": "# Project Proposal Template\n\n## General Information\n1.1. Name of Project\nDstack\n\n1.2. Project Description (what it does, why it is valuable, origin and history)\nDstack is a developer-friendly and security-first SDK that simplifies the deployment of arbitrary containerized applications into Trusted Execution Environments (TEEs). It enables developers to securely deploy containerized applications in TEEs in minutes using familiar tools like docker-compose.yaml. Dstack provides safe management of secrets and sensitive data, along with built-in TLS termination for exposed services.\n\nThe project was built by Kevin Wang and others from Phala Network, inspired by Andrew Miller (Flashbots & Teleport), and has received contributions from Nethermind and many others. Dstack addresses the gap between raw TEE technology and Zero Trust platform requirements by providing portable confidential containers, decentralized code management, and verifiable domain management.\n\n1.3. How does this project align with the Consortium's Mission Statement\n[blank]\n\n1.4. Project website URL\nhttps://docs.phala.network/dstack/overview (inferred from documentation references)\n\n1.5. Social media accounts\n[blank]\n\n## Legal Information\n2.1. Project Logo URL or attachment (Vector Graphic: SVG, EPS).\n[blank]\n\n2.2. Project license. We recommend an OSI-approved license, so if the license is not one on the list, explain why.\nApache License, Version 2.0\n\n2.3. Existing financial sponsorship.\n[blank]\n\n2.4. Trademark status.\n[blank]\n\n## Technical Information\n3.1. High level assessment of project synergy with existing projects under the CCC, including how the project compliments/overlaps with existing projects, and potential ways to harmonize over time. Responses may be included both inline and/or in accompanying documentation.\n[blank]\n\n3.2. Describe the Trusted Computing Base (TCB) of the project. If the project supports multiple environments please describe each TCB. Also identify if dependencies of other project (both CCC or non-CCC) TCBs are taken.\nDstack's TCB includes:\n- Dstack-OS: A minimized operating system image that serves as a hardware abstraction layer\n- OVMF (Open Virtual Machine Firmware): Configures VM hardware specifications\n- Linux kernel with initial ramdisk (initrd)\n- Root filesystem with essential system libraries and tools\n- Intel TDX or equivalent TEE hardware as the foundation\n\nThe system establishes a secure and verifiable startup chain from TEE hardware through to user applications, with each component measuring the next and recording measurements in hardware registers that are incorporated into TEE attestation reports.\n\n3.3. Project Code of Conduct URL. We recommend a Contributor Covenant v2.0 based Code of Conduct, so if the Code of Conduct is not based on that, explain why.\n[blank]\n\n3.4. Source control URL\nhttps://github.com/Dstack-TEE/dstack\n\n3.5. Issue tracker URL\nhttps://github.com/Dstack-TEE/dstack/issues (inferred)\n\n3.6. External dependencies (including licenses, and indicate whether each is a build time or runtime dependency)\n- Intel TDX or equivalent TEE hardware (runtime)\n- Linux kernel (runtime)\n- Docker/container runtime (runtime)\n- Busybox (runtime)\n- LUKS for encryption (runtime)\n- Wireguard-tools (build time)\n- Build-essential, chrpath, diffstat, lz4, xorriso (build time)\n- Rust (build time)\n\n3.7. Standards implemented by the project, if any. Include links to any such standards.\n- TLS/HTTPS for secure communications\n- Certificate Transparency (CT) for certificate monitoring\n- Certificate Authority Authorization (CAA) for domain security\n- Remote Attestation for TEE verification\n\n3.8. Release methodology and mechanics\n[blank]\n\n3.9. Names of initial committers, if different from those submitting proposal\nInitial committers include:\n- Kevin Wang (kvinwang)\n- Shelven Zhou (shelvenzhou)\n- Leechael\n\n3.10. List of project's official communication channels (slack, irc, mailing lists)\n[blank]\n\n3.11. Project Security Response Policy\n[blank]\n\n3.12. Preferred maturity level (Incubation, Graduation, or Emeritus)\n[blank]\n\n3.13. Any additional information the TAC and Board should take into consideration when reviewing your proposal.\nDstack includes several key components:\n- dstack-vmm: Service running on bare TDX host to manage CVMs\n- dstack-gateway: Reverse proxy to forward TLS connections to CVMs\n- dstack-kms: KMS server to generate keys for CVMs\n- dstack-guest-agent: Service in CVM to serve containers' key derivation and attestation requests\n- meta-dstack: Yocto meta layer to build CVM guest images\n\nThe project provides innovative solutions for portable confidential containers, decentralized code management, and verifiable domain management, addressing critical limitations in current TEE implementations for Web3 contexts."
  },
  {
    "role": "user",
    "content": "You can simplify the 3.2 answers. Just dstack code base, TDX and other TEE solutions that we will support in the future\n"
  }
]

Response:

## Technical Information 3.2. Describe the Trusted Computing Base (TCB) of the project. If the project supports multiple environments please describe each TCB. Also identify if dependencies of other project (both CCC or non-CCC) TCBs are taken. The TCB consists of the Dstack codebase, Intel TDX, and other TEE solutions that will be supported in the future.

Model: claude-3-7-sonnet-202502192025-06-25 13:13:07

Context:

[
  {
    "role": "user",
    "content": [
      {
        "type": "text",
        "text": "Help me fill in the follow template given the project whitepaper and README file.\n\nFor fields with not enough info, leave it \"[blank]\".\n\n```\nProject Proposal Template\n\nGeneral Information\n1.1. Name of Project\n1.2. Project Description (what it does, why it is valuable, origin and history)\n1.3. How does this project align with the Consortium's Mission Statement\n1.4. Project website URL\n1.5. Social media accounts\n\nLegal Information\n2.1. Project Logo URL or attachment (Vector Graphic: SVG, EPS).\n2.2. Project license. We recommend an OSI-approved license, so if the license is not one on the list, explain why.\n2.3. Existing financial sponsorship.\n2.4. Trademark status.\n\nTechnical Information\n3.1. High level assessment of project synergy with existing projects under the CCC, including how the project compliments/overlaps with existing projects, and potential ways to harmonize over time. Responses may be included both inline and/or in accompanying documentation.\n3.2. Describe the Trusted Computing Base (TCB) of the project. If the project supports multiple environments please describe each TCB. Also identify if dependencies of other project (both CCC or non-CCC) TCBs are taken.\n3.3. Project Code of Conduct URL. We recommend a Contributor Covenant v2.0 based Code of Conduct, so if the Code of Conduct is not based on that, explain why.\n3.4. Source control URL\n3.5. Issue tracker URL\n3.6. External dependencies (including licenses, and indicate whether each is a build time or runtime dependency)\n3.7. Standards implemented by the project, if any. Include links to any such standards.\n3.8. Release methodology and mechanics\n3.9. Names of initial committers, if different from those submitting proposal\n3.10. List of project's official communication channels (slack, irc, mailing lists)\n3.11. Project Security Response Policy\n3.12. Preferred maturity level (Incubation, Graduation, or Emeritus) 3.13. Any additional information the TAC and Board should take into consideration when reviewing your proposal.\n```"
      },
      {
        "type": "text",
        "text": "README.md\n# Dstack\n\n[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/Dstack-TEE/dstack)\n\nDstack is a **developer friendly** and **security first** SDK to simplify the deployment of arbitrary containerized apps into TEE.\n\nMain features:\n\n- 🔒 Deploy containerized apps securely in TEE in minutes\n- 🛠️ Use familiar tools - just write a docker-compose.yaml\n- 🔑 Safely manage secrets and sensitive data\n- 📡 Expose services via built-in TLS termination\n\nDstack is community driven. Open sourced and built by [Kevin Wang](https://github.com/kvinwang) and many others from [Phala Network](https://github.com/Phala-Network), inspired by [Andrew Miller](https://github.com/amiller) (Flashbots & Teleport), and contributed by [Nethermind](https://github.com/NethermindEth/nethermind) and [many others](#contributors).\n\n![Alt](https://repobeats.axiom.co/api/embed/0a001cc3c1f387fae08172a9e116b0ec367b8971.svg \"Repobeats analytics image\")\n\n# Overview\n\nComponents in Dstack:\n\n- `dstack-vmm`: A service running in bare TDX host to manage CVMs\n- `dstack-gateway`: A reverse proxy to forward TLS connections to CVMs\n- `dstack-kms`: A KMS server to generate keys for CVMs\n- `dstack-guest-agent`: A service running in CVM to serve containers' key derivation and attestation requests\n- `meta-dstack`: A Yocto meta layer to build CVM guest images\n\nThe overall architecture is shown below:\n![arch](./docs/assets/arch.png)\n\n# Directory structure\n\n```text\ndstack/\n    kms/                         A prototype KMS server\n    guest-agent/                 A service running in CVM to serve containers' key derivation and attestation requests.\n    dstack-util/                 A CLI tool in the guest setting up the system, getting TDX quote, extending RTMR, generating cert for RA-TLS, etc.\n    vmm/                         A service running in bare TDX host to manage CVMs\n    gateway/                     A reverse proxy to forward TLS connections to CVMs\n    certbot/                     A tool to automatically obtain and renew TLS certificates for dstack-gateway\n    ra-rpc/                      RA-TLS support for pRPC\n    ra-tls/                      RA-TLS support library\n    tdx-attest/                  Guest library for getting TDX quote and extending RTMR\n```\n\n# Build and play locally\n\n## Prerequisites\n\n- A bare metal TDX server setup following [canonical/tdx](https://github.com/canonical/tdx)\n- Public IPv4 address assigned to the machine\n- At least 16GB RAM, 100GB free disk space.\n- A domain with DNS access if you want to set up `dstack-gateway` for Zero Trust HTTPS\n\n> [!NOTE]\n>\n> This doc assumes you have access to a compatible Intel TDX Server ready to be configured with Dstack. Check the [Hardware Requirements](https://docs.phala.network/dstack/hardware-requirements) for more information on buying a bare metal server or renting a server from OVH. To start learning about Dstack check out the [docs](https://docs.phala.network/dstack/overview).\n>\n> If you are looking to deploy a CVM in minutes, go to the docs to learn how to [sign-up for a Phala Cloud Account](https://docs.phala.network/phala-cloud/getting-started/sign-up-for-cloud-account) and [deploy your first CVM on Dstack]((https://docs.phala.network/phala-cloud/getting-started/start-from-cloud-ui)).\n\n## Install dependencies\n\n```bash\n# for Ubuntu 24.04\nsudo apt install -y build-essential chrpath diffstat lz4 wireguard-tools xorriso\n# install rust\ncurl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh\n```\n\n## Build and run for local development\n\n### Build the artifacts\n```bash\ngit clone https://github.com/Dstack-TEE/meta-dstack.git --recursive\ncd meta-dstack/\n\nmkdir build\ncd build\n../build.sh hostcfg\n# This outputs the following message:\n# Config file ../build-config.sh created, please edit it to configure the build\n\nvim ./build-config.sh\n```\n\nReview and customize the `build-config.sh` configuration file according to your environment requirements. The file contains network ports, domain settings, and other important parameters. Once configured, run the build script again to generate the necessary artifacts:\n\n```bash\n../build.sh hostcfg\n\n# If everything is okay, you should see the built artifacts in the `build` directory.\n$ ls\ncerts  images  dstack-kms  kms.toml  run  dstack-vmm  vmm.toml  dstack-gateway  gateway.toml\n```\n\n### Download guest image or build guest image from source\n\n```bash\n# This will download the guest image from the release page.\n../build.sh dl 0.5.2\n```\n\nOr build guest image from source:\n\n```bash\n# This will build the guest image from source using the yocto meta layer. This will take a while.\n../build.sh guest\n```\n\n> **Note on Reproducible Builds**: The build command above does not guarantee reproducibility. For reproducible builds across different build environments, please refer to the [reproducible build instructions](https://github.com/Dstack-TEE/meta-dstack?tab=readme-ov-file#reproducible-build-the-guest-image) in the meta-dstack repository.\n\n### Run components\nNow you can open 3 terminals to start the components:\n\n1. Run `./dstack-kms -c kms.toml`\n2. Run `sudo ./dstack-gateway -c gateway.toml`\n3. Run `./dstack-vmm -c vmm.toml`\n\n⚠️ *Warning: this is for local development, and the kms is not secure, so you should not use it in production.*\nFor production, you should follow the [deployment guide](./docs/deployment.md) and read the [security guide](./docs/security-guide/security-guide.md).\n\n## Deploy an App\nOpen the dstack-vmm webpage [http://localhost:9080](http://localhost:9080)(change the port according to your configuration) on your local machine to deploy a `docker-compose.yaml` file:\n\n![vmm](./docs/assets/vmm.png)\n\nAfter the container deployed, it should need some time to start the CVM and the containers. Time would be vary depending on your workload.\n\n- Click the [Logs] button to see the logs of the CVM, you can see if the container is finished starting there.\n\n- Once the container is running, you can click the [Dashboard] button to see some information of the container. And the logs of the containers can be seen in the [Dashboard] page.\n\n    ![dstack-guest-agent](./docs/assets/guest-agent.png)\n\n- You can open dstack-gateway's dashboard at [https://localhost:9070](https://localhost:9070) to see the CVM's wireguard ip address, as shown below:\n\n![dstack-gateway](./docs/assets/gateway.png)\n\n## Pass Secrets to Apps\nWhen deploying a new App, you can pass private data via Encrypted Environment Variables. These variables can be referenced in the docker-compose.yaml file as shown below:\n\n![secret](./docs/assets/secret.png)\n\nThe environment variables will be encrypted in the client-side and decrypted in the CVM before being passed to the containers.\n\n## Access the App\n\nOnce the app is deployed and listening on an HTTP port, you can access the HTTP service via dstack-gateway's public domain. The ingress mapping rules are:\n\n- `<id>[s].<base_domain>` maps to port `80` or `443` if with `s` in the CVM.\n- `<id>-<port>[s].<base_domain>` maps to port `<port>` in the CVM.\n\nFor example, `3327603e03f5bd1f830812ca4a789277fc31f577-8080.app.kvin.wang` maps to port `8080` in the CVM.\n\nWhere the `<id>` can be either the app id or the instance id. If the app id is used, one of the instances will be selected by the load balancer.\nIf the `id-port` part ends with `s`, it means the TLS connection will be passthrough to the app rather than terminating at dstack-gateway.\n\nYou can also ssh into the CVM to inspect more information, if your deployment uses the image `dstack-x.x.x-dev`:\n\n```bash\n# The IP address of the CVM can be found in the dstack-gateway dashboard.\nssh [email protected]\n```\n\n## Getting TDX quote in docker container\n\nTo get a TDX quote within app containers:\n\n1. Mount `/var/run/dstack.sock` to the target container in `docker-compose.yaml`\n\n    ```yaml\n    version: '3'\n    services:\n    nginx:\n        image: nginx:latest\n        volumes:\n        - /var/run/dstack.sock:/var/run/dstack.sock\n        ports:\n        - \"8080:80\"\n        restart: always\n    ```\n\n2. Execute the quote request command in the container.\n\n    ```bash\n    # The argument report_data accepts binary data encoding in hex string.\n    # The actual report_data passing the to the underlying TDX driver is sha2_256(report_data).\n    curl --unix-socket /var/run/dstack.sock http://localhost/GetQuote?report_data=0x1234deadbeef | jq .  \n    ```\n\n## Container logs\n\nContainer logs can be obtained from the CVM's `dashboard` page or by curl:\n\n```bash\ncurl 'http://<appid>.app.kvin.wang:9090/logs/<container name>?since=0&until=0&follow=true&text=true&timestamps=true&bare=true'\n```\n\nReplace `<appid>` and `<container name>` with actual values. Available parameters:\n\n- since=0: Starting Unix timestamp for log retrieval\n- until=0: Ending Unix timestamp for log retrieval\n- follow: Enables continuous log streaming\n- text: Returns human-readable text instead of base64 encoding\n- timestamps: Adds timestamps to each log line\n- bare: Returns the raw log lines without json format\n\nThe response of the RPC looks like:\n```\n$ curl 'http://0.0.0.0:9190/logs/zk-provider-server?text&timestamps'\n{\"channel\":\"stdout\",\"message\":\"2024-09-29T03:05:45.209507046Z Initializing Rust backend...\\n\"}\n{\"channel\":\"stdout\",\"message\":\"2024-09-29T03:05:45.209543047Z Calling Rust function: init\\n\"}\n{\"channel\":\"stdout\",\"message\":\"2024-09-29T03:05:45.209544957Z [2024-09-29T03:05:44Z INFO  rust_prover] Initializing...\\n\"}\n{\"channel\":\"stdout\",\"message\":\"2024-09-29T03:05:45.209546381Z [2024-09-29T03:05:44Z INFO  rust_prover::groth16] Starting setup process\\n\"}\n```\n\n## TLS Passthrough with Custom Domain\n\ndstack-gateway supports TLS passthrough for custom domains.\n\nSee the example [here](https://github.com/Dstack-TEE/dstack-examples/tree/main/custom-domain/dstack-ingress) for more details.\n\n## Upgrade an App\n\nGot to the dstack-vmm webpage, click the [Upgrade] button, select or paste the compose file you want to upgrade to, and click the [Upgrade] button again.\nThe app id does not change after the upgrade. Stop and start the app to apply the upgrade.\n\n## HTTPS Certificate Transparency\n\nIn the tutorial above, we used a TLS certificate with a private key external to the TEE. To establish trust, we need to generate and maintain the certificate's private key within the TEE and provide evidence that all TLS certificates for the domain were originate solely from dstack-gateway CVM.\n\nBy combining Certificate Transparency Logs and CAA DNS records, we can make best effort to minimize security risks. Here's our approach:\n\n- Set CAA records to allow only the account created in dstack-gateway CVM to request Certificates.\n- Launch a program to monitor Certificate Transparency Log and give alarm once any certificate issued to a pubkey that isn’t generated by dstack-gateway CVM.\n\n### Configurations\n\nTo launch Certbot, you need to own a domain hosted on Cloudflare. Obtain an API token with DNS operation permissions from the Cloudflare dashboard. Configure it in the `build-config.sh`:\n\n```bash\n# The directory to store the auto obtained TLS certificate and key\nGATEWAY_CERT=${CERBOT_WORKDIR}/live/cert.pem\nGATEWAY_KEY=${CERBOT_WORKDIR}/live/key.pem\n\n# for certbot\nCF_ZONE_ID=cc0a40...\nCF_API_TOKEN=g-DwMH...\n# ACME_URL=https://acme-v02.api.letsencrypt.org/directory\nACME_URL=https://acme-staging-v02.api.letsencrypt.org/directory\n```\n\nThen re-run the ../build.sh:\n\n```bash\n../build.sh\n```\n\n### Launch certbot\n\nThen run the certbot in the `build/` and you will see the following log:\n```text\n$ RUST_LOG=info,certbot=debug ./certbot renew -c certbot.toml\n2024-10-25T07:41:00.682990Z  INFO certbot::bot: creating new ACME account\n2024-10-25T07:41:00.869246Z  INFO certbot::bot: created new ACME account: https://acme-staging-v02.api.letsencrypt.org/acme/acct/168601853\n2024-10-25T07:41:00.869270Z  INFO certbot::bot: setting CAA records\n2024-10-25T07:41:00.869276Z DEBUG certbot::acme_client: setting guard CAA records for app.kvin.wang\n2024-10-25T07:41:01.740767Z DEBUG certbot::acme_client: removing existing CAA record app.kvin.wang 0 issuewild \"letsencrypt.org;validationmethods=dns-01;accounturi=https://acme-staging-v02.api.letsencrypt.org/acme/acct/168578683\"\n2024-10-25T07:41:01.991298Z DEBUG certbot::acme_client: removing existing CAA record app.kvin.wang 0 issue \"letsencrypt.org;validationmethods=dns-01;accounturi=https://acme-staging-v02.api.letsencrypt.org/acme/acct/168578683\"\n2024-10-25T07:41:02.216751Z DEBUG certbot::acme_client: setting CAA records for app.kvin.wang, 0 issue \"letsencrypt.org;validationmethods=dns-01;accounturi=https://acme-staging-v02.api.letsencrypt.org/acme/acct/168601853\"\n2024-10-25T07:41:02.424217Z DEBUG certbot::acme_client: setting CAA records for app.kvin.wang, 0 issuewild \"letsencrypt.org;validationmethods=dns-01;accounturi=https://acme-staging-v02.api.letsencrypt.org/acme/acct/168601853\"\n2024-10-25T07:41:02.663824Z DEBUG certbot::acme_client: removing guard CAA records for app.kvin.wang\n2024-10-25T07:41:03.095564Z DEBUG certbot::acme_client: generating new cert key pair\n2024-10-25T07:41:03.095678Z DEBUG certbot::acme_client: requesting new certificates for *.app.kvin.wang\n2024-10-25T07:41:03.095699Z DEBUG certbot::acme_client: creating new order\n2024-10-25T07:41:03.250382Z DEBUG certbot::acme_client: order is pending, waiting for authorization\n2024-10-25T07:41:03.283600Z DEBUG certbot::acme_client: creating dns record for app.kvin.wang\n2024-10-25T07:41:04.027882Z DEBUG certbot::acme_client: challenge not found, waiting 500ms tries=2 domain=\"_acme-challenge.app.kvin.wang\"\n2024-10-25T07:41:04.600711Z DEBUG certbot::acme_client: challenge not found, waiting 1s tries=3 domain=\"_acme-challenge.app.kvin.wang\"\n2024-10-25T07:41:05.642300Z DEBUG certbot::acme_client: challenge not found, waiting 2s tries=4 domain=\"_acme-challenge.app.kvin.wang\"\n2024-10-25T07:41:07.715947Z DEBUG certbot::acme_client: challenge not found, waiting 4s tries=5 domain=\"_acme-challenge.app.kvin.wang\"\n2024-10-25T07:41:11.724831Z DEBUG certbot::acme_client: challenge not found, waiting 8s tries=6 domain=\"_acme-challenge.app.kvin.wang\"\n2024-10-25T07:41:19.815990Z DEBUG certbot::acme_client: challenge not found, waiting 16s tries=7 domain=\"_acme-challenge.app.kvin.wang\"\n2024-10-25T07:41:35.852790Z DEBUG certbot::acme_client: setting challenge ready for https://acme-staging-v02.api.letsencrypt.org/acme/chall-v3/14584884443/mQ-I2A\n2024-10-25T07:41:35.934425Z DEBUG certbot::acme_client: challenges are ready, waiting for order to be ready\n2024-10-25T07:41:37.972434Z DEBUG certbot::acme_client: order is ready, uploading csr\n2024-10-25T07:41:38.052901Z DEBUG certbot::acme_client: order is processing, waiting for challenge to be accepted\n2024-10-25T07:41:40.088190Z DEBUG certbot::acme_client: order is valid, getting certificate\n2024-10-25T07:41:40.125988Z DEBUG certbot::acme_client: removing dns record 6ab5724e8fa7e3e8f14e93333a98866a\n2024-10-25T07:41:40.377379Z DEBUG certbot::acme_client: stored new cert in /home/kvin/codes/meta-dstack/dstack/build/run/certbot/backup/2024-10-25T07:41:40.377174477Z\n2024-10-25T07:41:40.377472Z  INFO certbot::bot: checking if certificate needs to be renewed\n2024-10-25T07:41:40.377719Z DEBUG certbot::acme_client: will expire in Duration { seconds: 7772486, nanoseconds: 622281542 }\n2024-10-25T07:41:40.377752Z  INFO certbot::bot: certificate /home/kvin/codes/meta-dstack/dstack/build/run/certbot/live/cert.pem is up to date\n```\n\nWhere the command did are:\n\n- Registered to letsencrypt and got a new account `https://acme-staging-v02.api.letsencrypt.org/acme/acct/168601853`\n- Auto set CAA records for the domain on cloudflare, you can open the CF dashboard to see the record:\n\n    ![certbot-caa](./docs/assets/certbot-caa.png)\n\n- Auto requested a new certificate from Let's Encrypt. Automatically renews the certificate to maintain its validity\n\n### Launch dstack-gateway\n\nExecute dstack-gateway with `sudo ./dstack-gateway -c gateway.toml`, then access the web portal to check the dstack-gateway CVM managed Let's Encrypt account. The account's private key remains securely sealed within the TEE.\n\n![gateway-accountid](./docs/assets/gateway-accountid.png)\n\n## Certificate transparency log monitor\n\nTo enhance security, we've limited TLS certificate issuance to dstack-gateway via CAA records. However, since these records can be modified through Cloudflare's domain management, we need to implement global CA certificate monitoring to maintain security oversight.\n\n`ct_monitor` tracks Certificate Transparency logs via [https://crt.sh](https://crt.sh/?q=app.kvin.wang), comparing their public key with the ones got from dstack-gateway RPC. It immediately alerts when detecting unauthorized certificates not issued through dstack-gateway:\n\n```text\n$ ./ct_monitor -t https://localhost:9010/prpc -d app.kvin.wang\n2024-10-25T08:12:11.366463Z  INFO ct_monitor: monitoring app.kvin.wang...\n2024-10-25T08:12:11.366488Z  INFO ct_monitor: fetching known public keys from https://localhost:9010/prpc\n2024-10-25T08:12:11.566222Z  INFO ct_monitor: got 2 known public keys\n2024-10-25T08:12:13.142122Z  INFO ct_monitor: ✅ checked log id=14705660685\n2024-10-25T08:12:13.802573Z  INFO ct_monitor: ✅ checked log id=14705656674\n2024-10-25T08:12:14.494944Z ERROR ct_monitor: ❌ error in CTLog { id: 14666084839, issuer_ca_id: 295815, issuer_name: \"C=US, O=Let's Encrypt, CN=R11\", common_name: \"kvin.wang\", name_value: \"*.app.kvin.wang\", not_before: \"2024-09-24T02:23:15\", not_after: \"2024-12-23T02:23:14\", serial_number: \"03ae796f56a933c8ff7e32c7c0d662a253d4\", result_count: 1, entry_timestamp: \"2024-09-24T03:21:45.825\" }\n2024-10-25T08:12:14.494998Z ERROR ct_monitor: error: certificate has issued to unknown pubkey: 30820122300d06092a864886f70d01010105000382010f003082010a02820101009de65c767caf117880626d1acc1ee78f3c6a992e3fe458f34066f92812ac550190a67e49ebf4f537003c393c000a8ec3e114da088c0cb02ffd0881fd39a2b32cc60d2e9989f0efab3345bee418262e0179d307d8d361fd0837f85d17eab92ec6f4126247e614aa01f4efcc05bc6303a8be68230f04326c9e85406fc4d234e9ce92089253b11d002cdf325582df45d5da42981cd546cbd2e9e49f0fa6636e747a345aaf8cefa02556aa258e1f7f90906be8fe51567ac9626f35bc46837e4f3203387fee59c71cea400000007c24e7537debc1941b36ff1612990233e4c219632e35858b1771f17a71944adf6c657dd7303583e3aeed199bd36a3152f49980f4f30203010001\n```\n\n# Troubleshooting\n\n### Error from dstack-vmm: qemu-system-x86_64: -device vhost-vsock-pci,guest-cid=<id>: vhost-vsock: unable to set guest cid: Address already in use\n\n`dstack-vmm` may throw this error when creating a new VM if the [Unix Socket CID](https://man7.org/linux/man-pages/man7/vsock.7.html) is occupied. To solve the problem, first, you should list the occupied CID:\n\n```bash\nps aux | grep 'guest-cid='\n```\n\nThen choose a new range of the CID not conflicting with the CID in use. You can change `build/vmm.toml` file and restart `dstack-vmm`. This error should disappear. For example, you may find 33000-34000 free to use:\n\n```toml\n[cvm]\ncid_start = 33000\ncid_pool_size = 1000\n```\n\nWhen building the dstack from scratch, you should change the CID configs in `build-config.sh` instead, because `vmm.toml` file is generated by `build.sh`. Its content is derived from `build-config.sh`.\n\nYou may encounter this problem when upgrading from an older version of dstack, because CID was introduced in `build-config.sh` in later versions. In such case, please follow the docs to add the missing entries in `build-config.sh` and rebuild dstack.\n\n### Error: Operation not permitted when building guest image\n\nWhen running `../build.sh guest`, you might encounter this error:\n\n```\nTraceback (most recent call last):\n  File \"/meta-dstack/poky/bitbake/bin/bitbake-worker\", line 278, in child\n    bb.utils.disable_network(uid, gid)\n  File \"/meta-dstack/poky/bitbake/lib/bb/utils.py\", line 1696, in disable_network\n    with open(\"/proc/self/uid_map\", \"w\") as f:\nPermissionError: [Errno 1] Operation not permitted\n```\n\nThis error occurs because Ubuntu 23.10 and later versions restrict unprivileged user namespaces by default. To fix this, run:\n\n```bash\nsudo sysctl kernel.apparmor_restrict_unprivileged_userns=0\n```\n\nThen try building again. For more information about this restriction, see the [Ubuntu discourse post](https://discourse.ubuntu.com/t/spec-unprivileged-user-namespace-restrictions-via-apparmor-in-ubuntu-23-10/37626).\n\n\n# Contributors\n\nDstack is proudly built by open source and Pi-rateship contributors:\n\n- Phala Network: [Kevin Wang](https://github.com/kvinwang), [Shelven Zhou](https://github.com/shelvenzhou), [Leechael](https://github.com/leechael)\n- Teleport: [Andrew Miller](https://github.com/amiller), [Sxy Sun](https://github.com/sxysun)\n- Flashbots: [Tina](https://github.com/CarboClanC), [Mateusz](https://github.com/Ruteri), [Dmarz](https://github.com/dmarzzz), [Moe](https://github.com/MoeMahhouk)\n- Ithaca: [Georgios](https://github.com/gakonst)\n- Fabric: [@gaoist](https://x.com/gaoist)\n- And many more...\n\nThe inspiration for this work stems from [Andrew Miller](https://github.com/amiller)’s pioneering concept of a [Docker-based P2P TEE SDK](https://collective.flashbots.net/t/dstack-speedrunning-a-p2p-confidential-vm/3876).\n\nThis project cannot be built without standing on the shoulders of giants:\n\n- [konvera/meta-confidential-compute](https://github.com/konvera/meta-confidential-compute)\n\nSpecial acknowledgment to [Flashbots](https://github.com/flashbots) for building a community around TEE. The TEE Hacker House initiative, organized by [Flashbots](https://github.com/flashbots) and led by [Tina](https://github.com/CarboClanC), has brought together TEE builders to develop tools for TEE-Web3 integration. This collaborative journey has generated invaluable insights for advancing secure, confidential environments within Web3.\n\nTogether, we’re shaping the future of TEE in Web3, paving the way for more secure and developer-accessible confidential computing!\n\nFor a full list of the direct contributors to this repo, see [Contributors](https://github.com/Dstack-TEE/dstack/contributors) on GitHub.\n\n\n# License\n\nCopyright 2024 Phala Network and Contributors.\n\nLicensed under the Apache License, Version 2.0 (the \"License\"); you may not use this file except in compliance with the License. You may obtain a copy of the License at\n\n[http://www.apache.org/licenses/LICENSE-2.0](http://www.apache.org/licenses/LICENSE-2.0)"
      },
      {
        "type": "text",
        "text": "main.pdf\nDstack:  A Zero Trust Framework for Confidential Containers\nJune 23, 2025\nAbstract\nWeb3 applications require execution platforms that maintain confidentiality and integrity with-\nout relying on centralized trust authorities.  While Trusted Execution Environments (TEEs) offer\npromising capabilities for confidential computing, current implementations face significant limita-\ntions in security reliability, censorship resistance, and vendor independence when applied to Web3\ncontexts.  This paper presents Dstack, a comprehensive framework that transforms raw TEE tech-\nnology  into  a  true  Zero  Trust  platform  aligned  with  Web3  principles.   We  introduce  three  key\ninnovations:  (1) Portable Confidential Containers that enable seamless workload migration across\nheterogeneous TEE environments while maintaining security guarantees, (2) Decentralized Code\nManagement that leverages smart contracts for transparent governance of TEE applications, and\n(3) Verifiable Domain Management that ensures secure and verifiable application identity without\ncentralized authorities. Through these innovations, implemented via Dstack-OS, Dstack-KMS, and\nDstack-Gateway components, we demonstrate how to achieve both the performance advantages of\nVM-level TEE solutions and the trustless guarantees required by Web3 applications.  Our evalu-\nation shows that Dstack provides comprehensive security guarantees while maintaining practical\nusability for real-world applications.\n1    Introduction\nThe Web3 ecosystem represents a paradigm shift in digital trust models, fundamentally transforming\nthe relationship between users and application developers.  Unlike traditional systems, Web3 empowers\nusers with unprecedented control over their data through the principle of ”Code is Law” - once deployed,\ncode  operates  autonomously  and  independently  of  external  control.   This  transformation  demands\nrobust execution platforms that maintain confidentiality and integrity without relying on centralized\ntrust authorities.\nFigure 1:  The evolution of trust models from Web2 to Web3, highlighting the shift from centralized control\nto decentralized governance and execution.\nThe contrast between Web2 and Web3 architectures in Figure 1 illustrates this fundamental shift.\nIn Web2 systems, developers maintain complete control through proprietary applications and central-\nized servers, retaining administrative privileges to access and modify user data at will.  Web3’s smart\n1\ncontracts,  however,  represent  the  first  significant  step  toward  true  trustlessness  by  executing  pro-\ngrams on decentralized platforms (blockchains).  Once deployed, administrators cannot influence pro-\ngram execution, and lifecycle management (e.g., code updates) follows predefined agreements through\ndemocratic governance mechanisms like multi-signature wallets and Decentralized Autonomous Orga-\nnizations (DAOs).  This emerging trust model extends beyond basic applications to mission-critical\nscenarios such as AI model training, where data providers and model developers often have competing\ninterests,  and  autonomous  AI  agents  designed  to  operate  independently  of  human  intervention.   In\nthese  contexts,  Zero  Trust  platforms  become  essential  to  host  applications  and  enforce  verification\nmechanisms that appropriately constrain developer authority.\nA Zero Trust platform must enforce the following key principles:\n•  Code is Law: This manifests in two dimensions: (1) the application logic, once deployed, cannot\nbe  changed  unexpectedly;  and  (2)  the  lifecycle  management  of  code—including  deployment,\nupgrades, and deletion—follows predefined governance rules.\n•  Censorship Resistance:  User data remains beyond the control of any single entity, with data\navailability protected against Denial-of-Service attacks.\n•  Full Chain-of-Trust:  When users interact with applications on a Zero Trust platform,  they\nmust be able to verify all aspects of that application, including network setup, application identity\nand code logic, underlying hardware, and execution environment.\n•  Assume Breach:  The platform operates under the assumption that compromises will occur,\nimplementing  mechanisms  for  damage  containment,  rapid  recovery,  and  minimization  of  data\nexposure during security incidents.\nConfidential Computing, particularly through Trusted Execution Environments (TEEs), has emerged\nas a promising foundation for extending blockchain capabilities to support complex computational tasks\nwith confidentiality guarantees.  Recent advances in VM-level TEE solutions, including Intel TDX and\nAMD SEV, have demonstrated substantial performance improvements and developer-friendly inter-\nfaces,  making  them  compelling  candidates  for  Web3  deployment.   The  integration  of  GPUs  within\nTEEs [?] now enables verifiable execution of both Large Language Models and AI agents, providing\ncryptographic guarantees of computational integrity.\nHowever, a significant gap exists between raw TEE technology and the requirements of a true Zero\nTrust platform.  Current TEE implementations face several critical limitations when applied to Web3\ncontexts:\n•  Security Reliability:  Recent vulnerability discoveries in TEE systems have raised significant con-\ncerns  about  their  effectiveness  as  trust  anchors.   The  persistence  of  side-channel  attacks  and\nmicro-architectural vulnerabilities undermines confidence in TEE security guarantees, particu-\nlarly for high-value Web3 applications where a single compromise could lead to catastrophic data\nexposure.\n•  Censorship Vulnerability:  Conventional TEE encryption schemes bind encryption keys to spe-\ncific  hardware  instances,  creating  single  points  of  failure  that  contradict  Web3’s  requirement\nfor censorship resistance.  This architectural limitation means that data availability cannot be\nguaranteed if specific hardware instances are compromised or become unavailable.\n•  Vendor Dependencies:  Current trust models heavily rely on centralized hardware manufacturers\nand verification processes, introducing risks of vendor lock-in and potential censorship vectors.\nThis centralization contradicts Web3’s core principles of decentralization and trustlessness.\n•  Incomplete Verifiability:  While TEEs provide Remote Attestation capabilities to verify applica-\ntion and hardware identity, they fail to deliver the comprehensive chain of trust required in Zero\nTrust environments.  Users need guarantees that programs will process their data as expected\nand cannot be modified without proper authorization—capabilities beyond current attestation\nmechanisms.\nTo bridge this gap between raw TEE technology and Zero Trust requirements, we present Dstack,\na comprehensive framework for confidential containers that introduces three key innovations:\n2\n•  Portable Confidential Container: Our architecture enables seamless migration of confidential\nworkloads across different TEE instances and hardware vendors,  significantly reducing vendor\nlock-in risks while maintaining robust security guarantees.  This innovation directly addresses the\ncensorship vulnerability and vendor dependency limitations by providing hardware abstraction\nand state continuity across heterogeneous TEE environments.\n•  Decentralized Code Management:  We implement a comprehensive governance framework\nthat leverages smart contracts for transparent and decentralized management of TEE applica-\ntions.  This  system ensures verifiable deployment  and upgrade processes,  enforcing the  “Code\nis Law” principle by binding application lifecycles to on-chain governance decisions.  This inno-\nvation addresses the incomplete verifiability limitation by creating an immutable audit trail of\napplication changes.\n•  Verifiable Domain Management: Our novel approach to certificate management ensures that\nconfidential containers can exclusively control domains and provide native HTTPS support to\nTEE applications without relying on centralized authorities.  This system serves as a middleware\nbetween TEE applications and existing TLS-based networks, enabling users to establish end-to-\nend encrypted channels to TEE applications without modifications to client software.\nThese innovations are implemented through a cohesive system architecture comprising three core\ncomponents:\n•  Dstack-OS: A hardware abstraction layer with a minimized operating system image that elimi-\nnates differences in underlying TEE hardware while reducing the attack surface.  This component\nprovides a consistent, secure runtime environment across diverse TEE implementations.\n•  Dstack-KMS:  A  blockchain-controlled  key  management  service  that  replaces  hardware-based\nencryption schemas with an independent service for generating and managing secret keys.  This\ncomponent  enables  secure  data  migration  across  TEE  instances  and  supports  key  rotation  to\nprovide forward and backward data secrecy, mitigating the impact of potential TEE compromises.\n•  Dstack-Ingress and Dstack-Gateway: Complementary systems providing TEE-controlled domain\nmanagement through different approaches—Dstack-Ingress enables applications to specify cus-\ntom domains with minimal integration requirements, while Dstack-Gateway offers pre-registered\nwildcard domains requiring no application code changes.\nBy addressing the critical limitations of current TEE implementations, Dstack establishes a compre-\nhensive framework that transforms raw TEE technology into a true Zero Trust platform aligned with\nWeb3’s fundamental principles.  Our approach not only enhances the security and reliability of confi-\ndential computing but also provides a practical path toward truly decentralized, censorship-resistant\ninfrastructure for next-generation applications.\nThe remainder of this paper details the technical design of Dstack, evaluates its performance and\nsecurity characteristics, and demonstrates how our innovations collectively create a Zero Trust platform\nthat maintains the performance advantages of VM-level TEE solutions while addressing their inherent\nlimitations in Web3 contexts.\n2    System Design\n2.1    Portable Confidential Container\nContainerization has transformed cloud-native application deployment by providing unparalleled porta-\nbility and scalability through effective data separation.  These capabilities are particularly critical for\nTrusted Execution Environment (TEE) applications, as they directly address the inherent limitations\noutlined in Section 1:\n•  Security Reliability:  Containerized applications can be efficiently transferred from compro-\nmised TEE hardware to secure instances,  preserving code integrity.  Together with our secure\ndata migration mechanism that ensures both forward and backward secrecy, this approach sig-\nnificantly limits privacy leakage risks even when individual TEE instances are compromised.\n3\nFigure 2:  The architecture of Dstack, including Dstack-OS and Dstack-KMS. Dstack-OS provides a hardware\nabstraction layer with a minimized operating system image, while Dstack-KMS replaces the hardware-based\ndata encryption keys with a blockchain-controlled key management service.  TODO: redraw this to put the\ncomponents into solutions.\n•  Censorship Resistance: The architecture’s inherent scalability provides robust defense against\nDenial-of-Service attacks. Additionally, by decoupling data storage from execution environments,\nestablished  data  availability  solutions  can  be  readily  integrated  to  ensure  persistent  access  to\napplication data.\n•  Vendor  Independence:   Our  hardware  abstraction  layer  enables  confidential  containers  to\noperate across diverse TEE hardware platforms without modification, eliminating vendor lock-in\nwhile facilitating rapid adoption of emerging TEE technologies as they become available.\nHowever, implementing truly portable confidential containers presents substantial technical chal-\nlenges that differentiate them from conventional containerization.  Two fundamental obstacles must be\novercome:\nFirst, existing TEE implementations generate data sealing keys derived from hardware-bound root\nkeys unique to each TEE instance.  This architectural design creates an inherent barrier to portability\n— data encrypted by one TEE instance cannot be decrypted by any other, even when running identical\napplication code.  Prior research has largely circumvented this limitation by restricting TEEs to state-\nless applications, but this approach severely constrains their utility in complex real-world scenarios.\nSecond,  TEE implementations from different vendors impose disparate specifications for deploy-\nable programs.  This fragmentation forces developers to create and maintain multiple artifacts across\nplatforms, each requiring separate (and expensive) code reviews to verify functional equivalence — a\nprocess that undermines the trust guarantees central to Web3 applications.\nTo address these challenges comprehensively, we introduce two complementary components: Dstack-\nKMS and Dstack-OS.\n2.1.1    Dstack-KMS: Blockchain-Controlled Secret Derivation\nDstack-KMS  is  a  secret  derivation  service  that  fundamentally  transforms  how  encryption  keys  are\nmanaged in confidential computing environments.  Its primary function is to generate a unique and\nstable secret (the Root Key ) for each application based on its code and configurations.  This root key\n4\nserves as the foundation for deriving additional application-specific secrets used for data encryption\nand verifiable random number generation.\nUnlike hardware-based encryption approaches, Dstack-KMS deliberately decouples key generation\nfrom specific TEE hardware instances.  This architectural decision enables the critical capability of\nencrypted  data  migration  between  different  TEE  instances,  with  decryption  possible  after\nproper authorization.  This feature is essential for achieving true censorship resistance.\nGiven  its  position  as  the  root-of-trust  for  the  entire  system,  the  verifiability  and  availability  of\nDstack-KMS are paramount.  Unlike previous approaches [?] that assume TEE infallibility, our threat\nmodel explicitly acknowledges that TEEs can be compromised.  To address this reality, Dstack-\nKMS  implements  comprehensive  key  rotation  capabilities  that  provide  both  backward  and  forward\nsecrecy for application data. This ensures that even if a specific TEE hardware instance is compromised,\napplications can be migrated with limited data exposure.\nFigure 3:  The key derivation hierarchy of Intel SGX illustrates how conventional TEE implementations bind\nencryption keys to hardware.\nTo understand the limitations of conventional approaches, Figure 3 illustrates the key derivation\nhierarchy in Intel SGX. This design uses a hardware-bound key to both identify the TEE instance (for\nRemote Attestation) and generate encryption keys for data sealing.  While this approach effectively\nestablishes hardware identity, it fundamentally undermines censorship resistance:\n•  The root key cannot be updated, meaning a compromised TEE with a leaked root key remains\npermanently vulnerable even after patching the underlying vulnerability.\n•  Encrypted data becomes intrinsically bound to specific TEE hardware instances, creating single\npoints of failure that contradict Web3’s censorship resistance requirements.\nOur  Dstack-KMS  addresses  these  limitations  by  delegating  secret  generation  to  an  independent\nservice that ensures encrypted data remains portable across TEE instances.\nAs illustrated in Figure 4, Dstack-KMS comprises an on-chain governance smart contract coupled\nwith an off-chain peer-to-peer network where the actual secret derivation service operates.  To ensure\ncomprehensive verifiability of the Dstack-KMS program’s integrity and correctness, we implement a\nmulti-stage verification process:\n1.  The Dstack-KMS codebase is fully open-sourced [?], enabling thorough code and security reviews\nto verify key management logic and ensure the absence of backdoors.\n5\nFigure 4:  The architecture of Dstack-KMS combines on-chain governance through smart contracts with an\noff-chain P2P network of secret derivation service nodes.  This design ensures both verifiability and resilience\nagainst compromise.\n2.  Executable  binaries  are  produced  through  reproducible  build  processes,  allowing  verifiers  to\nconfirm that the runtime code matches the reviewed source code.\n3.  The cryptographic digest of valid executables is published through the governance smart contract,\ncreating an immutable reference for verification.\n4.  Each service node operates within its own TEE instance.  Critically, we rely on the TEE solely for\nmeasuring the executable and ensuring it matches the on-chain digest—not for the fundamental\nsecurity of the key management process.\nThis verification framework ensures that Dstack-KMS remains trustworthy to any third-party verifier\nwhile avoiding dependency on the absolute security of any single TEE instance.\nThe core logic of each Dstack-KMS service node is intentionally minimalist, focusing exclusively on\nthe generation and secure distribution of the root key, along with deriving encryption keys for TEE\napplications.  This simplicity enables the implementation of Multi-Party Computation (MPC) based\nthreshold key generation and derivation without concerning performance overhead.  We have developed\ntwo complementary implementations:\n•  Simple Duplication:  The first node in the P2P network generates a cryptographically secure\nrandom number as the root key, then shares it with other nodes after verifying their attestation\nreports.  All nodes maintain identical copies of the root key and derive consistent encryption keys\nfor  applications.   This  approach  maximizes  availability—as  long  as  at  least  one  node  remains\noperational, the root key can be recovered.\n•  MPC-Based Key Generation:  While simple duplication provides robust availability, it cre-\nates vulnerability to single-node compromises.  Our MPC implementation uses Shamir’s Secret\nSharing scheme [?] to distribute the root key across multiple nodes, ensuring that compromising\nany individual node (or even up tot− 1 nodes, wheret is the configured threshold) does not\nexpose  the  root  key.   This  approach  also  enables  advanced  features  like  key  rotation  without\nrequiring application reconfiguration.\nKey Derivation    Dstack-KMS implements a comprehensive key derivation framework to generate\napplication-specific keys from the root key:\n•  Application CA Key:  Derived from the root CA key using the application’s unique identifier\n(calculated as the hash of the application’s code and configuration).\n•  Disk Encryption Key:  Derived using a combination of the application identifier and instance\nidentifier, enabling secure storage with portability.\n6\n•  Environment Encryption Key: Derived using the application identifier alone, allowing secure\nenvironment variable management across instances.\n•  ECDSA Key:  Derived from the root ECDSA key, providing applications with consistent cryp-\ntographic identity for signing operations.\nEach derived key maintains cryptographic isolation while ensuring consistency across different TEE\ninstances running the same application.\nKey Rotation    A critical security feature of Dstack-KMS is its support for key rotation, which signif-\nicantly limits the exposure window during potential attacks while ensuring both forward and backward\nsecrecy for sealed data.  Key rotation procedures are initiated exclusively through the governance smart\ncontract, ensuring transparency and auditability.  We discuss two distinct rotation mechanisms:\n•  Root Key Share Rotation:  Our MPC-based implementation enables rotation of individual\nkey  shares  without  modifying  the  root  key  itself.   This  process  enhances  root  key  security  by\nregularly updating the distribution mechanism while remaining transparent to applications, as\nall derived application keys remain unchanged.\n•  Root Key Rotation:  In scenarios where the root key may have been compromised, we support\ncomplete root key rotation.  This process generates an entirely new root key and implements a\ncontrolled handover period during which both old and new keys remain valid.  This transition\nwindow  allows  applications  to  re-encrypt  their  data  with  keys  derived  from  the  new  root  key\nbefore the old root key is permanently destroyed, minimizing service disruption while enhancing\nsecurity.\nThrough these mechanisms, Dstack-KMS provides the foundation for truly portable confidential con-\ntainers by decoupling encryption from hardware dependencies while maintaining robust security guar-\nantees.\n2.1.2    Dstack-OS: Hardware Abstraction Layer\nDstack-OS provides a comprehensive hardware abstraction layer with a minimized operating system\nimage that bridges the gap between application containers and VM-level TEE implementations.  This\nlayer enables applications to deploy across diverse TEE environments without code modifications while\nmaintaining security integrity.  As a shared component across all TEE applications, Dstack-OS must be\nintrinsically secure and verifiable, with no administrative backdoors that could compromise program\ncode or user data.\nVM-level  TEE  solutions  typically  require  developers  to  provide  complete  system  images  encom-\npassing  bootloader,  kernel,  operating  system,  and  application  components.   This  requirement  not\nonly increases development complexity but also introduces potential security vulnerabilities through\nmisconfigured system components.  A secure and properly configured operating system environment\nfundamentally determines the security baseline for all TEE applications built upon it.\nFigure 5 illustrates how Dstack-OS establishes a secure and verifiable startup chain from the TEE\nhardware foundation through to user-provided container images.  Our modular design ensures that the\nmajority of the system can be reused across different TEE hardware implementations, substantially\nreducing the effort required for code review and security auditing.  Combined with reproducible build\nprocesses, this approach enables comprehensive verification of Dstack-OS with minimal overhead while\nsupporting multiple TEE hardware platforms.\nUsing Intel TDX as an exemplar (with similar procedures applicable to other TEE implementa-\ntions like AMD SEV), Dstack-OS consists of the following components,  presented in boot sequence\norder.  During this process, each component measures the next one and records these measurements\nin hardware registers, which are ultimately incorporated into the TEE attestation report:\n•  Hypervisor: When application deployment initiates, the underlying hypervisor (the TDX mod-\nule) loads the Open Virtual Machine Firmware (OVMF), enabling UEFI support for confidential\nvirtual  machines.   The  TDX  module  measures  the  OVMF  code  and  records  its  cryptographic\ndigest in the MRTD register, with the hypervisor’s integrity guaranteed by the TEE hardware\nitself.\n7\nFigure 5:  The architecture of Dstack-OS establishes a secure and verifiable startup chain from TEE hardware\nthrough to user applications.\n•  Open Virtual Machine Firmware (OVMF): The OVMF configures virtual machine hard-\nware  specifications  (CPU,  memory,  and  device  configurations)  and  records  the  configuration\nmeasurement  to  the  RTMR0  register.   It  then  loads  the  Linux  kernel  and  records  the  kernel\nimage measurement to the RTMR1 register.\n•  Kernel:  The kernel first loads an initial ramdisk (initrd) — a temporary in-memory filesystem\ncontaining  minimal  command-line  tools  and  disk  encryption  libraries.   The  initrd  mounts  the\nroot filesystem and records this measurement in the RTMR2 register.\n•  Root Filesystem: The root filesystem (RootFs) is a read-only environment containing essential\nsystem libraries and tools.  It manages the entire lifecycle of deployed applications, measuring\napplication images along with their associated key management system and storing these mea-\nsurements  in  the  RTMR3  register.   The  RootFs  serves  two  primary  functions:  (1)  providing\nthe runtime environment for user-level container images, and (2) managing application data en-\ncryption.   It  interfaces  with  Dstack-KMS  to  acquire  encryption  secrets  and  implements  Linux\nUnified Key Setup (LUKS) to encrypt application data in isolated volumes.  Data integrity is\nensured through dm-verity, a Merkle-tree-based block-level verification tool.  Finally, the RootFs\nconfigures network ingress for the application and initiates execution.\nRather than adapting existing system images, we built Dstack-OS from scratch to ensure only es-\nsential components are included in both the initrd and RootFs.  A comprehensive component inventory\nis provided in Appendix ?? for transparency and review.  Generally,  Dstack-OS includes only basic\nutilities (busybox), filesystem support, and container runtime components.  By implementing Docker\nsupport  while  delegating  orchestration  to  the  application  level,  we  maintain  a  minimal  base  image\nfootprint.\nTo ensure comprehensive verifiability, Dstack-OS is fully open-sourced and supports reproducible\nbuilds,  allowing  anyone  to  review  the  code  and  generate  identical  artifacts  for  verification.   This\napproach provides significant benefits for applications requiring security reviews,  as evaluators need\nonly review the application code rather than the entire system image.\nData Backup and Defense against Rollback Attacks    A critical challenge in confidential com-\nputing is ensuring data durability and integrity, particularly against rollback attacks where adversaries\nattempt to revert applications to previous states to bypass security checks or reuse expired secrets.\nOur architecture provides robust secure data backup support and implements robust anti-rollback\nmechanisms that application developers can integrate:\n•  Secure Backup:  Application data is encrypted using keys derived from Dstack-KMS and can\nbe backed up to external storage providers.  Since encryption keys are not bound to specific TEE\n8\ninstances, data can be restored on any authorized TEE, supporting true portability and disaster\nrecovery.\n•  Monotonic Counters: To prevent rollback attacks, developers can implement monotonic coun-\nters that increment with each critical data update, incorporating the counter value into the en-\ncrypted data.  During restoration, applications verify that the counter value equals or exceeds\nthe last known value, preventing replay of outdated snapshots.\nBy combining these techniques,  Dstack ensures both the recoverability and integrity of confidential\ndata across portable container migrations and backup scenarios.\nTogether, Dstack-KMS and Dstack-OS provide the foundational infrastructure for truly portable\nconfidential containers that maintain security and integrity across heterogeneous TEE environments\nwhile eliminating vendor lock-in and supporting comprehensive verifiability.\n2.2    Decentralized Code Management\nA core principle of Zero Trust platforms is the enforcement of “Code is Law”, ensuring that application\ncode  operates  as  intended  without  unexpected  modifications.   While  TEE  hardware  provides  code\nintegrity guarantees during execution, it cannot independently prevent administrators from deploying\nmalicious code or making unauthorized modifications.  Conversely, smart contracts have established\nrobust methodologies for implementing programmable governance over code lifecycle management —\nsuch as multi-signature requirements that prevent single-actor manipulation.\nOur  decentralized  code  management  framework  bridges  these  two  worlds  by  placing  TEE  ap-\nplication governance under smart contract control,  creating a transparent and auditable system for\napplication deployment and updates that aligns with Web3 principles.\nFigure 6:  The architecture of decentralized code management integrates on-chain governance contracts with\noff-chain TEE through Dstack-KMS.\nAs illustrated in Figure 6, our architecture consists of two complementary components:  on-chain\ngovernance  smart  contracts  and  off-chain  TEE  execution  environments  connected  through  Dstack-\nKMS. This design establishes the on-chain contracts as the definitive root-of-trust for the entire system.\nEvery operation — from initial deployment to code upgrades — must first be initiated and authorized\nthrough the governance contracts before off-chain TEE instances can execute these operations.\nThe governance framework implements a two-tier structure:\n•  KmsAuth Contract:  Serves as the global authority controlling Dstack-KMS operations.  This\ncontract maintains the registry of authorized applications and their governance parameters, en-\nforcing system-wide policies for TEE deployment.  By controlling whether Dstack-KMS shares\n9\napplication  secrets  with  specific  TEE  instances,  the  KmsAuth  contract  effectively  determines\nwhether applications can decrypt their data, thus controlling their complete lifecycle.\n•  AppAuth Contracts:  Individual governance contracts deployed for each application that de-\nfine  application-specific  management  rules.   These  contracts  specify  permissible  code  versions\n(through cryptographic hashes), authorized TEE instance identities, and upgrade approval re-\nquirements.  This modular approach enables customized governance models ranging from tradi-\ntional multi-signature schemes to complex DAO voting mechanisms, allowing each application\nto implement governance appropriate to its requirements.\nThe enforcement mechanism operates through Dstack-KMS, which will only provide application\nsecrets  to  TEE  instances  running  code  versions  explicitly  authorized  by  the  governance  contracts.\nThis creates a cryptographically enforced governance system where unauthorized code versions cannot\naccess application data, regardless of administrative privileges.\nTo  illustrate  this  mechanism,  consider  a  code  upgrade  process  for  an  application  using  a  multi-\nsignature AppAuth contract in Figure 6:\n1.  Developers  publish  the  new  code  version  and  submit  its  cryptographic  hash  to  the  AppAuth\ncontract.\n2.  The  contract  initiates  the  approval  process,  requiring  signatures  from  designated  key  holders\n(e.g., core developers, security auditors, and community representatives).\n3.  Each signature is recorded on-chain, creating an immutable audit trail of the approval process.\n4.  Once the required signature threshold is reached, the AppAuth contract updates its registry of\nauthorized code versions.\n5.  The  KmsAuth  contract,  monitoring  the  AppAuth  contract,  updates  its  authorization  records\naccordingly.\n6.  Dstack-KMS,  which  continuously  synchronizes  with  the  KmsAuth  contract,  begins  providing\napplication secrets to TEE instances running the newly approved code version.\n7.  TEE instances can now deploy the new code with full access to encrypted application data.\nThis process ensures that every code change follows predefined governance rules with complete trans-\nparency.  The on-chain approval records create an immutable audit trail that allows users to verify\nthe entire history of application changes, while the cryptographic enforcement through Dstack-KMS\nguarantees that only properly authorized code can access application data.\nBy combining the code integrity guarantees of TEEs with the transparent governance capabilities\nof  smart  contracts,  our  decentralized  code  management  framework  ensures  that  applications  truly\nembody the ”Code is Law” principle. Every aspect of the application lifecycle—from initial deployment\nto  version  updates  and  potential  retirement—follows  predefined,  transparent  rules  that  cannot  be\ncircumvented by any single entity, including the platform operators themselves.\n2.3    Verifiable Domain Management\nA  complete  Zero  Trust  platform  must  enable  seamless  verification  for  users  across  both  Web3  and\ntraditional  Web2  environments.   Our  Verifiable  Domain  Management  system  completes  the  chain-\nof-trust  by  allowing  standard  Web  browsers  to  cryptographically  verify  TEE  applications  without\nrequiring any client-side modifications or specialized knowledge.\nThis  capability  is  critical  for  mainstream  adoption,  as  it  allows  users  to  interact  with  confiden-\ntial applications using familiar tools while maintaining the same security guarantees provided by the\nunderlying TEE infrastructure.  We implement this through two complementary components—Dstack-\nIngress and Dstack-Gateway—both leveraging our novel Zero Trust TLS (ZT-TLS) protocol.\nThe  fundamental  innovation  in  ZT-TLS  is  establishing  cryptographic  proof  that  a  specific  TLS\ncertificate  (and  therefore  a  domain)  is  exclusively  controlled  by  a  verified  TEE  application.   This\ncreates a verification chain extending from the blockchain to standard HTTPS connections, enabling\nusers to confirm application authenticity through familiar security indicators in their browsers.\n10\nFigure  7:   The  Zero  Trust  TLS  architecture  establishes  a  cryptographically  verifiable  connection  between\nstandard web browsers and TEE applications through blockchain-anchored certificate management.\n2.3.1    Zero Trust TLS Protocol\nThe  ZT-TLS  protocol  addresses  a  critical  challenge:  how  to  cryptographically  bind  a  domain  to  a\nspecific TEE application in a way that prevents unauthorized certificate issuance or domain hijacking.\nOur solution integrates three key components:\n•  TEE-Generated Certificates:  The TEE application (specifically Dstack-Gateway) generates\nits TLS certificate using application secrets derived from Dstack-KMS. This ensures the private\nkey  never  exists  outside  the  TEE  environment  and  creates  a  cryptographic  link  between  the\non-chain governance and the TLS certificate.\n•  Certificate  Authority  Authorization  (CAA):  We  leverage  DNS  CAA  records  to  restrict\nwhich  certificate authorities can  issue certificates  for managed  domains.  By  configuring CAA\nrecords  to  only  authorize  certificates  from  specific  issuers  (which  verify  TEE  attestation),  we\nprevent unauthorized certificate issuance through alternative validation methods.\n•  Certificate Transparency (CT) Monitoring:  To protect against unauthorized DNS record\nmodifications, we implement continuous monitoring of Certificate Transparency logs.  This allows\ndetection of any unauthorized certificates and provides an immutable audit trail of certificate\nissuance history.\n2.3.2    Implementation Components\nWe provide two complementary implementations to accommodate different application requirements:\n•  Dstack-Gateway:  A fully managed reverse proxy running within a TEE that provides imme-\ndiate domain verification with zero application code changes.  Applications register with Dstack-\nGateway through a simple API call, during which Dstack-Gateway verifies the application’s re-\nmote attestation report.  Once verified, applications receive a subdomain under a pre-registered\nwildcard domain (e.g., app-id.Dstack.com), with all TLS termination and certificate manage-\nment handled automatically.\n•  Dstack-Ingress:   A  more  flexible  solution  for  applications  requiring  custom  domain  names.\nDstack-Ingress provides libraries and services that enable applications to manage their own TLS\ncertificates while maintaining the same verification guarantees.  This approach requires minimal\nintegration work while supporting application-specific domain requirements.\n11\nBoth implementations ensure that certificates are cryptographically bound to verified TEE environ-\nments, with the verification chain extending from the blockchain governance contracts through to the\nTLS certificates presented to users’ browsers.\n2.3.3    Security Guarantees and Protections\nOur Verifiable Domain Management system provides several critical security guarantees:\n•  Certificate Provenance Verification:  Users can verify that the TLS certificate presented by\nan application was issued to a legitimate TEE environment by checking the certificate against\non-chain records.\n•  Domain Binding Integrity:  The combination of CAA records and Certificate Transparency\nmonitoring ensures that domains remain bound to their designated TEE applications, preventing\nunauthorized certificate issuance.\n•  Tamper-Evident Certificate Changes:  Any unauthorized attempts to modify domain con-\nfigurations or issue alternative certificates are detected through Certificate Transparency moni-\ntoring, with alerts propagated to clients.\nWhile we cannot technically prevent all attacks against centralized DNS infrastructure, our multi-\nlayered approach creates a tamper-evident system where unauthorized changes are quickly detected\nand rejected by client verification processes.  This approach aligns with the ”Assume Breach” principle\nby implementing defense-in-depth strategies that maintain security even when individual components\nare compromised.\nBy extending the verification chain from blockchain governance through TEE attestation to stan-\ndard TLS certificates, our Verifiable Domain Management system enables seamless integration of Zero\nTrust  applications  into  existing  web  infrastructure.   This  creates  a  practical  path  for  mainstream\nadoption without requiring specialized knowledge or tools from end users, while maintaining the com-\nprehensive security guarantees that define true Zero Trust platforms.\n3    Verifying TEE Applications:  A Practical Walkthrough\nTo demonstrate how Dstack fulfills the Zero Trust principles and addresses the challenges outlined in\nSection 1,  we present a practical end-to-end verification scenario.  This walkthrough illustrates how\nthe architectural components described in Section 2 work together to provide a comprehensive chain\nof trust for real-world Web3 applications.\nTraditional  Zero  Trust  programs  like  smart  contracts  achieve  verifiability  through  transparent\nsource  code  and  inputs.   However,  extending  similar  verifiability  to  real-world  applications  presents\nunique  challenges,  particularly  in  maintaining  privacy  and  compatibility  with  existing  development\npractices.   Dstack  addresses  these  challenges  through  a  comprehensive  verification  framework  that\nrequires minimal code changes.\nThis section demonstrates Dstack’s complete chain of trust through a practical example:  verifying\nthat  a  cryptographic  key  was  genuinely  generated  within  a  TEE  environment.   This  scenario  is  es-\npecially relevant for Web3 and AI Agent applications where cryptographic keys establish application\nidentity and authority.\n3.1    Threat Model\nOur verification framework assumes the correct implementation and integrity of core Dstack compo-\nnents (Dstack-OS, Dstack-KMS, Dstack-Gateway, and governance contracts). While these components’\nsecurity guarantees are detailed in later sections, we explicitly consider developers and administrators\nas potential adversaries.\nPotential attack vectors include:\n•  Application-Level Attacks\n–  Deployment of unauthorized or malicious code through falsified Docker images\n12\n–  Introduction of malicious dependencies through supply chain attacks\n–  Unauthorized application updates that bypass governance controls\n•  Infrastructure-Level Attacks\n–  Tampering with Dstack-OS to circumvent security controls\n–  Deployment of compromised key management services\n–  Operation of unpatched or vulnerable TEE firmware\n–  Execution of applications on non-TEE hardware with spoofed attestation\n•  Network-Level Attacks\n–  DNS hijacking to redirect traffic to unauthorized applications\n–  Man-in-the-middle attacks on communication channels\nDirect attacks on TEE hardware security (e.g., exploitation of hardware vulnerabilities) are con-\nsidered out of scope for this discussion and addressed separately.\n3.2    The Reproducibility Challenge\nA  fundamental  challenge  in  TEE  attestation  lies  in  bridging  the  gap  between  source  code  and  the\nactual  artifacts  (binaries  or  container  images)  running  inside  enclaves.   While  TEE  attestation  can\nprove that a specific artifact runs within a secure environment, it cannot independently verify that the\nartifact accurately represents its claimed source code.\nThis limitation creates several security risks:\n•  Source Code Manipulation:  Developers could intentionally deploy artifacts that differ from\npublicly reviewed source code\n•  Build Process Compromise:  Supply chain attacks could inject malicious code during artifact\ncreation\n•  Toolchain  Vulnerabilities:   As  demonstrated  by  the  Ken  Thompson  Hack,  even  compiler\ntoolchains could be compromised to inject malicious behavior\nTEE  quotes  only  attest  to  measurements  (cryptographic  hashes)  of  running  artifacts.   Without\nguarantees that these artifacts accurately represent reviewed source code, users cannot fully trust ap-\nplications even when running in secure enclaves.  This challenge affects all TEE applications, including\nDstack’s core components.\nFigure 8:  Comprehensive verification chain from source code to running TEE applications\nEstablishing a complete verification chain requires three key elements:\n13\n•  Source Code Verification:  Open-source code or trusted third-party review ensuring no back-\ndoors exist\n•  Build Process Integrity:  Reproducible builds allowing independent verification of artifacts\n•  Runtime Attestation:  TEE quotes proving that verified artifacts are actually running\nTraditional reproducible builds, while ideal, often introduce significant complexity through special-\nized  toolchains  and  build  scripts.   The  following  section  introduces  an  alternative  approach, In-CC\nBuild, that achieves similar guarantees with improved practicality.\n3.3    Dstack Component Verifiability\nEach  core  Dstack  component  implements  specific  verifiability  mechanisms  anchored  in  transparent,\nimmutable records.  Table 1 summarizes these mechanisms:\nComponentSourceBuild MethodRegistryVerification\nDstack-OSOpenReproducibleKmsAuthOS Digest\nDstack-KMSOpenIn-CCKmsAuthImage Hash, Root PubKey\nDstack-GatewayOpenIn-CCAppAuthImage Hash\nTable 1:  Verifiability mechanisms and trust anchors for Dstack components\nAll components maintain open-source codebases with comprehensive documentation. Dstack-OS, as\nthe foundational component, undergoes third-party security audits and implements fully reproducible\nbuilds.\nThe governance smart contracts serve as authoritative registries, anchoring each component’s trust\nbase:\n•  Dstack-OS digests are registered in KmsAuth and managed through multi-signature governance\n•  Dstack-KMS measurements and root public keys are recorded in KmsAuth\n•  Dstack-Gateway artifacts are verified through dedicated AppAuth contracts\nIn-ConfidentialContainer Build    While reproducible builds represent the gold standard for arti-\nfact verification, they often prove impractical for complex applications.  Dstack addresses this through\nIn-CC Build,  leveraging  the  verified  Dstack-OS  as  a  trusted  foundation.   The  In-CC  Build  process\nexecutes entirely within Dstack-OS environment, encompassing code fetching, compilation, and arti-\nfact creation.  By specifying precise source references (e.g., a snapshot of the codebase), the system\nproduces verifiable artifacts with measurements attested in TEE quotes.  This approach minimizes the\ntrusted computing base while eliminating the complexity of traditional reproducible builds.\n3.4    End-to-End Verification Walkthrough\nFrom a user’s perspective, verifying a TEE application in Dstack requires validating a chain of mea-\nsurements against authoritative registries,  encompassing the user application,  runtime data,  Dstack\ncomponents, and network infrastructure.  This section walks through the verification process, demon-\nstrating how each step builds upon the previous one to create a comprehensive chain of trust.\nAs shown in Figure 9, the verification chain begins with the KmsAuth smart contract, which serves\nas the root of trust for the entire system, and concludes with the key generation application running\nin a TEE. We explain the verification steps as follows.\nFirst,  the address of the Dstack-KMS governance contract (i.e.,  KmsAuth) is publicly available.\nThe KMS governance contract serves as the authoritative registry for (1) off-chain KMS nodes and\n(2) dedicated governance contracts (i.e., AppAuth) for TEE applications.  It is worth noting that the\nDstack-Gateway can be regarded as a special TEE application that attests and forwards requests to\nother user applications while maintaining consistent verification procedures.\nThe  KmsAuth  contract  records  both  the  measurements  of  off-chain  KMS  node  programs  (KMS\ndigest, which is the hash of the docker compose file and the images used in In-CC Build) and the TDX\n14\nFigure 9:  The verification chain from authoritative registries to runtime measurements\nQuote of the first KMS node, which acts as the primary key generator.  The identities of subsequent\nKMS  nodes  must  first  be  registered  in  KmsAuth  and  verified  by  the  first  KMS  node  before  they\ncan participate in key generation.  These data, together with the open-source Dstack-KMS codebase,\nallow users to verify the integrity of the KMS nodes and their code correctness.  Subsequently,  the\noff-chain KMS nodes can be considered trusted extensions and used to verify Quotes from other TEE\napplications,  which  cannot  be  achieved  by  the  on-chain  governance  contract  alone.   The  off-chain\nKMS nodes are responsible for generating and managing cryptographic keys (i.e., the root key) and\nthe corresponding certificates (explained in Section 2.3.1), which are further used to authorize TEE\napplications after they are verified, thereby avoiding redundant verification.\nSecond, users can verify the validity of Dstack-Gateway.  By default, this is delegated to the off-\nchain  KMS  nodes  during  gateway  registration,  although  users  can  always  request  the  Quote  of  the\ngateway and check the digest of its docker compose file in its governance contract and the codebase.\nAfter the KMS nodes verify the gateway, it will generate its application root key along with a certificate\nchain ending with the root certificate.\nNext, users can access the TEE application through Dstack-Gateway forwarding.  In this case, users\neffectively delegate the verification of the key generation application to the gateway.  The deployment\nof the key generation application starts from the KmsAuth contract.  The deployer first registers it\nand stores the digest (the hash of the docker compose file and the images) on the dedicated AppAuth\ncontract.  Then, as in the previous step, the off-chain KMS nodes verify the Quote of the application\nafter  it  is  deployed  to  the  TEE  and  ensure  it  matches  the  registered  digest.   Only  after  successful\nverification will the key be generated along with the certificate chain.  To be forwarded by the gateway,\nthe application must also register with it.  In this case, the gateway verifies the application’s certificate\nchain and ensures it shares the same root certificate, indicating authorization by the same KMS.\nFinally, the user can invoke the application and request proof of the key it generated.  The applica-\ntion can generate a Quote on demand, with the generated public key included as custom data in the\nQuote.\n15\n3.5    Security Analysis:  Mitigating Threats\nOur key generation example demonstrates Dstack’s comprehensive approach to security across multiple\nattack surfaces.  At the application level, the system prevents unauthorized code deployment through\nrigorous  measurement  verification  against  the  AppAuth  registry.   The  In-CC  Build  process  ensures\nall dependencies originate from verified sources,  while any updates require new registry entries and\ncomplete re-verification.  It is important to note, however, that code audit and review processes remain\nessential for ensuring application code correctness, as the In-CC Build only guarantees the integrity of\nthe build process.\nInfrastructure security is maintained through multiple mechanisms.  TDX Quotes verify Dstack-OS\nintegrity, preventing OS-level tampering.  KMS updates require multi-signature governance approval,\nsafeguarding against unauthorized changes to key management services.  The Quote verification pro-\ncess  includes  firmware  version  validation,  ensuring  applications  run  on  up-to-date  TEE  hardware.\nHardware-backed TDX Quotes effectively prevent attestation spoofing attempts.\nNetwork-level threats are mitigated through the certificate chain validation system.  This prevents\nboth  DNS  hijacking  and  man-in-the-middle  attacks  by  ensuring  authentic  application  identity  and\nenabling end-to-end encryption with verified certificates.  The combination of these security measures\nensures that cryptographic keys maintain their integrity guarantees even when confronted with sophis-\nticated attacks targeting different system layers.\nReferences\n16"
      }
    ]
  },
  {
    "role": "assistant",
    "content": "# Project Proposal Template\n\n## General Information\n1.1. Name of Project\nDstack\n\n1.2. Project Description (what it does, why it is valuable, origin and history)\nDstack is a developer-friendly and security-first SDK that simplifies the deployment of arbitrary containerized applications into Trusted Execution Environments (TEEs). It enables developers to securely deploy containerized applications in TEEs in minutes using familiar tools like docker-compose.yaml. Dstack provides safe management of secrets and sensitive data, along with built-in TLS termination for exposed services.\n\nThe project was built by Kevin Wang and others from Phala Network, inspired by Andrew Miller (Flashbots & Teleport), and has received contributions from Nethermind and many others. Dstack addresses the gap between raw TEE technology and Zero Trust platform requirements by providing portable confidential containers, decentralized code management, and verifiable domain management.\n\n1.3. How does this project align with the Consortium's Mission Statement\n[blank]\n\n1.4. Project website URL\nhttps://docs.phala.network/dstack/overview (inferred from documentation references)\n\n1.5. Social media accounts\n[blank]\n\n## Legal Information\n2.1. Project Logo URL or attachment (Vector Graphic: SVG, EPS).\n[blank]\n\n2.2. Project license. We recommend an OSI-approved license, so if the license is not one on the list, explain why.\nApache License, Version 2.0\n\n2.3. Existing financial sponsorship.\n[blank]\n\n2.4. Trademark status.\n[blank]\n\n## Technical Information\n3.1. High level assessment of project synergy with existing projects under the CCC, including how the project compliments/overlaps with existing projects, and potential ways to harmonize over time. Responses may be included both inline and/or in accompanying documentation.\n[blank]\n\n3.2. Describe the Trusted Computing Base (TCB) of the project. If the project supports multiple environments please describe each TCB. Also identify if dependencies of other project (both CCC or non-CCC) TCBs are taken.\nDstack's TCB includes:\n- Dstack-OS: A minimized operating system image that serves as a hardware abstraction layer\n- OVMF (Open Virtual Machine Firmware): Configures VM hardware specifications\n- Linux kernel with initial ramdisk (initrd)\n- Root filesystem with essential system libraries and tools\n- Intel TDX or equivalent TEE hardware as the foundation\n\nThe system establishes a secure and verifiable startup chain from TEE hardware through to user applications, with each component measuring the next and recording measurements in hardware registers that are incorporated into TEE attestation reports.\n\n3.3. Project Code of Conduct URL. We recommend a Contributor Covenant v2.0 based Code of Conduct, so if the Code of Conduct is not based on that, explain why.\n[blank]\n\n3.4. Source control URL\nhttps://github.com/Dstack-TEE/dstack\n\n3.5. Issue tracker URL\nhttps://github.com/Dstack-TEE/dstack/issues (inferred)\n\n3.6. External dependencies (including licenses, and indicate whether each is a build time or runtime dependency)\n- Intel TDX or equivalent TEE hardware (runtime)\n- Linux kernel (runtime)\n- Docker/container runtime (runtime)\n- Busybox (runtime)\n- LUKS for encryption (runtime)\n- Wireguard-tools (build time)\n- Build-essential, chrpath, diffstat, lz4, xorriso (build time)\n- Rust (build time)\n\n3.7. Standards implemented by the project, if any. Include links to any such standards.\n- TLS/HTTPS for secure communications\n- Certificate Transparency (CT) for certificate monitoring\n- Certificate Authority Authorization (CAA) for domain security\n- Remote Attestation for TEE verification\n\n3.8. Release methodology and mechanics\n[blank]\n\n3.9. Names of initial committers, if different from those submitting proposal\nInitial committers include:\n- Kevin Wang (kvinwang)\n- Shelven Zhou (shelvenzhou)\n- Leechael\n\n3.10. List of project's official communication channels (slack, irc, mailing lists)\n[blank]\n\n3.11. Project Security Response Policy\n[blank]\n\n3.12. Preferred maturity level (Incubation, Graduation, or Emeritus)\n[blank]\n\n3.13. Any additional information the TAC and Board should take into consideration when reviewing your proposal.\nDstack includes several key components:\n- dstack-vmm: Service running on bare TDX host to manage CVMs\n- dstack-gateway: Reverse proxy to forward TLS connections to CVMs\n- dstack-kms: KMS server to generate keys for CVMs\n- dstack-guest-agent: Service in CVM to serve containers' key derivation and attestation requests\n- meta-dstack: Yocto meta layer to build CVM guest images\n\nThe project provides innovative solutions for portable confidential containers, decentralized code management, and verifiable domain management, addressing critical limitations in current TEE implementations for Web3 contexts."
  },
  {
    "role": "user",
    "content": "This is the current project list. FIll in 3.1 with it.\n```\nCertifier Framework For Confidential Computing\nThe Certifier Framework for Confidential Computing consists of a client API called the Certifier API and server-based policy evaluation server called the Certifier Service.\n\n\nCOCONUT-SVSM\nThe COCONUT-SVSM is an implementation of a Secure VM Service Module for confidential computing virtual machines (CVMs).\n\n\nEnarx\nEnarx provides a platform abstraction for Trusted Execution Environments (TEEs) enabling creating and running “private, fungible, serverless” applications.\n\n\nGramine\nA particular use case for Gramine is Intel Software Guard Extensions (SGX), where applications do not work out-of-the-box. Gramine solves this problem, with the added security benefits. Gramine can serve as a compatibility layer on other platforms.\n\n\nIslet\nIslet is an open-source software project written in Rust that enables confidential computing on ARM architecture devices using the ARMv9 CCA. The primary objective of Islet is to enable on-device confidential computing and protect user privacy on end user devices.\n\n\nKeystone\nKeystone is an open-source project for building trusted execution environments (TEE) with secure hardware enclaves, based on the RISC-V architecture. Our goal is to build a secure and trustworthy open-source secure hardware enclave, accessible to everyone in industry and academia.\n\n\nManaTEE\nManaTEE is an open-source project for easily building and deploying data collaboration framework to the cloud using trusted execution environments (TEEs). It allows users to easily collaborate on private datasets without leaking privacy of individual data.\n\n\nOcclum\nOcclum makes running applications inside enclaves easy. It allows one to run unmodified programs inside enclaves with just a few simple commands. And Occlum is open-source and free to use.\n\n\nOpen Enclave SDK\nOpen Enclave SDK is an open source framework that allows developers to build Trusted Execution Environment (TEE) applications using a single enclaving abstraction.\n\n\nSPDM Tools\nThis project provides a Rust language implementation of SPDM, IDE_KM and TDISP. These protocols are used to facilitate direct device assignment for Trusted Execution Environment I/O (TEE-I/O) in Confidential Computing.\n\n\nVeracruz\nVeracruz is a research project exploring the design of privacy-preserving distributed systems. Veracruz uses strong isolation technology and remote attestation protocols to establish a “neutral ground” within which a collaborative, multi-party computation between a group of mistrusting principals takes place.\n\n\nVeraison\nProject Veraison builds software components that can be used to build an Attestation Verification Service.\n\n\nVirTEE\nVirTEE is an open community dedicated to developing open source tools for the bring-up, attestation, and management of Trusted Execution Environments.\n```"
  }
]

Response:

3.1. High level assessment of project synergy with existing projects under the CCC, including how the project compliments/overlaps with existing projects, and potential ways to harmonize over time. Responses may be included both inline and/or in accompanying documentation. Dstack complements several existing CCC projects while addressing unique needs in the confidential computing ecosystem: - **Synergy with Gramine**: While Gramine provides a compatibility layer for Intel SGX applications, Dstack extends this concept by offering a higher-level abstraction focused on containerized applications. Potential harmonization could involve Dstack leveraging Gramine's compatibility layer for specific workloads while providing a more developer-friendly interface. - **Complementary to Open Enclave SDK**: Open Enclave SDK provides a framework for building TEE applications with a single enclaving abstraction. Dstack takes a different approach by focusing on deploying existing containerized applications into TEEs without requiring code modifications. These projects could harmonize by having Dstack support applications built with Open Enclave SDK. - **Alignment with VirTEE**: VirTEE's focus on tools for bring-up, attestation, and management of TEEs aligns well with Dstack's goals. Dstack could potentially integrate with or leverage VirTEE's attestation components to enhance its security verification capabilities. - **Complementary to Veraison**: Veraison's attestation verification service components could be integrated with Dstack's attestation workflow to enhance the verification capabilities of Dstack's confidential containers. - **Differentiation from Enarx**: While Enarx provides a platform abstraction for TEEs focusing on "private, fungible, serverless" applications, Dstack focuses specifically on containerized applications with familiar Docker tooling. Both projects could share insights on TEE abstraction techniques. - **Extension beyond COCONUT-SVSM**: COCONUT-SVSM implements a Secure VM Service Module for confidential computing VMs. Dstack builds upon this concept by providing a complete framework for deploying and managing containerized applications within these secure VMs. Dstack uniquely addresses the developer experience gap in confidential computing by providing a Docker-compose compatible interface for deploying applications in TEEs, with built-in solutions for key management, domain verification, and portable containers. This focus on developer experience and containerization complements the more foundational TEE technologies represented in the CCC.

Model: claude-3-7-sonnet-202502192025-06-25 13:10:57

Context:

[
  {
    "role": "user",
    "content": [
      {
        "type": "text",
        "text": "Help me fill in the follow template given the project whitepaper and README file.\n\nFor fields with not enough info, leave it \"[blank]\".\n\n```\nProject Proposal Template\n\nGeneral Information\n1.1. Name of Project\n1.2. Project Description (what it does, why it is valuable, origin and history)\n1.3. How does this project align with the Consortium's Mission Statement\n1.4. Project website URL\n1.5. Social media accounts\n\nLegal Information\n2.1. Project Logo URL or attachment (Vector Graphic: SVG, EPS).\n2.2. Project license. We recommend an OSI-approved license, so if the license is not one on the list, explain why.\n2.3. Existing financial sponsorship.\n2.4. Trademark status.\n\nTechnical Information\n3.1. High level assessment of project synergy with existing projects under the CCC, including how the project compliments/overlaps with existing projects, and potential ways to harmonize over time. Responses may be included both inline and/or in accompanying documentation.\n3.2. Describe the Trusted Computing Base (TCB) of the project. If the project supports multiple environments please describe each TCB. Also identify if dependencies of other project (both CCC or non-CCC) TCBs are taken.\n3.3. Project Code of Conduct URL. We recommend a Contributor Covenant v2.0 based Code of Conduct, so if the Code of Conduct is not based on that, explain why.\n3.4. Source control URL\n3.5. Issue tracker URL\n3.6. External dependencies (including licenses, and indicate whether each is a build time or runtime dependency)\n3.7. Standards implemented by the project, if any. Include links to any such standards.\n3.8. Release methodology and mechanics\n3.9. Names of initial committers, if different from those submitting proposal\n3.10. List of project's official communication channels (slack, irc, mailing lists)\n3.11. Project Security Response Policy\n3.12. Preferred maturity level (Incubation, Graduation, or Emeritus) 3.13. Any additional information the TAC and Board should take into consideration when reviewing your proposal.\n```"
      },
      {
        "type": "text",
        "text": "README.md\n# Dstack\n\n[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/Dstack-TEE/dstack)\n\nDstack is a **developer friendly** and **security first** SDK to simplify the deployment of arbitrary containerized apps into TEE.\n\nMain features:\n\n- 🔒 Deploy containerized apps securely in TEE in minutes\n- 🛠️ Use familiar tools - just write a docker-compose.yaml\n- 🔑 Safely manage secrets and sensitive data\n- 📡 Expose services via built-in TLS termination\n\nDstack is community driven. Open sourced and built by [Kevin Wang](https://github.com/kvinwang) and many others from [Phala Network](https://github.com/Phala-Network), inspired by [Andrew Miller](https://github.com/amiller) (Flashbots & Teleport), and contributed by [Nethermind](https://github.com/NethermindEth/nethermind) and [many others](#contributors).\n\n![Alt](https://repobeats.axiom.co/api/embed/0a001cc3c1f387fae08172a9e116b0ec367b8971.svg \"Repobeats analytics image\")\n\n# Overview\n\nComponents in Dstack:\n\n- `dstack-vmm`: A service running in bare TDX host to manage CVMs\n- `dstack-gateway`: A reverse proxy to forward TLS connections to CVMs\n- `dstack-kms`: A KMS server to generate keys for CVMs\n- `dstack-guest-agent`: A service running in CVM to serve containers' key derivation and attestation requests\n- `meta-dstack`: A Yocto meta layer to build CVM guest images\n\nThe overall architecture is shown below:\n![arch](./docs/assets/arch.png)\n\n# Directory structure\n\n```text\ndstack/\n    kms/                         A prototype KMS server\n    guest-agent/                 A service running in CVM to serve containers' key derivation and attestation requests.\n    dstack-util/                 A CLI tool in the guest setting up the system, getting TDX quote, extending RTMR, generating cert for RA-TLS, etc.\n    vmm/                         A service running in bare TDX host to manage CVMs\n    gateway/                     A reverse proxy to forward TLS connections to CVMs\n    certbot/                     A tool to automatically obtain and renew TLS certificates for dstack-gateway\n    ra-rpc/                      RA-TLS support for pRPC\n    ra-tls/                      RA-TLS support library\n    tdx-attest/                  Guest library for getting TDX quote and extending RTMR\n```\n\n# Build and play locally\n\n## Prerequisites\n\n- A bare metal TDX server setup following [canonical/tdx](https://github.com/canonical/tdx)\n- Public IPv4 address assigned to the machine\n- At least 16GB RAM, 100GB free disk space.\n- A domain with DNS access if you want to set up `dstack-gateway` for Zero Trust HTTPS\n\n> [!NOTE]\n>\n> This doc assumes you have access to a compatible Intel TDX Server ready to be configured with Dstack. Check the [Hardware Requirements](https://docs.phala.network/dstack/hardware-requirements) for more information on buying a bare metal server or renting a server from OVH. To start learning about Dstack check out the [docs](https://docs.phala.network/dstack/overview).\n>\n> If you are looking to deploy a CVM in minutes, go to the docs to learn how to [sign-up for a Phala Cloud Account](https://docs.phala.network/phala-cloud/getting-started/sign-up-for-cloud-account) and [deploy your first CVM on Dstack]((https://docs.phala.network/phala-cloud/getting-started/start-from-cloud-ui)).\n\n## Install dependencies\n\n```bash\n# for Ubuntu 24.04\nsudo apt install -y build-essential chrpath diffstat lz4 wireguard-tools xorriso\n# install rust\ncurl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh\n```\n\n## Build and run for local development\n\n### Build the artifacts\n```bash\ngit clone https://github.com/Dstack-TEE/meta-dstack.git --recursive\ncd meta-dstack/\n\nmkdir build\ncd build\n../build.sh hostcfg\n# This outputs the following message:\n# Config file ../build-config.sh created, please edit it to configure the build\n\nvim ./build-config.sh\n```\n\nReview and customize the `build-config.sh` configuration file according to your environment requirements. The file contains network ports, domain settings, and other important parameters. Once configured, run the build script again to generate the necessary artifacts:\n\n```bash\n../build.sh hostcfg\n\n# If everything is okay, you should see the built artifacts in the `build` directory.\n$ ls\ncerts  images  dstack-kms  kms.toml  run  dstack-vmm  vmm.toml  dstack-gateway  gateway.toml\n```\n\n### Download guest image or build guest image from source\n\n```bash\n# This will download the guest image from the release page.\n../build.sh dl 0.5.2\n```\n\nOr build guest image from source:\n\n```bash\n# This will build the guest image from source using the yocto meta layer. This will take a while.\n../build.sh guest\n```\n\n> **Note on Reproducible Builds**: The build command above does not guarantee reproducibility. For reproducible builds across different build environments, please refer to the [reproducible build instructions](https://github.com/Dstack-TEE/meta-dstack?tab=readme-ov-file#reproducible-build-the-guest-image) in the meta-dstack repository.\n\n### Run components\nNow you can open 3 terminals to start the components:\n\n1. Run `./dstack-kms -c kms.toml`\n2. Run `sudo ./dstack-gateway -c gateway.toml`\n3. Run `./dstack-vmm -c vmm.toml`\n\n⚠️ *Warning: this is for local development, and the kms is not secure, so you should not use it in production.*\nFor production, you should follow the [deployment guide](./docs/deployment.md) and read the [security guide](./docs/security-guide/security-guide.md).\n\n## Deploy an App\nOpen the dstack-vmm webpage [http://localhost:9080](http://localhost:9080)(change the port according to your configuration) on your local machine to deploy a `docker-compose.yaml` file:\n\n![vmm](./docs/assets/vmm.png)\n\nAfter the container deployed, it should need some time to start the CVM and the containers. Time would be vary depending on your workload.\n\n- Click the [Logs] button to see the logs of the CVM, you can see if the container is finished starting there.\n\n- Once the container is running, you can click the [Dashboard] button to see some information of the container. And the logs of the containers can be seen in the [Dashboard] page.\n\n    ![dstack-guest-agent](./docs/assets/guest-agent.png)\n\n- You can open dstack-gateway's dashboard at [https://localhost:9070](https://localhost:9070) to see the CVM's wireguard ip address, as shown below:\n\n![dstack-gateway](./docs/assets/gateway.png)\n\n## Pass Secrets to Apps\nWhen deploying a new App, you can pass private data via Encrypted Environment Variables. These variables can be referenced in the docker-compose.yaml file as shown below:\n\n![secret](./docs/assets/secret.png)\n\nThe environment variables will be encrypted in the client-side and decrypted in the CVM before being passed to the containers.\n\n## Access the App\n\nOnce the app is deployed and listening on an HTTP port, you can access the HTTP service via dstack-gateway's public domain. The ingress mapping rules are:\n\n- `<id>[s].<base_domain>` maps to port `80` or `443` if with `s` in the CVM.\n- `<id>-<port>[s].<base_domain>` maps to port `<port>` in the CVM.\n\nFor example, `3327603e03f5bd1f830812ca4a789277fc31f577-8080.app.kvin.wang` maps to port `8080` in the CVM.\n\nWhere the `<id>` can be either the app id or the instance id. If the app id is used, one of the instances will be selected by the load balancer.\nIf the `id-port` part ends with `s`, it means the TLS connection will be passthrough to the app rather than terminating at dstack-gateway.\n\nYou can also ssh into the CVM to inspect more information, if your deployment uses the image `dstack-x.x.x-dev`:\n\n```bash\n# The IP address of the CVM can be found in the dstack-gateway dashboard.\nssh [email protected]\n```\n\n## Getting TDX quote in docker container\n\nTo get a TDX quote within app containers:\n\n1. Mount `/var/run/dstack.sock` to the target container in `docker-compose.yaml`\n\n    ```yaml\n    version: '3'\n    services:\n    nginx:\n        image: nginx:latest\n        volumes:\n        - /var/run/dstack.sock:/var/run/dstack.sock\n        ports:\n        - \"8080:80\"\n        restart: always\n    ```\n\n2. Execute the quote request command in the container.\n\n    ```bash\n    # The argument report_data accepts binary data encoding in hex string.\n    # The actual report_data passing the to the underlying TDX driver is sha2_256(report_data).\n    curl --unix-socket /var/run/dstack.sock http://localhost/GetQuote?report_data=0x1234deadbeef | jq .  \n    ```\n\n## Container logs\n\nContainer logs can be obtained from the CVM's `dashboard` page or by curl:\n\n```bash\ncurl 'http://<appid>.app.kvin.wang:9090/logs/<container name>?since=0&until=0&follow=true&text=true&timestamps=true&bare=true'\n```\n\nReplace `<appid>` and `<container name>` with actual values. Available parameters:\n\n- since=0: Starting Unix timestamp for log retrieval\n- until=0: Ending Unix timestamp for log retrieval\n- follow: Enables continuous log streaming\n- text: Returns human-readable text instead of base64 encoding\n- timestamps: Adds timestamps to each log line\n- bare: Returns the raw log lines without json format\n\nThe response of the RPC looks like:\n```\n$ curl 'http://0.0.0.0:9190/logs/zk-provider-server?text&timestamps'\n{\"channel\":\"stdout\",\"message\":\"2024-09-29T03:05:45.209507046Z Initializing Rust backend...\\n\"}\n{\"channel\":\"stdout\",\"message\":\"2024-09-29T03:05:45.209543047Z Calling Rust function: init\\n\"}\n{\"channel\":\"stdout\",\"message\":\"2024-09-29T03:05:45.209544957Z [2024-09-29T03:05:44Z INFO  rust_prover] Initializing...\\n\"}\n{\"channel\":\"stdout\",\"message\":\"2024-09-29T03:05:45.209546381Z [2024-09-29T03:05:44Z INFO  rust_prover::groth16] Starting setup process\\n\"}\n```\n\n## TLS Passthrough with Custom Domain\n\ndstack-gateway supports TLS passthrough for custom domains.\n\nSee the example [here](https://github.com/Dstack-TEE/dstack-examples/tree/main/custom-domain/dstack-ingress) for more details.\n\n## Upgrade an App\n\nGot to the dstack-vmm webpage, click the [Upgrade] button, select or paste the compose file you want to upgrade to, and click the [Upgrade] button again.\nThe app id does not change after the upgrade. Stop and start the app to apply the upgrade.\n\n## HTTPS Certificate Transparency\n\nIn the tutorial above, we used a TLS certificate with a private key external to the TEE. To establish trust, we need to generate and maintain the certificate's private key within the TEE and provide evidence that all TLS certificates for the domain were originate solely from dstack-gateway CVM.\n\nBy combining Certificate Transparency Logs and CAA DNS records, we can make best effort to minimize security risks. Here's our approach:\n\n- Set CAA records to allow only the account created in dstack-gateway CVM to request Certificates.\n- Launch a program to monitor Certificate Transparency Log and give alarm once any certificate issued to a pubkey that isn’t generated by dstack-gateway CVM.\n\n### Configurations\n\nTo launch Certbot, you need to own a domain hosted on Cloudflare. Obtain an API token with DNS operation permissions from the Cloudflare dashboard. Configure it in the `build-config.sh`:\n\n```bash\n# The directory to store the auto obtained TLS certificate and key\nGATEWAY_CERT=${CERBOT_WORKDIR}/live/cert.pem\nGATEWAY_KEY=${CERBOT_WORKDIR}/live/key.pem\n\n# for certbot\nCF_ZONE_ID=cc0a40...\nCF_API_TOKEN=g-DwMH...\n# ACME_URL=https://acme-v02.api.letsencrypt.org/directory\nACME_URL=https://acme-staging-v02.api.letsencrypt.org/directory\n```\n\nThen re-run the ../build.sh:\n\n```bash\n../build.sh\n```\n\n### Launch certbot\n\nThen run the certbot in the `build/` and you will see the following log:\n```text\n$ RUST_LOG=info,certbot=debug ./certbot renew -c certbot.toml\n2024-10-25T07:41:00.682990Z  INFO certbot::bot: creating new ACME account\n2024-10-25T07:41:00.869246Z  INFO certbot::bot: created new ACME account: https://acme-staging-v02.api.letsencrypt.org/acme/acct/168601853\n2024-10-25T07:41:00.869270Z  INFO certbot::bot: setting CAA records\n2024-10-25T07:41:00.869276Z DEBUG certbot::acme_client: setting guard CAA records for app.kvin.wang\n2024-10-25T07:41:01.740767Z DEBUG certbot::acme_client: removing existing CAA record app.kvin.wang 0 issuewild \"letsencrypt.org;validationmethods=dns-01;accounturi=https://acme-staging-v02.api.letsencrypt.org/acme/acct/168578683\"\n2024-10-25T07:41:01.991298Z DEBUG certbot::acme_client: removing existing CAA record app.kvin.wang 0 issue \"letsencrypt.org;validationmethods=dns-01;accounturi=https://acme-staging-v02.api.letsencrypt.org/acme/acct/168578683\"\n2024-10-25T07:41:02.216751Z DEBUG certbot::acme_client: setting CAA records for app.kvin.wang, 0 issue \"letsencrypt.org;validationmethods=dns-01;accounturi=https://acme-staging-v02.api.letsencrypt.org/acme/acct/168601853\"\n2024-10-25T07:41:02.424217Z DEBUG certbot::acme_client: setting CAA records for app.kvin.wang, 0 issuewild \"letsencrypt.org;validationmethods=dns-01;accounturi=https://acme-staging-v02.api.letsencrypt.org/acme/acct/168601853\"\n2024-10-25T07:41:02.663824Z DEBUG certbot::acme_client: removing guard CAA records for app.kvin.wang\n2024-10-25T07:41:03.095564Z DEBUG certbot::acme_client: generating new cert key pair\n2024-10-25T07:41:03.095678Z DEBUG certbot::acme_client: requesting new certificates for *.app.kvin.wang\n2024-10-25T07:41:03.095699Z DEBUG certbot::acme_client: creating new order\n2024-10-25T07:41:03.250382Z DEBUG certbot::acme_client: order is pending, waiting for authorization\n2024-10-25T07:41:03.283600Z DEBUG certbot::acme_client: creating dns record for app.kvin.wang\n2024-10-25T07:41:04.027882Z DEBUG certbot::acme_client: challenge not found, waiting 500ms tries=2 domain=\"_acme-challenge.app.kvin.wang\"\n2024-10-25T07:41:04.600711Z DEBUG certbot::acme_client: challenge not found, waiting 1s tries=3 domain=\"_acme-challenge.app.kvin.wang\"\n2024-10-25T07:41:05.642300Z DEBUG certbot::acme_client: challenge not found, waiting 2s tries=4 domain=\"_acme-challenge.app.kvin.wang\"\n2024-10-25T07:41:07.715947Z DEBUG certbot::acme_client: challenge not found, waiting 4s tries=5 domain=\"_acme-challenge.app.kvin.wang\"\n2024-10-25T07:41:11.724831Z DEBUG certbot::acme_client: challenge not found, waiting 8s tries=6 domain=\"_acme-challenge.app.kvin.wang\"\n2024-10-25T07:41:19.815990Z DEBUG certbot::acme_client: challenge not found, waiting 16s tries=7 domain=\"_acme-challenge.app.kvin.wang\"\n2024-10-25T07:41:35.852790Z DEBUG certbot::acme_client: setting challenge ready for https://acme-staging-v02.api.letsencrypt.org/acme/chall-v3/14584884443/mQ-I2A\n2024-10-25T07:41:35.934425Z DEBUG certbot::acme_client: challenges are ready, waiting for order to be ready\n2024-10-25T07:41:37.972434Z DEBUG certbot::acme_client: order is ready, uploading csr\n2024-10-25T07:41:38.052901Z DEBUG certbot::acme_client: order is processing, waiting for challenge to be accepted\n2024-10-25T07:41:40.088190Z DEBUG certbot::acme_client: order is valid, getting certificate\n2024-10-25T07:41:40.125988Z DEBUG certbot::acme_client: removing dns record 6ab5724e8fa7e3e8f14e93333a98866a\n2024-10-25T07:41:40.377379Z DEBUG certbot::acme_client: stored new cert in /home/kvin/codes/meta-dstack/dstack/build/run/certbot/backup/2024-10-25T07:41:40.377174477Z\n2024-10-25T07:41:40.377472Z  INFO certbot::bot: checking if certificate needs to be renewed\n2024-10-25T07:41:40.377719Z DEBUG certbot::acme_client: will expire in Duration { seconds: 7772486, nanoseconds: 622281542 }\n2024-10-25T07:41:40.377752Z  INFO certbot::bot: certificate /home/kvin/codes/meta-dstack/dstack/build/run/certbot/live/cert.pem is up to date\n```\n\nWhere the command did are:\n\n- Registered to letsencrypt and got a new account `https://acme-staging-v02.api.letsencrypt.org/acme/acct/168601853`\n- Auto set CAA records for the domain on cloudflare, you can open the CF dashboard to see the record:\n\n    ![certbot-caa](./docs/assets/certbot-caa.png)\n\n- Auto requested a new certificate from Let's Encrypt. Automatically renews the certificate to maintain its validity\n\n### Launch dstack-gateway\n\nExecute dstack-gateway with `sudo ./dstack-gateway -c gateway.toml`, then access the web portal to check the dstack-gateway CVM managed Let's Encrypt account. The account's private key remains securely sealed within the TEE.\n\n![gateway-accountid](./docs/assets/gateway-accountid.png)\n\n## Certificate transparency log monitor\n\nTo enhance security, we've limited TLS certificate issuance to dstack-gateway via CAA records. However, since these records can be modified through Cloudflare's domain management, we need to implement global CA certificate monitoring to maintain security oversight.\n\n`ct_monitor` tracks Certificate Transparency logs via [https://crt.sh](https://crt.sh/?q=app.kvin.wang), comparing their public key with the ones got from dstack-gateway RPC. It immediately alerts when detecting unauthorized certificates not issued through dstack-gateway:\n\n```text\n$ ./ct_monitor -t https://localhost:9010/prpc -d app.kvin.wang\n2024-10-25T08:12:11.366463Z  INFO ct_monitor: monitoring app.kvin.wang...\n2024-10-25T08:12:11.366488Z  INFO ct_monitor: fetching known public keys from https://localhost:9010/prpc\n2024-10-25T08:12:11.566222Z  INFO ct_monitor: got 2 known public keys\n2024-10-25T08:12:13.142122Z  INFO ct_monitor: ✅ checked log id=14705660685\n2024-10-25T08:12:13.802573Z  INFO ct_monitor: ✅ checked log id=14705656674\n2024-10-25T08:12:14.494944Z ERROR ct_monitor: ❌ error in CTLog { id: 14666084839, issuer_ca_id: 295815, issuer_name: \"C=US, O=Let's Encrypt, CN=R11\", common_name: \"kvin.wang\", name_value: \"*.app.kvin.wang\", not_before: \"2024-09-24T02:23:15\", not_after: \"2024-12-23T02:23:14\", serial_number: \"03ae796f56a933c8ff7e32c7c0d662a253d4\", result_count: 1, entry_timestamp: \"2024-09-24T03:21:45.825\" }\n2024-10-25T08:12:14.494998Z ERROR ct_monitor: error: certificate has issued to unknown pubkey: 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\n```\n\n# Troubleshooting\n\n### Error from dstack-vmm: qemu-system-x86_64: -device vhost-vsock-pci,guest-cid=<id>: vhost-vsock: unable to set guest cid: Address already in use\n\n`dstack-vmm` may throw this error when creating a new VM if the [Unix Socket CID](https://man7.org/linux/man-pages/man7/vsock.7.html) is occupied. To solve the problem, first, you should list the occupied CID:\n\n```bash\nps aux | grep 'guest-cid='\n```\n\nThen choose a new range of the CID not conflicting with the CID in use. You can change `build/vmm.toml` file and restart `dstack-vmm`. This error should disappear. For example, you may find 33000-34000 free to use:\n\n```toml\n[cvm]\ncid_start = 33000\ncid_pool_size = 1000\n```\n\nWhen building the dstack from scratch, you should change the CID configs in `build-config.sh` instead, because `vmm.toml` file is generated by `build.sh`. Its content is derived from `build-config.sh`.\n\nYou may encounter this problem when upgrading from an older version of dstack, because CID was introduced in `build-config.sh` in later versions. In such case, please follow the docs to add the missing entries in `build-config.sh` and rebuild dstack.\n\n### Error: Operation not permitted when building guest image\n\nWhen running `../build.sh guest`, you might encounter this error:\n\n```\nTraceback (most recent call last):\n  File \"/meta-dstack/poky/bitbake/bin/bitbake-worker\", line 278, in child\n    bb.utils.disable_network(uid, gid)\n  File \"/meta-dstack/poky/bitbake/lib/bb/utils.py\", line 1696, in disable_network\n    with open(\"/proc/self/uid_map\", \"w\") as f:\nPermissionError: [Errno 1] Operation not permitted\n```\n\nThis error occurs because Ubuntu 23.10 and later versions restrict unprivileged user namespaces by default. To fix this, run:\n\n```bash\nsudo sysctl kernel.apparmor_restrict_unprivileged_userns=0\n```\n\nThen try building again. For more information about this restriction, see the [Ubuntu discourse post](https://discourse.ubuntu.com/t/spec-unprivileged-user-namespace-restrictions-via-apparmor-in-ubuntu-23-10/37626).\n\n\n# Contributors\n\nDstack is proudly built by open source and Pi-rateship contributors:\n\n- Phala Network: [Kevin Wang](https://github.com/kvinwang), [Shelven Zhou](https://github.com/shelvenzhou), [Leechael](https://github.com/leechael)\n- Teleport: [Andrew Miller](https://github.com/amiller), [Sxy Sun](https://github.com/sxysun)\n- Flashbots: [Tina](https://github.com/CarboClanC), [Mateusz](https://github.com/Ruteri), [Dmarz](https://github.com/dmarzzz), [Moe](https://github.com/MoeMahhouk)\n- Ithaca: [Georgios](https://github.com/gakonst)\n- Fabric: [@gaoist](https://x.com/gaoist)\n- And many more...\n\nThe inspiration for this work stems from [Andrew Miller](https://github.com/amiller)’s pioneering concept of a [Docker-based P2P TEE SDK](https://collective.flashbots.net/t/dstack-speedrunning-a-p2p-confidential-vm/3876).\n\nThis project cannot be built without standing on the shoulders of giants:\n\n- [konvera/meta-confidential-compute](https://github.com/konvera/meta-confidential-compute)\n\nSpecial acknowledgment to [Flashbots](https://github.com/flashbots) for building a community around TEE. The TEE Hacker House initiative, organized by [Flashbots](https://github.com/flashbots) and led by [Tina](https://github.com/CarboClanC), has brought together TEE builders to develop tools for TEE-Web3 integration. This collaborative journey has generated invaluable insights for advancing secure, confidential environments within Web3.\n\nTogether, we’re shaping the future of TEE in Web3, paving the way for more secure and developer-accessible confidential computing!\n\nFor a full list of the direct contributors to this repo, see [Contributors](https://github.com/Dstack-TEE/dstack/contributors) on GitHub.\n\n\n# License\n\nCopyright 2024 Phala Network and Contributors.\n\nLicensed under the Apache License, Version 2.0 (the \"License\"); you may not use this file except in compliance with the License. You may obtain a copy of the License at\n\n[http://www.apache.org/licenses/LICENSE-2.0](http://www.apache.org/licenses/LICENSE-2.0)"
      },
      {
        "type": "text",
        "text": "main.pdf\nDstack:  A Zero Trust Framework for Confidential Containers\nJune 23, 2025\nAbstract\nWeb3 applications require execution platforms that maintain confidentiality and integrity with-\nout relying on centralized trust authorities.  While Trusted Execution Environments (TEEs) offer\npromising capabilities for confidential computing, current implementations face significant limita-\ntions in security reliability, censorship resistance, and vendor independence when applied to Web3\ncontexts.  This paper presents Dstack, a comprehensive framework that transforms raw TEE tech-\nnology  into  a  true  Zero  Trust  platform  aligned  with  Web3  principles.   We  introduce  three  key\ninnovations:  (1) Portable Confidential Containers that enable seamless workload migration across\nheterogeneous TEE environments while maintaining security guarantees, (2) Decentralized Code\nManagement that leverages smart contracts for transparent governance of TEE applications, and\n(3) Verifiable Domain Management that ensures secure and verifiable application identity without\ncentralized authorities. Through these innovations, implemented via Dstack-OS, Dstack-KMS, and\nDstack-Gateway components, we demonstrate how to achieve both the performance advantages of\nVM-level TEE solutions and the trustless guarantees required by Web3 applications.  Our evalu-\nation shows that Dstack provides comprehensive security guarantees while maintaining practical\nusability for real-world applications.\n1    Introduction\nThe Web3 ecosystem represents a paradigm shift in digital trust models, fundamentally transforming\nthe relationship between users and application developers.  Unlike traditional systems, Web3 empowers\nusers with unprecedented control over their data through the principle of ”Code is Law” - once deployed,\ncode  operates  autonomously  and  independently  of  external  control.   This  transformation  demands\nrobust execution platforms that maintain confidentiality and integrity without relying on centralized\ntrust authorities.\nFigure 1:  The evolution of trust models from Web2 to Web3, highlighting the shift from centralized control\nto decentralized governance and execution.\nThe contrast between Web2 and Web3 architectures in Figure 1 illustrates this fundamental shift.\nIn Web2 systems, developers maintain complete control through proprietary applications and central-\nized servers, retaining administrative privileges to access and modify user data at will.  Web3’s smart\n1\ncontracts,  however,  represent  the  first  significant  step  toward  true  trustlessness  by  executing  pro-\ngrams on decentralized platforms (blockchains).  Once deployed, administrators cannot influence pro-\ngram execution, and lifecycle management (e.g., code updates) follows predefined agreements through\ndemocratic governance mechanisms like multi-signature wallets and Decentralized Autonomous Orga-\nnizations (DAOs).  This emerging trust model extends beyond basic applications to mission-critical\nscenarios such as AI model training, where data providers and model developers often have competing\ninterests,  and  autonomous  AI  agents  designed  to  operate  independently  of  human  intervention.   In\nthese  contexts,  Zero  Trust  platforms  become  essential  to  host  applications  and  enforce  verification\nmechanisms that appropriately constrain developer authority.\nA Zero Trust platform must enforce the following key principles:\n•  Code is Law: This manifests in two dimensions: (1) the application logic, once deployed, cannot\nbe  changed  unexpectedly;  and  (2)  the  lifecycle  management  of  code—including  deployment,\nupgrades, and deletion—follows predefined governance rules.\n•  Censorship Resistance:  User data remains beyond the control of any single entity, with data\navailability protected against Denial-of-Service attacks.\n•  Full Chain-of-Trust:  When users interact with applications on a Zero Trust platform,  they\nmust be able to verify all aspects of that application, including network setup, application identity\nand code logic, underlying hardware, and execution environment.\n•  Assume Breach:  The platform operates under the assumption that compromises will occur,\nimplementing  mechanisms  for  damage  containment,  rapid  recovery,  and  minimization  of  data\nexposure during security incidents.\nConfidential Computing, particularly through Trusted Execution Environments (TEEs), has emerged\nas a promising foundation for extending blockchain capabilities to support complex computational tasks\nwith confidentiality guarantees.  Recent advances in VM-level TEE solutions, including Intel TDX and\nAMD SEV, have demonstrated substantial performance improvements and developer-friendly inter-\nfaces,  making  them  compelling  candidates  for  Web3  deployment.   The  integration  of  GPUs  within\nTEEs [?] now enables verifiable execution of both Large Language Models and AI agents, providing\ncryptographic guarantees of computational integrity.\nHowever, a significant gap exists between raw TEE technology and the requirements of a true Zero\nTrust platform.  Current TEE implementations face several critical limitations when applied to Web3\ncontexts:\n•  Security Reliability:  Recent vulnerability discoveries in TEE systems have raised significant con-\ncerns  about  their  effectiveness  as  trust  anchors.   The  persistence  of  side-channel  attacks  and\nmicro-architectural vulnerabilities undermines confidence in TEE security guarantees, particu-\nlarly for high-value Web3 applications where a single compromise could lead to catastrophic data\nexposure.\n•  Censorship Vulnerability:  Conventional TEE encryption schemes bind encryption keys to spe-\ncific  hardware  instances,  creating  single  points  of  failure  that  contradict  Web3’s  requirement\nfor censorship resistance.  This architectural limitation means that data availability cannot be\nguaranteed if specific hardware instances are compromised or become unavailable.\n•  Vendor Dependencies:  Current trust models heavily rely on centralized hardware manufacturers\nand verification processes, introducing risks of vendor lock-in and potential censorship vectors.\nThis centralization contradicts Web3’s core principles of decentralization and trustlessness.\n•  Incomplete Verifiability:  While TEEs provide Remote Attestation capabilities to verify applica-\ntion and hardware identity, they fail to deliver the comprehensive chain of trust required in Zero\nTrust environments.  Users need guarantees that programs will process their data as expected\nand cannot be modified without proper authorization—capabilities beyond current attestation\nmechanisms.\nTo bridge this gap between raw TEE technology and Zero Trust requirements, we present Dstack,\na comprehensive framework for confidential containers that introduces three key innovations:\n2\n•  Portable Confidential Container: Our architecture enables seamless migration of confidential\nworkloads across different TEE instances and hardware vendors,  significantly reducing vendor\nlock-in risks while maintaining robust security guarantees.  This innovation directly addresses the\ncensorship vulnerability and vendor dependency limitations by providing hardware abstraction\nand state continuity across heterogeneous TEE environments.\n•  Decentralized Code Management:  We implement a comprehensive governance framework\nthat leverages smart contracts for transparent and decentralized management of TEE applica-\ntions.  This  system ensures verifiable deployment  and upgrade processes,  enforcing the  “Code\nis Law” principle by binding application lifecycles to on-chain governance decisions.  This inno-\nvation addresses the incomplete verifiability limitation by creating an immutable audit trail of\napplication changes.\n•  Verifiable Domain Management: Our novel approach to certificate management ensures that\nconfidential containers can exclusively control domains and provide native HTTPS support to\nTEE applications without relying on centralized authorities.  This system serves as a middleware\nbetween TEE applications and existing TLS-based networks, enabling users to establish end-to-\nend encrypted channels to TEE applications without modifications to client software.\nThese innovations are implemented through a cohesive system architecture comprising three core\ncomponents:\n•  Dstack-OS: A hardware abstraction layer with a minimized operating system image that elimi-\nnates differences in underlying TEE hardware while reducing the attack surface.  This component\nprovides a consistent, secure runtime environment across diverse TEE implementations.\n•  Dstack-KMS:  A  blockchain-controlled  key  management  service  that  replaces  hardware-based\nencryption schemas with an independent service for generating and managing secret keys.  This\ncomponent  enables  secure  data  migration  across  TEE  instances  and  supports  key  rotation  to\nprovide forward and backward data secrecy, mitigating the impact of potential TEE compromises.\n•  Dstack-Ingress and Dstack-Gateway: Complementary systems providing TEE-controlled domain\nmanagement through different approaches—Dstack-Ingress enables applications to specify cus-\ntom domains with minimal integration requirements, while Dstack-Gateway offers pre-registered\nwildcard domains requiring no application code changes.\nBy addressing the critical limitations of current TEE implementations, Dstack establishes a compre-\nhensive framework that transforms raw TEE technology into a true Zero Trust platform aligned with\nWeb3’s fundamental principles.  Our approach not only enhances the security and reliability of confi-\ndential computing but also provides a practical path toward truly decentralized, censorship-resistant\ninfrastructure for next-generation applications.\nThe remainder of this paper details the technical design of Dstack, evaluates its performance and\nsecurity characteristics, and demonstrates how our innovations collectively create a Zero Trust platform\nthat maintains the performance advantages of VM-level TEE solutions while addressing their inherent\nlimitations in Web3 contexts.\n2    System Design\n2.1    Portable Confidential Container\nContainerization has transformed cloud-native application deployment by providing unparalleled porta-\nbility and scalability through effective data separation.  These capabilities are particularly critical for\nTrusted Execution Environment (TEE) applications, as they directly address the inherent limitations\noutlined in Section 1:\n•  Security Reliability:  Containerized applications can be efficiently transferred from compro-\nmised TEE hardware to secure instances,  preserving code integrity.  Together with our secure\ndata migration mechanism that ensures both forward and backward secrecy, this approach sig-\nnificantly limits privacy leakage risks even when individual TEE instances are compromised.\n3\nFigure 2:  The architecture of Dstack, including Dstack-OS and Dstack-KMS. Dstack-OS provides a hardware\nabstraction layer with a minimized operating system image, while Dstack-KMS replaces the hardware-based\ndata encryption keys with a blockchain-controlled key management service.  TODO: redraw this to put the\ncomponents into solutions.\n•  Censorship Resistance: The architecture’s inherent scalability provides robust defense against\nDenial-of-Service attacks. Additionally, by decoupling data storage from execution environments,\nestablished  data  availability  solutions  can  be  readily  integrated  to  ensure  persistent  access  to\napplication data.\n•  Vendor  Independence:   Our  hardware  abstraction  layer  enables  confidential  containers  to\noperate across diverse TEE hardware platforms without modification, eliminating vendor lock-in\nwhile facilitating rapid adoption of emerging TEE technologies as they become available.\nHowever, implementing truly portable confidential containers presents substantial technical chal-\nlenges that differentiate them from conventional containerization.  Two fundamental obstacles must be\novercome:\nFirst, existing TEE implementations generate data sealing keys derived from hardware-bound root\nkeys unique to each TEE instance.  This architectural design creates an inherent barrier to portability\n— data encrypted by one TEE instance cannot be decrypted by any other, even when running identical\napplication code.  Prior research has largely circumvented this limitation by restricting TEEs to state-\nless applications, but this approach severely constrains their utility in complex real-world scenarios.\nSecond,  TEE implementations from different vendors impose disparate specifications for deploy-\nable programs.  This fragmentation forces developers to create and maintain multiple artifacts across\nplatforms, each requiring separate (and expensive) code reviews to verify functional equivalence — a\nprocess that undermines the trust guarantees central to Web3 applications.\nTo address these challenges comprehensively, we introduce two complementary components: Dstack-\nKMS and Dstack-OS.\n2.1.1    Dstack-KMS: Blockchain-Controlled Secret Derivation\nDstack-KMS  is  a  secret  derivation  service  that  fundamentally  transforms  how  encryption  keys  are\nmanaged in confidential computing environments.  Its primary function is to generate a unique and\nstable secret (the Root Key ) for each application based on its code and configurations.  This root key\n4\nserves as the foundation for deriving additional application-specific secrets used for data encryption\nand verifiable random number generation.\nUnlike hardware-based encryption approaches, Dstack-KMS deliberately decouples key generation\nfrom specific TEE hardware instances.  This architectural decision enables the critical capability of\nencrypted  data  migration  between  different  TEE  instances,  with  decryption  possible  after\nproper authorization.  This feature is essential for achieving true censorship resistance.\nGiven  its  position  as  the  root-of-trust  for  the  entire  system,  the  verifiability  and  availability  of\nDstack-KMS are paramount.  Unlike previous approaches [?] that assume TEE infallibility, our threat\nmodel explicitly acknowledges that TEEs can be compromised.  To address this reality, Dstack-\nKMS  implements  comprehensive  key  rotation  capabilities  that  provide  both  backward  and  forward\nsecrecy for application data. This ensures that even if a specific TEE hardware instance is compromised,\napplications can be migrated with limited data exposure.\nFigure 3:  The key derivation hierarchy of Intel SGX illustrates how conventional TEE implementations bind\nencryption keys to hardware.\nTo understand the limitations of conventional approaches, Figure 3 illustrates the key derivation\nhierarchy in Intel SGX. This design uses a hardware-bound key to both identify the TEE instance (for\nRemote Attestation) and generate encryption keys for data sealing.  While this approach effectively\nestablishes hardware identity, it fundamentally undermines censorship resistance:\n•  The root key cannot be updated, meaning a compromised TEE with a leaked root key remains\npermanently vulnerable even after patching the underlying vulnerability.\n•  Encrypted data becomes intrinsically bound to specific TEE hardware instances, creating single\npoints of failure that contradict Web3’s censorship resistance requirements.\nOur  Dstack-KMS  addresses  these  limitations  by  delegating  secret  generation  to  an  independent\nservice that ensures encrypted data remains portable across TEE instances.\nAs illustrated in Figure 4, Dstack-KMS comprises an on-chain governance smart contract coupled\nwith an off-chain peer-to-peer network where the actual secret derivation service operates.  To ensure\ncomprehensive verifiability of the Dstack-KMS program’s integrity and correctness, we implement a\nmulti-stage verification process:\n1.  The Dstack-KMS codebase is fully open-sourced [?], enabling thorough code and security reviews\nto verify key management logic and ensure the absence of backdoors.\n5\nFigure 4:  The architecture of Dstack-KMS combines on-chain governance through smart contracts with an\noff-chain P2P network of secret derivation service nodes.  This design ensures both verifiability and resilience\nagainst compromise.\n2.  Executable  binaries  are  produced  through  reproducible  build  processes,  allowing  verifiers  to\nconfirm that the runtime code matches the reviewed source code.\n3.  The cryptographic digest of valid executables is published through the governance smart contract,\ncreating an immutable reference for verification.\n4.  Each service node operates within its own TEE instance.  Critically, we rely on the TEE solely for\nmeasuring the executable and ensuring it matches the on-chain digest—not for the fundamental\nsecurity of the key management process.\nThis verification framework ensures that Dstack-KMS remains trustworthy to any third-party verifier\nwhile avoiding dependency on the absolute security of any single TEE instance.\nThe core logic of each Dstack-KMS service node is intentionally minimalist, focusing exclusively on\nthe generation and secure distribution of the root key, along with deriving encryption keys for TEE\napplications.  This simplicity enables the implementation of Multi-Party Computation (MPC) based\nthreshold key generation and derivation without concerning performance overhead.  We have developed\ntwo complementary implementations:\n•  Simple Duplication:  The first node in the P2P network generates a cryptographically secure\nrandom number as the root key, then shares it with other nodes after verifying their attestation\nreports.  All nodes maintain identical copies of the root key and derive consistent encryption keys\nfor  applications.   This  approach  maximizes  availability—as  long  as  at  least  one  node  remains\noperational, the root key can be recovered.\n•  MPC-Based Key Generation:  While simple duplication provides robust availability, it cre-\nates vulnerability to single-node compromises.  Our MPC implementation uses Shamir’s Secret\nSharing scheme [?] to distribute the root key across multiple nodes, ensuring that compromising\nany individual node (or even up tot− 1 nodes, wheret is the configured threshold) does not\nexpose  the  root  key.   This  approach  also  enables  advanced  features  like  key  rotation  without\nrequiring application reconfiguration.\nKey Derivation    Dstack-KMS implements a comprehensive key derivation framework to generate\napplication-specific keys from the root key:\n•  Application CA Key:  Derived from the root CA key using the application’s unique identifier\n(calculated as the hash of the application’s code and configuration).\n•  Disk Encryption Key:  Derived using a combination of the application identifier and instance\nidentifier, enabling secure storage with portability.\n6\n•  Environment Encryption Key: Derived using the application identifier alone, allowing secure\nenvironment variable management across instances.\n•  ECDSA Key:  Derived from the root ECDSA key, providing applications with consistent cryp-\ntographic identity for signing operations.\nEach derived key maintains cryptographic isolation while ensuring consistency across different TEE\ninstances running the same application.\nKey Rotation    A critical security feature of Dstack-KMS is its support for key rotation, which signif-\nicantly limits the exposure window during potential attacks while ensuring both forward and backward\nsecrecy for sealed data.  Key rotation procedures are initiated exclusively through the governance smart\ncontract, ensuring transparency and auditability.  We discuss two distinct rotation mechanisms:\n•  Root Key Share Rotation:  Our MPC-based implementation enables rotation of individual\nkey  shares  without  modifying  the  root  key  itself.   This  process  enhances  root  key  security  by\nregularly updating the distribution mechanism while remaining transparent to applications, as\nall derived application keys remain unchanged.\n•  Root Key Rotation:  In scenarios where the root key may have been compromised, we support\ncomplete root key rotation.  This process generates an entirely new root key and implements a\ncontrolled handover period during which both old and new keys remain valid.  This transition\nwindow  allows  applications  to  re-encrypt  their  data  with  keys  derived  from  the  new  root  key\nbefore the old root key is permanently destroyed, minimizing service disruption while enhancing\nsecurity.\nThrough these mechanisms, Dstack-KMS provides the foundation for truly portable confidential con-\ntainers by decoupling encryption from hardware dependencies while maintaining robust security guar-\nantees.\n2.1.2    Dstack-OS: Hardware Abstraction Layer\nDstack-OS provides a comprehensive hardware abstraction layer with a minimized operating system\nimage that bridges the gap between application containers and VM-level TEE implementations.  This\nlayer enables applications to deploy across diverse TEE environments without code modifications while\nmaintaining security integrity.  As a shared component across all TEE applications, Dstack-OS must be\nintrinsically secure and verifiable, with no administrative backdoors that could compromise program\ncode or user data.\nVM-level  TEE  solutions  typically  require  developers  to  provide  complete  system  images  encom-\npassing  bootloader,  kernel,  operating  system,  and  application  components.   This  requirement  not\nonly increases development complexity but also introduces potential security vulnerabilities through\nmisconfigured system components.  A secure and properly configured operating system environment\nfundamentally determines the security baseline for all TEE applications built upon it.\nFigure 5 illustrates how Dstack-OS establishes a secure and verifiable startup chain from the TEE\nhardware foundation through to user-provided container images.  Our modular design ensures that the\nmajority of the system can be reused across different TEE hardware implementations, substantially\nreducing the effort required for code review and security auditing.  Combined with reproducible build\nprocesses, this approach enables comprehensive verification of Dstack-OS with minimal overhead while\nsupporting multiple TEE hardware platforms.\nUsing Intel TDX as an exemplar (with similar procedures applicable to other TEE implementa-\ntions like AMD SEV), Dstack-OS consists of the following components,  presented in boot sequence\norder.  During this process, each component measures the next one and records these measurements\nin hardware registers, which are ultimately incorporated into the TEE attestation report:\n•  Hypervisor: When application deployment initiates, the underlying hypervisor (the TDX mod-\nule) loads the Open Virtual Machine Firmware (OVMF), enabling UEFI support for confidential\nvirtual  machines.   The  TDX  module  measures  the  OVMF  code  and  records  its  cryptographic\ndigest in the MRTD register, with the hypervisor’s integrity guaranteed by the TEE hardware\nitself.\n7\nFigure 5:  The architecture of Dstack-OS establishes a secure and verifiable startup chain from TEE hardware\nthrough to user applications.\n•  Open Virtual Machine Firmware (OVMF): The OVMF configures virtual machine hard-\nware  specifications  (CPU,  memory,  and  device  configurations)  and  records  the  configuration\nmeasurement  to  the  RTMR0  register.   It  then  loads  the  Linux  kernel  and  records  the  kernel\nimage measurement to the RTMR1 register.\n•  Kernel:  The kernel first loads an initial ramdisk (initrd) — a temporary in-memory filesystem\ncontaining  minimal  command-line  tools  and  disk  encryption  libraries.   The  initrd  mounts  the\nroot filesystem and records this measurement in the RTMR2 register.\n•  Root Filesystem: The root filesystem (RootFs) is a read-only environment containing essential\nsystem libraries and tools.  It manages the entire lifecycle of deployed applications, measuring\napplication images along with their associated key management system and storing these mea-\nsurements  in  the  RTMR3  register.   The  RootFs  serves  two  primary  functions:  (1)  providing\nthe runtime environment for user-level container images, and (2) managing application data en-\ncryption.   It  interfaces  with  Dstack-KMS  to  acquire  encryption  secrets  and  implements  Linux\nUnified Key Setup (LUKS) to encrypt application data in isolated volumes.  Data integrity is\nensured through dm-verity, a Merkle-tree-based block-level verification tool.  Finally, the RootFs\nconfigures network ingress for the application and initiates execution.\nRather than adapting existing system images, we built Dstack-OS from scratch to ensure only es-\nsential components are included in both the initrd and RootFs.  A comprehensive component inventory\nis provided in Appendix ?? for transparency and review.  Generally,  Dstack-OS includes only basic\nutilities (busybox), filesystem support, and container runtime components.  By implementing Docker\nsupport  while  delegating  orchestration  to  the  application  level,  we  maintain  a  minimal  base  image\nfootprint.\nTo ensure comprehensive verifiability, Dstack-OS is fully open-sourced and supports reproducible\nbuilds,  allowing  anyone  to  review  the  code  and  generate  identical  artifacts  for  verification.   This\napproach provides significant benefits for applications requiring security reviews,  as evaluators need\nonly review the application code rather than the entire system image.\nData Backup and Defense against Rollback Attacks    A critical challenge in confidential com-\nputing is ensuring data durability and integrity, particularly against rollback attacks where adversaries\nattempt to revert applications to previous states to bypass security checks or reuse expired secrets.\nOur architecture provides robust secure data backup support and implements robust anti-rollback\nmechanisms that application developers can integrate:\n•  Secure Backup:  Application data is encrypted using keys derived from Dstack-KMS and can\nbe backed up to external storage providers.  Since encryption keys are not bound to specific TEE\n8\ninstances, data can be restored on any authorized TEE, supporting true portability and disaster\nrecovery.\n•  Monotonic Counters: To prevent rollback attacks, developers can implement monotonic coun-\nters that increment with each critical data update, incorporating the counter value into the en-\ncrypted data.  During restoration, applications verify that the counter value equals or exceeds\nthe last known value, preventing replay of outdated snapshots.\nBy combining these techniques,  Dstack ensures both the recoverability and integrity of confidential\ndata across portable container migrations and backup scenarios.\nTogether, Dstack-KMS and Dstack-OS provide the foundational infrastructure for truly portable\nconfidential containers that maintain security and integrity across heterogeneous TEE environments\nwhile eliminating vendor lock-in and supporting comprehensive verifiability.\n2.2    Decentralized Code Management\nA core principle of Zero Trust platforms is the enforcement of “Code is Law”, ensuring that application\ncode  operates  as  intended  without  unexpected  modifications.   While  TEE  hardware  provides  code\nintegrity guarantees during execution, it cannot independently prevent administrators from deploying\nmalicious code or making unauthorized modifications.  Conversely, smart contracts have established\nrobust methodologies for implementing programmable governance over code lifecycle management —\nsuch as multi-signature requirements that prevent single-actor manipulation.\nOur  decentralized  code  management  framework  bridges  these  two  worlds  by  placing  TEE  ap-\nplication governance under smart contract control,  creating a transparent and auditable system for\napplication deployment and updates that aligns with Web3 principles.\nFigure 6:  The architecture of decentralized code management integrates on-chain governance contracts with\noff-chain TEE through Dstack-KMS.\nAs illustrated in Figure 6, our architecture consists of two complementary components:  on-chain\ngovernance  smart  contracts  and  off-chain  TEE  execution  environments  connected  through  Dstack-\nKMS. This design establishes the on-chain contracts as the definitive root-of-trust for the entire system.\nEvery operation — from initial deployment to code upgrades — must first be initiated and authorized\nthrough the governance contracts before off-chain TEE instances can execute these operations.\nThe governance framework implements a two-tier structure:\n•  KmsAuth Contract:  Serves as the global authority controlling Dstack-KMS operations.  This\ncontract maintains the registry of authorized applications and their governance parameters, en-\nforcing system-wide policies for TEE deployment.  By controlling whether Dstack-KMS shares\n9\napplication  secrets  with  specific  TEE  instances,  the  KmsAuth  contract  effectively  determines\nwhether applications can decrypt their data, thus controlling their complete lifecycle.\n•  AppAuth Contracts:  Individual governance contracts deployed for each application that de-\nfine  application-specific  management  rules.   These  contracts  specify  permissible  code  versions\n(through cryptographic hashes), authorized TEE instance identities, and upgrade approval re-\nquirements.  This modular approach enables customized governance models ranging from tradi-\ntional multi-signature schemes to complex DAO voting mechanisms, allowing each application\nto implement governance appropriate to its requirements.\nThe enforcement mechanism operates through Dstack-KMS, which will only provide application\nsecrets  to  TEE  instances  running  code  versions  explicitly  authorized  by  the  governance  contracts.\nThis creates a cryptographically enforced governance system where unauthorized code versions cannot\naccess application data, regardless of administrative privileges.\nTo  illustrate  this  mechanism,  consider  a  code  upgrade  process  for  an  application  using  a  multi-\nsignature AppAuth contract in Figure 6:\n1.  Developers  publish  the  new  code  version  and  submit  its  cryptographic  hash  to  the  AppAuth\ncontract.\n2.  The  contract  initiates  the  approval  process,  requiring  signatures  from  designated  key  holders\n(e.g., core developers, security auditors, and community representatives).\n3.  Each signature is recorded on-chain, creating an immutable audit trail of the approval process.\n4.  Once the required signature threshold is reached, the AppAuth contract updates its registry of\nauthorized code versions.\n5.  The  KmsAuth  contract,  monitoring  the  AppAuth  contract,  updates  its  authorization  records\naccordingly.\n6.  Dstack-KMS,  which  continuously  synchronizes  with  the  KmsAuth  contract,  begins  providing\napplication secrets to TEE instances running the newly approved code version.\n7.  TEE instances can now deploy the new code with full access to encrypted application data.\nThis process ensures that every code change follows predefined governance rules with complete trans-\nparency.  The on-chain approval records create an immutable audit trail that allows users to verify\nthe entire history of application changes, while the cryptographic enforcement through Dstack-KMS\nguarantees that only properly authorized code can access application data.\nBy combining the code integrity guarantees of TEEs with the transparent governance capabilities\nof  smart  contracts,  our  decentralized  code  management  framework  ensures  that  applications  truly\nembody the ”Code is Law” principle. Every aspect of the application lifecycle—from initial deployment\nto  version  updates  and  potential  retirement—follows  predefined,  transparent  rules  that  cannot  be\ncircumvented by any single entity, including the platform operators themselves.\n2.3    Verifiable Domain Management\nA  complete  Zero  Trust  platform  must  enable  seamless  verification  for  users  across  both  Web3  and\ntraditional  Web2  environments.   Our  Verifiable  Domain  Management  system  completes  the  chain-\nof-trust  by  allowing  standard  Web  browsers  to  cryptographically  verify  TEE  applications  without\nrequiring any client-side modifications or specialized knowledge.\nThis  capability  is  critical  for  mainstream  adoption,  as  it  allows  users  to  interact  with  confiden-\ntial applications using familiar tools while maintaining the same security guarantees provided by the\nunderlying TEE infrastructure.  We implement this through two complementary components—Dstack-\nIngress and Dstack-Gateway—both leveraging our novel Zero Trust TLS (ZT-TLS) protocol.\nThe  fundamental  innovation  in  ZT-TLS  is  establishing  cryptographic  proof  that  a  specific  TLS\ncertificate  (and  therefore  a  domain)  is  exclusively  controlled  by  a  verified  TEE  application.   This\ncreates a verification chain extending from the blockchain to standard HTTPS connections, enabling\nusers to confirm application authenticity through familiar security indicators in their browsers.\n10\nFigure  7:   The  Zero  Trust  TLS  architecture  establishes  a  cryptographically  verifiable  connection  between\nstandard web browsers and TEE applications through blockchain-anchored certificate management.\n2.3.1    Zero Trust TLS Protocol\nThe  ZT-TLS  protocol  addresses  a  critical  challenge:  how  to  cryptographically  bind  a  domain  to  a\nspecific TEE application in a way that prevents unauthorized certificate issuance or domain hijacking.\nOur solution integrates three key components:\n•  TEE-Generated Certificates:  The TEE application (specifically Dstack-Gateway) generates\nits TLS certificate using application secrets derived from Dstack-KMS. This ensures the private\nkey  never  exists  outside  the  TEE  environment  and  creates  a  cryptographic  link  between  the\non-chain governance and the TLS certificate.\n•  Certificate  Authority  Authorization  (CAA):  We  leverage  DNS  CAA  records  to  restrict\nwhich  certificate authorities can  issue certificates  for managed  domains.  By  configuring CAA\nrecords  to  only  authorize  certificates  from  specific  issuers  (which  verify  TEE  attestation),  we\nprevent unauthorized certificate issuance through alternative validation methods.\n•  Certificate Transparency (CT) Monitoring:  To protect against unauthorized DNS record\nmodifications, we implement continuous monitoring of Certificate Transparency logs.  This allows\ndetection of any unauthorized certificates and provides an immutable audit trail of certificate\nissuance history.\n2.3.2    Implementation Components\nWe provide two complementary implementations to accommodate different application requirements:\n•  Dstack-Gateway:  A fully managed reverse proxy running within a TEE that provides imme-\ndiate domain verification with zero application code changes.  Applications register with Dstack-\nGateway through a simple API call, during which Dstack-Gateway verifies the application’s re-\nmote attestation report.  Once verified, applications receive a subdomain under a pre-registered\nwildcard domain (e.g., app-id.Dstack.com), with all TLS termination and certificate manage-\nment handled automatically.\n•  Dstack-Ingress:   A  more  flexible  solution  for  applications  requiring  custom  domain  names.\nDstack-Ingress provides libraries and services that enable applications to manage their own TLS\ncertificates while maintaining the same verification guarantees.  This approach requires minimal\nintegration work while supporting application-specific domain requirements.\n11\nBoth implementations ensure that certificates are cryptographically bound to verified TEE environ-\nments, with the verification chain extending from the blockchain governance contracts through to the\nTLS certificates presented to users’ browsers.\n2.3.3    Security Guarantees and Protections\nOur Verifiable Domain Management system provides several critical security guarantees:\n•  Certificate Provenance Verification:  Users can verify that the TLS certificate presented by\nan application was issued to a legitimate TEE environment by checking the certificate against\non-chain records.\n•  Domain Binding Integrity:  The combination of CAA records and Certificate Transparency\nmonitoring ensures that domains remain bound to their designated TEE applications, preventing\nunauthorized certificate issuance.\n•  Tamper-Evident Certificate Changes:  Any unauthorized attempts to modify domain con-\nfigurations or issue alternative certificates are detected through Certificate Transparency moni-\ntoring, with alerts propagated to clients.\nWhile we cannot technically prevent all attacks against centralized DNS infrastructure, our multi-\nlayered approach creates a tamper-evident system where unauthorized changes are quickly detected\nand rejected by client verification processes.  This approach aligns with the ”Assume Breach” principle\nby implementing defense-in-depth strategies that maintain security even when individual components\nare compromised.\nBy extending the verification chain from blockchain governance through TEE attestation to stan-\ndard TLS certificates, our Verifiable Domain Management system enables seamless integration of Zero\nTrust  applications  into  existing  web  infrastructure.   This  creates  a  practical  path  for  mainstream\nadoption without requiring specialized knowledge or tools from end users, while maintaining the com-\nprehensive security guarantees that define true Zero Trust platforms.\n3    Verifying TEE Applications:  A Practical Walkthrough\nTo demonstrate how Dstack fulfills the Zero Trust principles and addresses the challenges outlined in\nSection 1,  we present a practical end-to-end verification scenario.  This walkthrough illustrates how\nthe architectural components described in Section 2 work together to provide a comprehensive chain\nof trust for real-world Web3 applications.\nTraditional  Zero  Trust  programs  like  smart  contracts  achieve  verifiability  through  transparent\nsource  code  and  inputs.   However,  extending  similar  verifiability  to  real-world  applications  presents\nunique  challenges,  particularly  in  maintaining  privacy  and  compatibility  with  existing  development\npractices.   Dstack  addresses  these  challenges  through  a  comprehensive  verification  framework  that\nrequires minimal code changes.\nThis section demonstrates Dstack’s complete chain of trust through a practical example:  verifying\nthat  a  cryptographic  key  was  genuinely  generated  within  a  TEE  environment.   This  scenario  is  es-\npecially relevant for Web3 and AI Agent applications where cryptographic keys establish application\nidentity and authority.\n3.1    Threat Model\nOur verification framework assumes the correct implementation and integrity of core Dstack compo-\nnents (Dstack-OS, Dstack-KMS, Dstack-Gateway, and governance contracts). While these components’\nsecurity guarantees are detailed in later sections, we explicitly consider developers and administrators\nas potential adversaries.\nPotential attack vectors include:\n•  Application-Level Attacks\n–  Deployment of unauthorized or malicious code through falsified Docker images\n12\n–  Introduction of malicious dependencies through supply chain attacks\n–  Unauthorized application updates that bypass governance controls\n•  Infrastructure-Level Attacks\n–  Tampering with Dstack-OS to circumvent security controls\n–  Deployment of compromised key management services\n–  Operation of unpatched or vulnerable TEE firmware\n–  Execution of applications on non-TEE hardware with spoofed attestation\n•  Network-Level Attacks\n–  DNS hijacking to redirect traffic to unauthorized applications\n–  Man-in-the-middle attacks on communication channels\nDirect attacks on TEE hardware security (e.g., exploitation of hardware vulnerabilities) are con-\nsidered out of scope for this discussion and addressed separately.\n3.2    The Reproducibility Challenge\nA  fundamental  challenge  in  TEE  attestation  lies  in  bridging  the  gap  between  source  code  and  the\nactual  artifacts  (binaries  or  container  images)  running  inside  enclaves.   While  TEE  attestation  can\nprove that a specific artifact runs within a secure environment, it cannot independently verify that the\nartifact accurately represents its claimed source code.\nThis limitation creates several security risks:\n•  Source Code Manipulation:  Developers could intentionally deploy artifacts that differ from\npublicly reviewed source code\n•  Build Process Compromise:  Supply chain attacks could inject malicious code during artifact\ncreation\n•  Toolchain  Vulnerabilities:   As  demonstrated  by  the  Ken  Thompson  Hack,  even  compiler\ntoolchains could be compromised to inject malicious behavior\nTEE  quotes  only  attest  to  measurements  (cryptographic  hashes)  of  running  artifacts.   Without\nguarantees that these artifacts accurately represent reviewed source code, users cannot fully trust ap-\nplications even when running in secure enclaves.  This challenge affects all TEE applications, including\nDstack’s core components.\nFigure 8:  Comprehensive verification chain from source code to running TEE applications\nEstablishing a complete verification chain requires three key elements:\n13\n•  Source Code Verification:  Open-source code or trusted third-party review ensuring no back-\ndoors exist\n•  Build Process Integrity:  Reproducible builds allowing independent verification of artifacts\n•  Runtime Attestation:  TEE quotes proving that verified artifacts are actually running\nTraditional reproducible builds, while ideal, often introduce significant complexity through special-\nized  toolchains  and  build  scripts.   The  following  section  introduces  an  alternative  approach, In-CC\nBuild, that achieves similar guarantees with improved practicality.\n3.3    Dstack Component Verifiability\nEach  core  Dstack  component  implements  specific  verifiability  mechanisms  anchored  in  transparent,\nimmutable records.  Table 1 summarizes these mechanisms:\nComponentSourceBuild MethodRegistryVerification\nDstack-OSOpenReproducibleKmsAuthOS Digest\nDstack-KMSOpenIn-CCKmsAuthImage Hash, Root PubKey\nDstack-GatewayOpenIn-CCAppAuthImage Hash\nTable 1:  Verifiability mechanisms and trust anchors for Dstack components\nAll components maintain open-source codebases with comprehensive documentation. Dstack-OS, as\nthe foundational component, undergoes third-party security audits and implements fully reproducible\nbuilds.\nThe governance smart contracts serve as authoritative registries, anchoring each component’s trust\nbase:\n•  Dstack-OS digests are registered in KmsAuth and managed through multi-signature governance\n•  Dstack-KMS measurements and root public keys are recorded in KmsAuth\n•  Dstack-Gateway artifacts are verified through dedicated AppAuth contracts\nIn-ConfidentialContainer Build    While reproducible builds represent the gold standard for arti-\nfact verification, they often prove impractical for complex applications.  Dstack addresses this through\nIn-CC Build,  leveraging  the  verified  Dstack-OS  as  a  trusted  foundation.   The  In-CC  Build  process\nexecutes entirely within Dstack-OS environment, encompassing code fetching, compilation, and arti-\nfact creation.  By specifying precise source references (e.g., a snapshot of the codebase), the system\nproduces verifiable artifacts with measurements attested in TEE quotes.  This approach minimizes the\ntrusted computing base while eliminating the complexity of traditional reproducible builds.\n3.4    End-to-End Verification Walkthrough\nFrom a user’s perspective, verifying a TEE application in Dstack requires validating a chain of mea-\nsurements against authoritative registries,  encompassing the user application,  runtime data,  Dstack\ncomponents, and network infrastructure.  This section walks through the verification process, demon-\nstrating how each step builds upon the previous one to create a comprehensive chain of trust.\nAs shown in Figure 9, the verification chain begins with the KmsAuth smart contract, which serves\nas the root of trust for the entire system, and concludes with the key generation application running\nin a TEE. We explain the verification steps as follows.\nFirst,  the address of the Dstack-KMS governance contract (i.e.,  KmsAuth) is publicly available.\nThe KMS governance contract serves as the authoritative registry for (1) off-chain KMS nodes and\n(2) dedicated governance contracts (i.e., AppAuth) for TEE applications.  It is worth noting that the\nDstack-Gateway can be regarded as a special TEE application that attests and forwards requests to\nother user applications while maintaining consistent verification procedures.\nThe  KmsAuth  contract  records  both  the  measurements  of  off-chain  KMS  node  programs  (KMS\ndigest, which is the hash of the docker compose file and the images used in In-CC Build) and the TDX\n14\nFigure 9:  The verification chain from authoritative registries to runtime measurements\nQuote of the first KMS node, which acts as the primary key generator.  The identities of subsequent\nKMS  nodes  must  first  be  registered  in  KmsAuth  and  verified  by  the  first  KMS  node  before  they\ncan participate in key generation.  These data, together with the open-source Dstack-KMS codebase,\nallow users to verify the integrity of the KMS nodes and their code correctness.  Subsequently,  the\noff-chain KMS nodes can be considered trusted extensions and used to verify Quotes from other TEE\napplications,  which  cannot  be  achieved  by  the  on-chain  governance  contract  alone.   The  off-chain\nKMS nodes are responsible for generating and managing cryptographic keys (i.e., the root key) and\nthe corresponding certificates (explained in Section 2.3.1), which are further used to authorize TEE\napplications after they are verified, thereby avoiding redundant verification.\nSecond, users can verify the validity of Dstack-Gateway.  By default, this is delegated to the off-\nchain  KMS  nodes  during  gateway  registration,  although  users  can  always  request  the  Quote  of  the\ngateway and check the digest of its docker compose file in its governance contract and the codebase.\nAfter the KMS nodes verify the gateway, it will generate its application root key along with a certificate\nchain ending with the root certificate.\nNext, users can access the TEE application through Dstack-Gateway forwarding.  In this case, users\neffectively delegate the verification of the key generation application to the gateway.  The deployment\nof the key generation application starts from the KmsAuth contract.  The deployer first registers it\nand stores the digest (the hash of the docker compose file and the images) on the dedicated AppAuth\ncontract.  Then, as in the previous step, the off-chain KMS nodes verify the Quote of the application\nafter  it  is  deployed  to  the  TEE  and  ensure  it  matches  the  registered  digest.   Only  after  successful\nverification will the key be generated along with the certificate chain.  To be forwarded by the gateway,\nthe application must also register with it.  In this case, the gateway verifies the application’s certificate\nchain and ensures it shares the same root certificate, indicating authorization by the same KMS.\nFinally, the user can invoke the application and request proof of the key it generated.  The applica-\ntion can generate a Quote on demand, with the generated public key included as custom data in the\nQuote.\n15\n3.5    Security Analysis:  Mitigating Threats\nOur key generation example demonstrates Dstack’s comprehensive approach to security across multiple\nattack surfaces.  At the application level, the system prevents unauthorized code deployment through\nrigorous  measurement  verification  against  the  AppAuth  registry.   The  In-CC  Build  process  ensures\nall dependencies originate from verified sources,  while any updates require new registry entries and\ncomplete re-verification.  It is important to note, however, that code audit and review processes remain\nessential for ensuring application code correctness, as the In-CC Build only guarantees the integrity of\nthe build process.\nInfrastructure security is maintained through multiple mechanisms.  TDX Quotes verify Dstack-OS\nintegrity, preventing OS-level tampering.  KMS updates require multi-signature governance approval,\nsafeguarding against unauthorized changes to key management services.  The Quote verification pro-\ncess  includes  firmware  version  validation,  ensuring  applications  run  on  up-to-date  TEE  hardware.\nHardware-backed TDX Quotes effectively prevent attestation spoofing attempts.\nNetwork-level threats are mitigated through the certificate chain validation system.  This prevents\nboth  DNS  hijacking  and  man-in-the-middle  attacks  by  ensuring  authentic  application  identity  and\nenabling end-to-end encryption with verified certificates.  The combination of these security measures\nensures that cryptographic keys maintain their integrity guarantees even when confronted with sophis-\nticated attacks targeting different system layers.\nReferences\n16"
      }
    ]
  },
  {
    "role": "assistant",
    "content": "# Project Proposal Template\n\n## General Information\n1.1. Name of Project\nDstack\n\n1.2. Project Description (what it does, why it is valuable, origin and history)\nDstack is a developer-friendly and security-first SDK that simplifies the deployment of arbitrary containerized applications into Trusted Execution Environments (TEEs). It enables developers to securely deploy containerized applications in TEEs in minutes using familiar tools like docker-compose.yaml. Dstack provides safe management of secrets and sensitive data, along with built-in TLS termination for exposed services.\n\nThe project was built by Kevin Wang and others from Phala Network, inspired by Andrew Miller (Flashbots & Teleport), and has received contributions from Nethermind and many others. Dstack addresses the gap between raw TEE technology and Zero Trust platform requirements by providing portable confidential containers, decentralized code management, and verifiable domain management.\n\n1.3. How does this project align with the Consortium's Mission Statement\n[blank]\n\n1.4. Project website URL\nhttps://docs.phala.network/dstack/overview (inferred from documentation references)\n\n1.5. Social media accounts\n[blank]\n\n## Legal Information\n2.1. Project Logo URL or attachment (Vector Graphic: SVG, EPS).\n[blank]\n\n2.2. Project license. We recommend an OSI-approved license, so if the license is not one on the list, explain why.\nApache License, Version 2.0\n\n2.3. Existing financial sponsorship.\n[blank]\n\n2.4. Trademark status.\n[blank]\n\n## Technical Information\n3.1. High level assessment of project synergy with existing projects under the CCC, including how the project compliments/overlaps with existing projects, and potential ways to harmonize over time. Responses may be included both inline and/or in accompanying documentation.\n[blank]\n\n3.2. Describe the Trusted Computing Base (TCB) of the project. If the project supports multiple environments please describe each TCB. Also identify if dependencies of other project (both CCC or non-CCC) TCBs are taken.\nDstack's TCB includes:\n- Dstack-OS: A minimized operating system image that serves as a hardware abstraction layer\n- OVMF (Open Virtual Machine Firmware): Configures VM hardware specifications\n- Linux kernel with initial ramdisk (initrd)\n- Root filesystem with essential system libraries and tools\n- Intel TDX or equivalent TEE hardware as the foundation\n\nThe system establishes a secure and verifiable startup chain from TEE hardware through to user applications, with each component measuring the next and recording measurements in hardware registers that are incorporated into TEE attestation reports.\n\n3.3. Project Code of Conduct URL. We recommend a Contributor Covenant v2.0 based Code of Conduct, so if the Code of Conduct is not based on that, explain why.\n[blank]\n\n3.4. Source control URL\nhttps://github.com/Dstack-TEE/dstack\n\n3.5. Issue tracker URL\nhttps://github.com/Dstack-TEE/dstack/issues (inferred)\n\n3.6. External dependencies (including licenses, and indicate whether each is a build time or runtime dependency)\n- Intel TDX or equivalent TEE hardware (runtime)\n- Linux kernel (runtime)\n- Docker/container runtime (runtime)\n- Busybox (runtime)\n- LUKS for encryption (runtime)\n- Wireguard-tools (build time)\n- Build-essential, chrpath, diffstat, lz4, xorriso (build time)\n- Rust (build time)\n\n3.7. Standards implemented by the project, if any. Include links to any such standards.\n- TLS/HTTPS for secure communications\n- Certificate Transparency (CT) for certificate monitoring\n- Certificate Authority Authorization (CAA) for domain security\n- Remote Attestation for TEE verification\n\n3.8. Release methodology and mechanics\n[blank]\n\n3.9. Names of initial committers, if different from those submitting proposal\nInitial committers include:\n- Kevin Wang (kvinwang)\n- Shelven Zhou (shelvenzhou)\n- Leechael\n\n3.10. List of project's official communication channels (slack, irc, mailing lists)\n[blank]\n\n3.11. Project Security Response Policy\n[blank]\n\n3.12. Preferred maturity level (Incubation, Graduation, or Emeritus)\n[blank]\n\n3.13. Any additional information the TAC and Board should take into consideration when reviewing your proposal.\nDstack includes several key components:\n- dstack-vmm: Service running on bare TDX host to manage CVMs\n- dstack-gateway: Reverse proxy to forward TLS connections to CVMs\n- dstack-kms: KMS server to generate keys for CVMs\n- dstack-guest-agent: Service in CVM to serve containers' key derivation and attestation requests\n- meta-dstack: Yocto meta layer to build CVM guest images\n\nThe project provides innovative solutions for portable confidential containers, decentralized code management, and verifiable domain management, addressing critical limitations in current TEE implementations for Web3 contexts."
  },
  {
    "role": "user",
    "content": "This is the Mission Statement, fill in 1.3 with it\n\n```\nThe purpose of the Confidential Computing Consortium is to raise, budget and spend funds in support of various open source and/or open standards projects relating to:\n\ndefining confidential computing and accelerating acceptance and adoption in the market.\ndeveloping open enterprise-grade building blocks (e.g., open specifications and open source licensed projects), including a Confidential Computing portfolio and development experience, to enable easy development and management of enterprise-grade Confidential Computing applications, and\ndefining foundational services and frameworks that are Confidential Computing aware and minimize the need for trust.\n```"
  },
  {
    "role": "assistant",
    "content": "## General Information\n1.3. How does this project align with the Consortium's Mission Statement\nDstack directly aligns with the Confidential Computing Consortium's mission by providing enterprise-grade building blocks for confidential computing applications. It accelerates adoption by making TEE deployment developer-friendly through familiar tools like docker-compose, lowering the barrier to entry. Dstack defines foundational services and frameworks that are Confidential Computing aware through its comprehensive architecture (Dstack-OS, Dstack-KMS, Dstack-Gateway). The project minimizes the need for trust by implementing Zero Trust principles with portable confidential containers, decentralized code management, and verifiable domain management. By enabling seamless deployment of containerized applications in TEEs, Dstack contributes significantly to the development experience and practical adoption of confidential computing in real-world scenarios."
  },
  {
    "role": "user",
    "content": "解释下问题3.1"
  }
]

Response:

问题3.1要求评估项目与CCC（Confidential Computing Consortium）现有项目的协同性，包括项目如何补充或与现有项目重叠，以及随着时间推移可能的协调方式。这个问题需要: 1. 分析Dstack与CCC现有项目的关系 2. 确定它如何补充现有项目或与之重叠 3. 提出随时间推移可能的协调方式回答这个问题需要了解CCC当前的项目组合，以及Dstack如何与这些项目互补或重叠，以及未来可能的协作方向。由于提供的资料中没有这方面的具体信息，所以在模板中标记为"[blank]"。如果要填写这部分，需要详细了解CCC的现有项目，然后分析Dstack的功能与这些项目的关系，以及潜在的协作机会。

Model: claude-3-7-sonnet-202502192025-06-25 13:09:02

Context:

[
  {
    "role": "user",
    "content": [
      {
        "type": "text",
        "text": "Help me fill in the follow template given the project whitepaper and README file.\n\nFor fields with not enough info, leave it \"[blank]\".\n\n```\nProject Proposal Template\n\nGeneral Information\n1.1. Name of Project\n1.2. Project Description (what it does, why it is valuable, origin and history)\n1.3. How does this project align with the Consortium's Mission Statement\n1.4. Project website URL\n1.5. Social media accounts\n\nLegal Information\n2.1. Project Logo URL or attachment (Vector Graphic: SVG, EPS).\n2.2. Project license. We recommend an OSI-approved license, so if the license is not one on the list, explain why.\n2.3. Existing financial sponsorship.\n2.4. Trademark status.\n\nTechnical Information\n3.1. High level assessment of project synergy with existing projects under the CCC, including how the project compliments/overlaps with existing projects, and potential ways to harmonize over time. Responses may be included both inline and/or in accompanying documentation.\n3.2. Describe the Trusted Computing Base (TCB) of the project. If the project supports multiple environments please describe each TCB. Also identify if dependencies of other project (both CCC or non-CCC) TCBs are taken.\n3.3. Project Code of Conduct URL. We recommend a Contributor Covenant v2.0 based Code of Conduct, so if the Code of Conduct is not based on that, explain why.\n3.4. Source control URL\n3.5. Issue tracker URL\n3.6. External dependencies (including licenses, and indicate whether each is a build time or runtime dependency)\n3.7. Standards implemented by the project, if any. Include links to any such standards.\n3.8. Release methodology and mechanics\n3.9. Names of initial committers, if different from those submitting proposal\n3.10. List of project's official communication channels (slack, irc, mailing lists)\n3.11. Project Security Response Policy\n3.12. Preferred maturity level (Incubation, Graduation, or Emeritus) 3.13. Any additional information the TAC and Board should take into consideration when reviewing your proposal.\n```"
      },
      {
        "type": "text",
        "text": "README.md\n# Dstack\n\n[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/Dstack-TEE/dstack)\n\nDstack is a **developer friendly** and **security first** SDK to simplify the deployment of arbitrary containerized apps into TEE.\n\nMain features:\n\n- 🔒 Deploy containerized apps securely in TEE in minutes\n- 🛠️ Use familiar tools - just write a docker-compose.yaml\n- 🔑 Safely manage secrets and sensitive data\n- 📡 Expose services via built-in TLS termination\n\nDstack is community driven. Open sourced and built by [Kevin Wang](https://github.com/kvinwang) and many others from [Phala Network](https://github.com/Phala-Network), inspired by [Andrew Miller](https://github.com/amiller) (Flashbots & Teleport), and contributed by [Nethermind](https://github.com/NethermindEth/nethermind) and [many others](#contributors).\n\n![Alt](https://repobeats.axiom.co/api/embed/0a001cc3c1f387fae08172a9e116b0ec367b8971.svg \"Repobeats analytics image\")\n\n# Overview\n\nComponents in Dstack:\n\n- `dstack-vmm`: A service running in bare TDX host to manage CVMs\n- `dstack-gateway`: A reverse proxy to forward TLS connections to CVMs\n- `dstack-kms`: A KMS server to generate keys for CVMs\n- `dstack-guest-agent`: A service running in CVM to serve containers' key derivation and attestation requests\n- `meta-dstack`: A Yocto meta layer to build CVM guest images\n\nThe overall architecture is shown below:\n![arch](./docs/assets/arch.png)\n\n# Directory structure\n\n```text\ndstack/\n    kms/                         A prototype KMS server\n    guest-agent/                 A service running in CVM to serve containers' key derivation and attestation requests.\n    dstack-util/                 A CLI tool in the guest setting up the system, getting TDX quote, extending RTMR, generating cert for RA-TLS, etc.\n    vmm/                         A service running in bare TDX host to manage CVMs\n    gateway/                     A reverse proxy to forward TLS connections to CVMs\n    certbot/                     A tool to automatically obtain and renew TLS certificates for dstack-gateway\n    ra-rpc/                      RA-TLS support for pRPC\n    ra-tls/                      RA-TLS support library\n    tdx-attest/                  Guest library for getting TDX quote and extending RTMR\n```\n\n# Build and play locally\n\n## Prerequisites\n\n- A bare metal TDX server setup following [canonical/tdx](https://github.com/canonical/tdx)\n- Public IPv4 address assigned to the machine\n- At least 16GB RAM, 100GB free disk space.\n- A domain with DNS access if you want to set up `dstack-gateway` for Zero Trust HTTPS\n\n> [!NOTE]\n>\n> This doc assumes you have access to a compatible Intel TDX Server ready to be configured with Dstack. Check the [Hardware Requirements](https://docs.phala.network/dstack/hardware-requirements) for more information on buying a bare metal server or renting a server from OVH. To start learning about Dstack check out the [docs](https://docs.phala.network/dstack/overview).\n>\n> If you are looking to deploy a CVM in minutes, go to the docs to learn how to [sign-up for a Phala Cloud Account](https://docs.phala.network/phala-cloud/getting-started/sign-up-for-cloud-account) and [deploy your first CVM on Dstack]((https://docs.phala.network/phala-cloud/getting-started/start-from-cloud-ui)).\n\n## Install dependencies\n\n```bash\n# for Ubuntu 24.04\nsudo apt install -y build-essential chrpath diffstat lz4 wireguard-tools xorriso\n# install rust\ncurl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh\n```\n\n## Build and run for local development\n\n### Build the artifacts\n```bash\ngit clone https://github.com/Dstack-TEE/meta-dstack.git --recursive\ncd meta-dstack/\n\nmkdir build\ncd build\n../build.sh hostcfg\n# This outputs the following message:\n# Config file ../build-config.sh created, please edit it to configure the build\n\nvim ./build-config.sh\n```\n\nReview and customize the `build-config.sh` configuration file according to your environment requirements. The file contains network ports, domain settings, and other important parameters. Once configured, run the build script again to generate the necessary artifacts:\n\n```bash\n../build.sh hostcfg\n\n# If everything is okay, you should see the built artifacts in the `build` directory.\n$ ls\ncerts  images  dstack-kms  kms.toml  run  dstack-vmm  vmm.toml  dstack-gateway  gateway.toml\n```\n\n### Download guest image or build guest image from source\n\n```bash\n# This will download the guest image from the release page.\n../build.sh dl 0.5.2\n```\n\nOr build guest image from source:\n\n```bash\n# This will build the guest image from source using the yocto meta layer. This will take a while.\n../build.sh guest\n```\n\n> **Note on Reproducible Builds**: The build command above does not guarantee reproducibility. For reproducible builds across different build environments, please refer to the [reproducible build instructions](https://github.com/Dstack-TEE/meta-dstack?tab=readme-ov-file#reproducible-build-the-guest-image) in the meta-dstack repository.\n\n### Run components\nNow you can open 3 terminals to start the components:\n\n1. Run `./dstack-kms -c kms.toml`\n2. Run `sudo ./dstack-gateway -c gateway.toml`\n3. Run `./dstack-vmm -c vmm.toml`\n\n⚠️ *Warning: this is for local development, and the kms is not secure, so you should not use it in production.*\nFor production, you should follow the [deployment guide](./docs/deployment.md) and read the [security guide](./docs/security-guide/security-guide.md).\n\n## Deploy an App\nOpen the dstack-vmm webpage [http://localhost:9080](http://localhost:9080)(change the port according to your configuration) on your local machine to deploy a `docker-compose.yaml` file:\n\n![vmm](./docs/assets/vmm.png)\n\nAfter the container deployed, it should need some time to start the CVM and the containers. Time would be vary depending on your workload.\n\n- Click the [Logs] button to see the logs of the CVM, you can see if the container is finished starting there.\n\n- Once the container is running, you can click the [Dashboard] button to see some information of the container. And the logs of the containers can be seen in the [Dashboard] page.\n\n    ![dstack-guest-agent](./docs/assets/guest-agent.png)\n\n- You can open dstack-gateway's dashboard at [https://localhost:9070](https://localhost:9070) to see the CVM's wireguard ip address, as shown below:\n\n![dstack-gateway](./docs/assets/gateway.png)\n\n## Pass Secrets to Apps\nWhen deploying a new App, you can pass private data via Encrypted Environment Variables. These variables can be referenced in the docker-compose.yaml file as shown below:\n\n![secret](./docs/assets/secret.png)\n\nThe environment variables will be encrypted in the client-side and decrypted in the CVM before being passed to the containers.\n\n## Access the App\n\nOnce the app is deployed and listening on an HTTP port, you can access the HTTP service via dstack-gateway's public domain. The ingress mapping rules are:\n\n- `<id>[s].<base_domain>` maps to port `80` or `443` if with `s` in the CVM.\n- `<id>-<port>[s].<base_domain>` maps to port `<port>` in the CVM.\n\nFor example, `3327603e03f5bd1f830812ca4a789277fc31f577-8080.app.kvin.wang` maps to port `8080` in the CVM.\n\nWhere the `<id>` can be either the app id or the instance id. If the app id is used, one of the instances will be selected by the load balancer.\nIf the `id-port` part ends with `s`, it means the TLS connection will be passthrough to the app rather than terminating at dstack-gateway.\n\nYou can also ssh into the CVM to inspect more information, if your deployment uses the image `dstack-x.x.x-dev`:\n\n```bash\n# The IP address of the CVM can be found in the dstack-gateway dashboard.\nssh [email protected]\n```\n\n## Getting TDX quote in docker container\n\nTo get a TDX quote within app containers:\n\n1. Mount `/var/run/dstack.sock` to the target container in `docker-compose.yaml`\n\n    ```yaml\n    version: '3'\n    services:\n    nginx:\n        image: nginx:latest\n        volumes:\n        - /var/run/dstack.sock:/var/run/dstack.sock\n        ports:\n        - \"8080:80\"\n        restart: always\n    ```\n\n2. Execute the quote request command in the container.\n\n    ```bash\n    # The argument report_data accepts binary data encoding in hex string.\n    # The actual report_data passing the to the underlying TDX driver is sha2_256(report_data).\n    curl --unix-socket /var/run/dstack.sock http://localhost/GetQuote?report_data=0x1234deadbeef | jq .  \n    ```\n\n## Container logs\n\nContainer logs can be obtained from the CVM's `dashboard` page or by curl:\n\n```bash\ncurl 'http://<appid>.app.kvin.wang:9090/logs/<container name>?since=0&until=0&follow=true&text=true&timestamps=true&bare=true'\n```\n\nReplace `<appid>` and `<container name>` with actual values. Available parameters:\n\n- since=0: Starting Unix timestamp for log retrieval\n- until=0: Ending Unix timestamp for log retrieval\n- follow: Enables continuous log streaming\n- text: Returns human-readable text instead of base64 encoding\n- timestamps: Adds timestamps to each log line\n- bare: Returns the raw log lines without json format\n\nThe response of the RPC looks like:\n```\n$ curl 'http://0.0.0.0:9190/logs/zk-provider-server?text&timestamps'\n{\"channel\":\"stdout\",\"message\":\"2024-09-29T03:05:45.209507046Z Initializing Rust backend...\\n\"}\n{\"channel\":\"stdout\",\"message\":\"2024-09-29T03:05:45.209543047Z Calling Rust function: init\\n\"}\n{\"channel\":\"stdout\",\"message\":\"2024-09-29T03:05:45.209544957Z [2024-09-29T03:05:44Z INFO  rust_prover] Initializing...\\n\"}\n{\"channel\":\"stdout\",\"message\":\"2024-09-29T03:05:45.209546381Z [2024-09-29T03:05:44Z INFO  rust_prover::groth16] Starting setup process\\n\"}\n```\n\n## TLS Passthrough with Custom Domain\n\ndstack-gateway supports TLS passthrough for custom domains.\n\nSee the example [here](https://github.com/Dstack-TEE/dstack-examples/tree/main/custom-domain/dstack-ingress) for more details.\n\n## Upgrade an App\n\nGot to the dstack-vmm webpage, click the [Upgrade] button, select or paste the compose file you want to upgrade to, and click the [Upgrade] button again.\nThe app id does not change after the upgrade. Stop and start the app to apply the upgrade.\n\n## HTTPS Certificate Transparency\n\nIn the tutorial above, we used a TLS certificate with a private key external to the TEE. To establish trust, we need to generate and maintain the certificate's private key within the TEE and provide evidence that all TLS certificates for the domain were originate solely from dstack-gateway CVM.\n\nBy combining Certificate Transparency Logs and CAA DNS records, we can make best effort to minimize security risks. Here's our approach:\n\n- Set CAA records to allow only the account created in dstack-gateway CVM to request Certificates.\n- Launch a program to monitor Certificate Transparency Log and give alarm once any certificate issued to a pubkey that isn’t generated by dstack-gateway CVM.\n\n### Configurations\n\nTo launch Certbot, you need to own a domain hosted on Cloudflare. Obtain an API token with DNS operation permissions from the Cloudflare dashboard. Configure it in the `build-config.sh`:\n\n```bash\n# The directory to store the auto obtained TLS certificate and key\nGATEWAY_CERT=${CERBOT_WORKDIR}/live/cert.pem\nGATEWAY_KEY=${CERBOT_WORKDIR}/live/key.pem\n\n# for certbot\nCF_ZONE_ID=cc0a40...\nCF_API_TOKEN=g-DwMH...\n# ACME_URL=https://acme-v02.api.letsencrypt.org/directory\nACME_URL=https://acme-staging-v02.api.letsencrypt.org/directory\n```\n\nThen re-run the ../build.sh:\n\n```bash\n../build.sh\n```\n\n### Launch certbot\n\nThen run the certbot in the `build/` and you will see the following log:\n```text\n$ RUST_LOG=info,certbot=debug ./certbot renew -c certbot.toml\n2024-10-25T07:41:00.682990Z  INFO certbot::bot: creating new ACME account\n2024-10-25T07:41:00.869246Z  INFO certbot::bot: created new ACME account: https://acme-staging-v02.api.letsencrypt.org/acme/acct/168601853\n2024-10-25T07:41:00.869270Z  INFO certbot::bot: setting CAA records\n2024-10-25T07:41:00.869276Z DEBUG certbot::acme_client: setting guard CAA records for app.kvin.wang\n2024-10-25T07:41:01.740767Z DEBUG certbot::acme_client: removing existing CAA record app.kvin.wang 0 issuewild \"letsencrypt.org;validationmethods=dns-01;accounturi=https://acme-staging-v02.api.letsencrypt.org/acme/acct/168578683\"\n2024-10-25T07:41:01.991298Z DEBUG certbot::acme_client: removing existing CAA record app.kvin.wang 0 issue \"letsencrypt.org;validationmethods=dns-01;accounturi=https://acme-staging-v02.api.letsencrypt.org/acme/acct/168578683\"\n2024-10-25T07:41:02.216751Z DEBUG certbot::acme_client: setting CAA records for app.kvin.wang, 0 issue \"letsencrypt.org;validationmethods=dns-01;accounturi=https://acme-staging-v02.api.letsencrypt.org/acme/acct/168601853\"\n2024-10-25T07:41:02.424217Z DEBUG certbot::acme_client: setting CAA records for app.kvin.wang, 0 issuewild \"letsencrypt.org;validationmethods=dns-01;accounturi=https://acme-staging-v02.api.letsencrypt.org/acme/acct/168601853\"\n2024-10-25T07:41:02.663824Z DEBUG certbot::acme_client: removing guard CAA records for app.kvin.wang\n2024-10-25T07:41:03.095564Z DEBUG certbot::acme_client: generating new cert key pair\n2024-10-25T07:41:03.095678Z DEBUG certbot::acme_client: requesting new certificates for *.app.kvin.wang\n2024-10-25T07:41:03.095699Z DEBUG certbot::acme_client: creating new order\n2024-10-25T07:41:03.250382Z DEBUG certbot::acme_client: order is pending, waiting for authorization\n2024-10-25T07:41:03.283600Z DEBUG certbot::acme_client: creating dns record for app.kvin.wang\n2024-10-25T07:41:04.027882Z DEBUG certbot::acme_client: challenge not found, waiting 500ms tries=2 domain=\"_acme-challenge.app.kvin.wang\"\n2024-10-25T07:41:04.600711Z DEBUG certbot::acme_client: challenge not found, waiting 1s tries=3 domain=\"_acme-challenge.app.kvin.wang\"\n2024-10-25T07:41:05.642300Z DEBUG certbot::acme_client: challenge not found, waiting 2s tries=4 domain=\"_acme-challenge.app.kvin.wang\"\n2024-10-25T07:41:07.715947Z DEBUG certbot::acme_client: challenge not found, waiting 4s tries=5 domain=\"_acme-challenge.app.kvin.wang\"\n2024-10-25T07:41:11.724831Z DEBUG certbot::acme_client: challenge not found, waiting 8s tries=6 domain=\"_acme-challenge.app.kvin.wang\"\n2024-10-25T07:41:19.815990Z DEBUG certbot::acme_client: challenge not found, waiting 16s tries=7 domain=\"_acme-challenge.app.kvin.wang\"\n2024-10-25T07:41:35.852790Z DEBUG certbot::acme_client: setting challenge ready for https://acme-staging-v02.api.letsencrypt.org/acme/chall-v3/14584884443/mQ-I2A\n2024-10-25T07:41:35.934425Z DEBUG certbot::acme_client: challenges are ready, waiting for order to be ready\n2024-10-25T07:41:37.972434Z DEBUG certbot::acme_client: order is ready, uploading csr\n2024-10-25T07:41:38.052901Z DEBUG certbot::acme_client: order is processing, waiting for challenge to be accepted\n2024-10-25T07:41:40.088190Z DEBUG certbot::acme_client: order is valid, getting certificate\n2024-10-25T07:41:40.125988Z DEBUG certbot::acme_client: removing dns record 6ab5724e8fa7e3e8f14e93333a98866a\n2024-10-25T07:41:40.377379Z DEBUG certbot::acme_client: stored new cert in /home/kvin/codes/meta-dstack/dstack/build/run/certbot/backup/2024-10-25T07:41:40.377174477Z\n2024-10-25T07:41:40.377472Z  INFO certbot::bot: checking if certificate needs to be renewed\n2024-10-25T07:41:40.377719Z DEBUG certbot::acme_client: will expire in Duration { seconds: 7772486, nanoseconds: 622281542 }\n2024-10-25T07:41:40.377752Z  INFO certbot::bot: certificate /home/kvin/codes/meta-dstack/dstack/build/run/certbot/live/cert.pem is up to date\n```\n\nWhere the command did are:\n\n- Registered to letsencrypt and got a new account `https://acme-staging-v02.api.letsencrypt.org/acme/acct/168601853`\n- Auto set CAA records for the domain on cloudflare, you can open the CF dashboard to see the record:\n\n    ![certbot-caa](./docs/assets/certbot-caa.png)\n\n- Auto requested a new certificate from Let's Encrypt. Automatically renews the certificate to maintain its validity\n\n### Launch dstack-gateway\n\nExecute dstack-gateway with `sudo ./dstack-gateway -c gateway.toml`, then access the web portal to check the dstack-gateway CVM managed Let's Encrypt account. The account's private key remains securely sealed within the TEE.\n\n![gateway-accountid](./docs/assets/gateway-accountid.png)\n\n## Certificate transparency log monitor\n\nTo enhance security, we've limited TLS certificate issuance to dstack-gateway via CAA records. However, since these records can be modified through Cloudflare's domain management, we need to implement global CA certificate monitoring to maintain security oversight.\n\n`ct_monitor` tracks Certificate Transparency logs via [https://crt.sh](https://crt.sh/?q=app.kvin.wang), comparing their public key with the ones got from dstack-gateway RPC. It immediately alerts when detecting unauthorized certificates not issued through dstack-gateway:\n\n```text\n$ ./ct_monitor -t https://localhost:9010/prpc -d app.kvin.wang\n2024-10-25T08:12:11.366463Z  INFO ct_monitor: monitoring app.kvin.wang...\n2024-10-25T08:12:11.366488Z  INFO ct_monitor: fetching known public keys from https://localhost:9010/prpc\n2024-10-25T08:12:11.566222Z  INFO ct_monitor: got 2 known public keys\n2024-10-25T08:12:13.142122Z  INFO ct_monitor: ✅ checked log id=14705660685\n2024-10-25T08:12:13.802573Z  INFO ct_monitor: ✅ checked log id=14705656674\n2024-10-25T08:12:14.494944Z ERROR ct_monitor: ❌ error in CTLog { id: 14666084839, issuer_ca_id: 295815, issuer_name: \"C=US, O=Let's Encrypt, CN=R11\", common_name: \"kvin.wang\", name_value: \"*.app.kvin.wang\", not_before: \"2024-09-24T02:23:15\", not_after: \"2024-12-23T02:23:14\", serial_number: \"03ae796f56a933c8ff7e32c7c0d662a253d4\", result_count: 1, entry_timestamp: \"2024-09-24T03:21:45.825\" }\n2024-10-25T08:12:14.494998Z ERROR ct_monitor: error: certificate has issued to unknown pubkey: 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\n```\n\n# Troubleshooting\n\n### Error from dstack-vmm: qemu-system-x86_64: -device vhost-vsock-pci,guest-cid=<id>: vhost-vsock: unable to set guest cid: Address already in use\n\n`dstack-vmm` may throw this error when creating a new VM if the [Unix Socket CID](https://man7.org/linux/man-pages/man7/vsock.7.html) is occupied. To solve the problem, first, you should list the occupied CID:\n\n```bash\nps aux | grep 'guest-cid='\n```\n\nThen choose a new range of the CID not conflicting with the CID in use. You can change `build/vmm.toml` file and restart `dstack-vmm`. This error should disappear. For example, you may find 33000-34000 free to use:\n\n```toml\n[cvm]\ncid_start = 33000\ncid_pool_size = 1000\n```\n\nWhen building the dstack from scratch, you should change the CID configs in `build-config.sh` instead, because `vmm.toml` file is generated by `build.sh`. Its content is derived from `build-config.sh`.\n\nYou may encounter this problem when upgrading from an older version of dstack, because CID was introduced in `build-config.sh` in later versions. In such case, please follow the docs to add the missing entries in `build-config.sh` and rebuild dstack.\n\n### Error: Operation not permitted when building guest image\n\nWhen running `../build.sh guest`, you might encounter this error:\n\n```\nTraceback (most recent call last):\n  File \"/meta-dstack/poky/bitbake/bin/bitbake-worker\", line 278, in child\n    bb.utils.disable_network(uid, gid)\n  File \"/meta-dstack/poky/bitbake/lib/bb/utils.py\", line 1696, in disable_network\n    with open(\"/proc/self/uid_map\", \"w\") as f:\nPermissionError: [Errno 1] Operation not permitted\n```\n\nThis error occurs because Ubuntu 23.10 and later versions restrict unprivileged user namespaces by default. To fix this, run:\n\n```bash\nsudo sysctl kernel.apparmor_restrict_unprivileged_userns=0\n```\n\nThen try building again. For more information about this restriction, see the [Ubuntu discourse post](https://discourse.ubuntu.com/t/spec-unprivileged-user-namespace-restrictions-via-apparmor-in-ubuntu-23-10/37626).\n\n\n# Contributors\n\nDstack is proudly built by open source and Pi-rateship contributors:\n\n- Phala Network: [Kevin Wang](https://github.com/kvinwang), [Shelven Zhou](https://github.com/shelvenzhou), [Leechael](https://github.com/leechael)\n- Teleport: [Andrew Miller](https://github.com/amiller), [Sxy Sun](https://github.com/sxysun)\n- Flashbots: [Tina](https://github.com/CarboClanC), [Mateusz](https://github.com/Ruteri), [Dmarz](https://github.com/dmarzzz), [Moe](https://github.com/MoeMahhouk)\n- Ithaca: [Georgios](https://github.com/gakonst)\n- Fabric: [@gaoist](https://x.com/gaoist)\n- And many more...\n\nThe inspiration for this work stems from [Andrew Miller](https://github.com/amiller)’s pioneering concept of a [Docker-based P2P TEE SDK](https://collective.flashbots.net/t/dstack-speedrunning-a-p2p-confidential-vm/3876).\n\nThis project cannot be built without standing on the shoulders of giants:\n\n- [konvera/meta-confidential-compute](https://github.com/konvera/meta-confidential-compute)\n\nSpecial acknowledgment to [Flashbots](https://github.com/flashbots) for building a community around TEE. The TEE Hacker House initiative, organized by [Flashbots](https://github.com/flashbots) and led by [Tina](https://github.com/CarboClanC), has brought together TEE builders to develop tools for TEE-Web3 integration. This collaborative journey has generated invaluable insights for advancing secure, confidential environments within Web3.\n\nTogether, we’re shaping the future of TEE in Web3, paving the way for more secure and developer-accessible confidential computing!\n\nFor a full list of the direct contributors to this repo, see [Contributors](https://github.com/Dstack-TEE/dstack/contributors) on GitHub.\n\n\n# License\n\nCopyright 2024 Phala Network and Contributors.\n\nLicensed under the Apache License, Version 2.0 (the \"License\"); you may not use this file except in compliance with the License. You may obtain a copy of the License at\n\n[http://www.apache.org/licenses/LICENSE-2.0](http://www.apache.org/licenses/LICENSE-2.0)"
      },
      {
        "type": "text",
        "text": "main.pdf\nDstack:  A Zero Trust Framework for Confidential Containers\nJune 23, 2025\nAbstract\nWeb3 applications require execution platforms that maintain confidentiality and integrity with-\nout relying on centralized trust authorities.  While Trusted Execution Environments (TEEs) offer\npromising capabilities for confidential computing, current implementations face significant limita-\ntions in security reliability, censorship resistance, and vendor independence when applied to Web3\ncontexts.  This paper presents Dstack, a comprehensive framework that transforms raw TEE tech-\nnology  into  a  true  Zero  Trust  platform  aligned  with  Web3  principles.   We  introduce  three  key\ninnovations:  (1) Portable Confidential Containers that enable seamless workload migration across\nheterogeneous TEE environments while maintaining security guarantees, (2) Decentralized Code\nManagement that leverages smart contracts for transparent governance of TEE applications, and\n(3) Verifiable Domain Management that ensures secure and verifiable application identity without\ncentralized authorities. Through these innovations, implemented via Dstack-OS, Dstack-KMS, and\nDstack-Gateway components, we demonstrate how to achieve both the performance advantages of\nVM-level TEE solutions and the trustless guarantees required by Web3 applications.  Our evalu-\nation shows that Dstack provides comprehensive security guarantees while maintaining practical\nusability for real-world applications.\n1    Introduction\nThe Web3 ecosystem represents a paradigm shift in digital trust models, fundamentally transforming\nthe relationship between users and application developers.  Unlike traditional systems, Web3 empowers\nusers with unprecedented control over their data through the principle of ”Code is Law” - once deployed,\ncode  operates  autonomously  and  independently  of  external  control.   This  transformation  demands\nrobust execution platforms that maintain confidentiality and integrity without relying on centralized\ntrust authorities.\nFigure 1:  The evolution of trust models from Web2 to Web3, highlighting the shift from centralized control\nto decentralized governance and execution.\nThe contrast between Web2 and Web3 architectures in Figure 1 illustrates this fundamental shift.\nIn Web2 systems, developers maintain complete control through proprietary applications and central-\nized servers, retaining administrative privileges to access and modify user data at will.  Web3’s smart\n1\ncontracts,  however,  represent  the  first  significant  step  toward  true  trustlessness  by  executing  pro-\ngrams on decentralized platforms (blockchains).  Once deployed, administrators cannot influence pro-\ngram execution, and lifecycle management (e.g., code updates) follows predefined agreements through\ndemocratic governance mechanisms like multi-signature wallets and Decentralized Autonomous Orga-\nnizations (DAOs).  This emerging trust model extends beyond basic applications to mission-critical\nscenarios such as AI model training, where data providers and model developers often have competing\ninterests,  and  autonomous  AI  agents  designed  to  operate  independently  of  human  intervention.   In\nthese  contexts,  Zero  Trust  platforms  become  essential  to  host  applications  and  enforce  verification\nmechanisms that appropriately constrain developer authority.\nA Zero Trust platform must enforce the following key principles:\n•  Code is Law: This manifests in two dimensions: (1) the application logic, once deployed, cannot\nbe  changed  unexpectedly;  and  (2)  the  lifecycle  management  of  code—including  deployment,\nupgrades, and deletion—follows predefined governance rules.\n•  Censorship Resistance:  User data remains beyond the control of any single entity, with data\navailability protected against Denial-of-Service attacks.\n•  Full Chain-of-Trust:  When users interact with applications on a Zero Trust platform,  they\nmust be able to verify all aspects of that application, including network setup, application identity\nand code logic, underlying hardware, and execution environment.\n•  Assume Breach:  The platform operates under the assumption that compromises will occur,\nimplementing  mechanisms  for  damage  containment,  rapid  recovery,  and  minimization  of  data\nexposure during security incidents.\nConfidential Computing, particularly through Trusted Execution Environments (TEEs), has emerged\nas a promising foundation for extending blockchain capabilities to support complex computational tasks\nwith confidentiality guarantees.  Recent advances in VM-level TEE solutions, including Intel TDX and\nAMD SEV, have demonstrated substantial performance improvements and developer-friendly inter-\nfaces,  making  them  compelling  candidates  for  Web3  deployment.   The  integration  of  GPUs  within\nTEEs [?] now enables verifiable execution of both Large Language Models and AI agents, providing\ncryptographic guarantees of computational integrity.\nHowever, a significant gap exists between raw TEE technology and the requirements of a true Zero\nTrust platform.  Current TEE implementations face several critical limitations when applied to Web3\ncontexts:\n•  Security Reliability:  Recent vulnerability discoveries in TEE systems have raised significant con-\ncerns  about  their  effectiveness  as  trust  anchors.   The  persistence  of  side-channel  attacks  and\nmicro-architectural vulnerabilities undermines confidence in TEE security guarantees, particu-\nlarly for high-value Web3 applications where a single compromise could lead to catastrophic data\nexposure.\n•  Censorship Vulnerability:  Conventional TEE encryption schemes bind encryption keys to spe-\ncific  hardware  instances,  creating  single  points  of  failure  that  contradict  Web3’s  requirement\nfor censorship resistance.  This architectural limitation means that data availability cannot be\nguaranteed if specific hardware instances are compromised or become unavailable.\n•  Vendor Dependencies:  Current trust models heavily rely on centralized hardware manufacturers\nand verification processes, introducing risks of vendor lock-in and potential censorship vectors.\nThis centralization contradicts Web3’s core principles of decentralization and trustlessness.\n•  Incomplete Verifiability:  While TEEs provide Remote Attestation capabilities to verify applica-\ntion and hardware identity, they fail to deliver the comprehensive chain of trust required in Zero\nTrust environments.  Users need guarantees that programs will process their data as expected\nand cannot be modified without proper authorization—capabilities beyond current attestation\nmechanisms.\nTo bridge this gap between raw TEE technology and Zero Trust requirements, we present Dstack,\na comprehensive framework for confidential containers that introduces three key innovations:\n2\n•  Portable Confidential Container: Our architecture enables seamless migration of confidential\nworkloads across different TEE instances and hardware vendors,  significantly reducing vendor\nlock-in risks while maintaining robust security guarantees.  This innovation directly addresses the\ncensorship vulnerability and vendor dependency limitations by providing hardware abstraction\nand state continuity across heterogeneous TEE environments.\n•  Decentralized Code Management:  We implement a comprehensive governance framework\nthat leverages smart contracts for transparent and decentralized management of TEE applica-\ntions.  This  system ensures verifiable deployment  and upgrade processes,  enforcing the  “Code\nis Law” principle by binding application lifecycles to on-chain governance decisions.  This inno-\nvation addresses the incomplete verifiability limitation by creating an immutable audit trail of\napplication changes.\n•  Verifiable Domain Management: Our novel approach to certificate management ensures that\nconfidential containers can exclusively control domains and provide native HTTPS support to\nTEE applications without relying on centralized authorities.  This system serves as a middleware\nbetween TEE applications and existing TLS-based networks, enabling users to establish end-to-\nend encrypted channels to TEE applications without modifications to client software.\nThese innovations are implemented through a cohesive system architecture comprising three core\ncomponents:\n•  Dstack-OS: A hardware abstraction layer with a minimized operating system image that elimi-\nnates differences in underlying TEE hardware while reducing the attack surface.  This component\nprovides a consistent, secure runtime environment across diverse TEE implementations.\n•  Dstack-KMS:  A  blockchain-controlled  key  management  service  that  replaces  hardware-based\nencryption schemas with an independent service for generating and managing secret keys.  This\ncomponent  enables  secure  data  migration  across  TEE  instances  and  supports  key  rotation  to\nprovide forward and backward data secrecy, mitigating the impact of potential TEE compromises.\n•  Dstack-Ingress and Dstack-Gateway: Complementary systems providing TEE-controlled domain\nmanagement through different approaches—Dstack-Ingress enables applications to specify cus-\ntom domains with minimal integration requirements, while Dstack-Gateway offers pre-registered\nwildcard domains requiring no application code changes.\nBy addressing the critical limitations of current TEE implementations, Dstack establishes a compre-\nhensive framework that transforms raw TEE technology into a true Zero Trust platform aligned with\nWeb3’s fundamental principles.  Our approach not only enhances the security and reliability of confi-\ndential computing but also provides a practical path toward truly decentralized, censorship-resistant\ninfrastructure for next-generation applications.\nThe remainder of this paper details the technical design of Dstack, evaluates its performance and\nsecurity characteristics, and demonstrates how our innovations collectively create a Zero Trust platform\nthat maintains the performance advantages of VM-level TEE solutions while addressing their inherent\nlimitations in Web3 contexts.\n2    System Design\n2.1    Portable Confidential Container\nContainerization has transformed cloud-native application deployment by providing unparalleled porta-\nbility and scalability through effective data separation.  These capabilities are particularly critical for\nTrusted Execution Environment (TEE) applications, as they directly address the inherent limitations\noutlined in Section 1:\n•  Security Reliability:  Containerized applications can be efficiently transferred from compro-\nmised TEE hardware to secure instances,  preserving code integrity.  Together with our secure\ndata migration mechanism that ensures both forward and backward secrecy, this approach sig-\nnificantly limits privacy leakage risks even when individual TEE instances are compromised.\n3\nFigure 2:  The architecture of Dstack, including Dstack-OS and Dstack-KMS. Dstack-OS provides a hardware\nabstraction layer with a minimized operating system image, while Dstack-KMS replaces the hardware-based\ndata encryption keys with a blockchain-controlled key management service.  TODO: redraw this to put the\ncomponents into solutions.\n•  Censorship Resistance: The architecture’s inherent scalability provides robust defense against\nDenial-of-Service attacks. Additionally, by decoupling data storage from execution environments,\nestablished  data  availability  solutions  can  be  readily  integrated  to  ensure  persistent  access  to\napplication data.\n•  Vendor  Independence:   Our  hardware  abstraction  layer  enables  confidential  containers  to\noperate across diverse TEE hardware platforms without modification, eliminating vendor lock-in\nwhile facilitating rapid adoption of emerging TEE technologies as they become available.\nHowever, implementing truly portable confidential containers presents substantial technical chal-\nlenges that differentiate them from conventional containerization.  Two fundamental obstacles must be\novercome:\nFirst, existing TEE implementations generate data sealing keys derived from hardware-bound root\nkeys unique to each TEE instance.  This architectural design creates an inherent barrier to portability\n— data encrypted by one TEE instance cannot be decrypted by any other, even when running identical\napplication code.  Prior research has largely circumvented this limitation by restricting TEEs to state-\nless applications, but this approach severely constrains their utility in complex real-world scenarios.\nSecond,  TEE implementations from different vendors impose disparate specifications for deploy-\nable programs.  This fragmentation forces developers to create and maintain multiple artifacts across\nplatforms, each requiring separate (and expensive) code reviews to verify functional equivalence — a\nprocess that undermines the trust guarantees central to Web3 applications.\nTo address these challenges comprehensively, we introduce two complementary components: Dstack-\nKMS and Dstack-OS.\n2.1.1    Dstack-KMS: Blockchain-Controlled Secret Derivation\nDstack-KMS  is  a  secret  derivation  service  that  fundamentally  transforms  how  encryption  keys  are\nmanaged in confidential computing environments.  Its primary function is to generate a unique and\nstable secret (the Root Key ) for each application based on its code and configurations.  This root key\n4\nserves as the foundation for deriving additional application-specific secrets used for data encryption\nand verifiable random number generation.\nUnlike hardware-based encryption approaches, Dstack-KMS deliberately decouples key generation\nfrom specific TEE hardware instances.  This architectural decision enables the critical capability of\nencrypted  data  migration  between  different  TEE  instances,  with  decryption  possible  after\nproper authorization.  This feature is essential for achieving true censorship resistance.\nGiven  its  position  as  the  root-of-trust  for  the  entire  system,  the  verifiability  and  availability  of\nDstack-KMS are paramount.  Unlike previous approaches [?] that assume TEE infallibility, our threat\nmodel explicitly acknowledges that TEEs can be compromised.  To address this reality, Dstack-\nKMS  implements  comprehensive  key  rotation  capabilities  that  provide  both  backward  and  forward\nsecrecy for application data. This ensures that even if a specific TEE hardware instance is compromised,\napplications can be migrated with limited data exposure.\nFigure 3:  The key derivation hierarchy of Intel SGX illustrates how conventional TEE implementations bind\nencryption keys to hardware.\nTo understand the limitations of conventional approaches, Figure 3 illustrates the key derivation\nhierarchy in Intel SGX. This design uses a hardware-bound key to both identify the TEE instance (for\nRemote Attestation) and generate encryption keys for data sealing.  While this approach effectively\nestablishes hardware identity, it fundamentally undermines censorship resistance:\n•  The root key cannot be updated, meaning a compromised TEE with a leaked root key remains\npermanently vulnerable even after patching the underlying vulnerability.\n•  Encrypted data becomes intrinsically bound to specific TEE hardware instances, creating single\npoints of failure that contradict Web3’s censorship resistance requirements.\nOur  Dstack-KMS  addresses  these  limitations  by  delegating  secret  generation  to  an  independent\nservice that ensures encrypted data remains portable across TEE instances.\nAs illustrated in Figure 4, Dstack-KMS comprises an on-chain governance smart contract coupled\nwith an off-chain peer-to-peer network where the actual secret derivation service operates.  To ensure\ncomprehensive verifiability of the Dstack-KMS program’s integrity and correctness, we implement a\nmulti-stage verification process:\n1.  The Dstack-KMS codebase is fully open-sourced [?], enabling thorough code and security reviews\nto verify key management logic and ensure the absence of backdoors.\n5\nFigure 4:  The architecture of Dstack-KMS combines on-chain governance through smart contracts with an\noff-chain P2P network of secret derivation service nodes.  This design ensures both verifiability and resilience\nagainst compromise.\n2.  Executable  binaries  are  produced  through  reproducible  build  processes,  allowing  verifiers  to\nconfirm that the runtime code matches the reviewed source code.\n3.  The cryptographic digest of valid executables is published through the governance smart contract,\ncreating an immutable reference for verification.\n4.  Each service node operates within its own TEE instance.  Critically, we rely on the TEE solely for\nmeasuring the executable and ensuring it matches the on-chain digest—not for the fundamental\nsecurity of the key management process.\nThis verification framework ensures that Dstack-KMS remains trustworthy to any third-party verifier\nwhile avoiding dependency on the absolute security of any single TEE instance.\nThe core logic of each Dstack-KMS service node is intentionally minimalist, focusing exclusively on\nthe generation and secure distribution of the root key, along with deriving encryption keys for TEE\napplications.  This simplicity enables the implementation of Multi-Party Computation (MPC) based\nthreshold key generation and derivation without concerning performance overhead.  We have developed\ntwo complementary implementations:\n•  Simple Duplication:  The first node in the P2P network generates a cryptographically secure\nrandom number as the root key, then shares it with other nodes after verifying their attestation\nreports.  All nodes maintain identical copies of the root key and derive consistent encryption keys\nfor  applications.   This  approach  maximizes  availability—as  long  as  at  least  one  node  remains\noperational, the root key can be recovered.\n•  MPC-Based Key Generation:  While simple duplication provides robust availability, it cre-\nates vulnerability to single-node compromises.  Our MPC implementation uses Shamir’s Secret\nSharing scheme [?] to distribute the root key across multiple nodes, ensuring that compromising\nany individual node (or even up tot− 1 nodes, wheret is the configured threshold) does not\nexpose  the  root  key.   This  approach  also  enables  advanced  features  like  key  rotation  without\nrequiring application reconfiguration.\nKey Derivation    Dstack-KMS implements a comprehensive key derivation framework to generate\napplication-specific keys from the root key:\n•  Application CA Key:  Derived from the root CA key using the application’s unique identifier\n(calculated as the hash of the application’s code and configuration).\n•  Disk Encryption Key:  Derived using a combination of the application identifier and instance\nidentifier, enabling secure storage with portability.\n6\n•  Environment Encryption Key: Derived using the application identifier alone, allowing secure\nenvironment variable management across instances.\n•  ECDSA Key:  Derived from the root ECDSA key, providing applications with consistent cryp-\ntographic identity for signing operations.\nEach derived key maintains cryptographic isolation while ensuring consistency across different TEE\ninstances running the same application.\nKey Rotation    A critical security feature of Dstack-KMS is its support for key rotation, which signif-\nicantly limits the exposure window during potential attacks while ensuring both forward and backward\nsecrecy for sealed data.  Key rotation procedures are initiated exclusively through the governance smart\ncontract, ensuring transparency and auditability.  We discuss two distinct rotation mechanisms:\n•  Root Key Share Rotation:  Our MPC-based implementation enables rotation of individual\nkey  shares  without  modifying  the  root  key  itself.   This  process  enhances  root  key  security  by\nregularly updating the distribution mechanism while remaining transparent to applications, as\nall derived application keys remain unchanged.\n•  Root Key Rotation:  In scenarios where the root key may have been compromised, we support\ncomplete root key rotation.  This process generates an entirely new root key and implements a\ncontrolled handover period during which both old and new keys remain valid.  This transition\nwindow  allows  applications  to  re-encrypt  their  data  with  keys  derived  from  the  new  root  key\nbefore the old root key is permanently destroyed, minimizing service disruption while enhancing\nsecurity.\nThrough these mechanisms, Dstack-KMS provides the foundation for truly portable confidential con-\ntainers by decoupling encryption from hardware dependencies while maintaining robust security guar-\nantees.\n2.1.2    Dstack-OS: Hardware Abstraction Layer\nDstack-OS provides a comprehensive hardware abstraction layer with a minimized operating system\nimage that bridges the gap between application containers and VM-level TEE implementations.  This\nlayer enables applications to deploy across diverse TEE environments without code modifications while\nmaintaining security integrity.  As a shared component across all TEE applications, Dstack-OS must be\nintrinsically secure and verifiable, with no administrative backdoors that could compromise program\ncode or user data.\nVM-level  TEE  solutions  typically  require  developers  to  provide  complete  system  images  encom-\npassing  bootloader,  kernel,  operating  system,  and  application  components.   This  requirement  not\nonly increases development complexity but also introduces potential security vulnerabilities through\nmisconfigured system components.  A secure and properly configured operating system environment\nfundamentally determines the security baseline for all TEE applications built upon it.\nFigure 5 illustrates how Dstack-OS establishes a secure and verifiable startup chain from the TEE\nhardware foundation through to user-provided container images.  Our modular design ensures that the\nmajority of the system can be reused across different TEE hardware implementations, substantially\nreducing the effort required for code review and security auditing.  Combined with reproducible build\nprocesses, this approach enables comprehensive verification of Dstack-OS with minimal overhead while\nsupporting multiple TEE hardware platforms.\nUsing Intel TDX as an exemplar (with similar procedures applicable to other TEE implementa-\ntions like AMD SEV), Dstack-OS consists of the following components,  presented in boot sequence\norder.  During this process, each component measures the next one and records these measurements\nin hardware registers, which are ultimately incorporated into the TEE attestation report:\n•  Hypervisor: When application deployment initiates, the underlying hypervisor (the TDX mod-\nule) loads the Open Virtual Machine Firmware (OVMF), enabling UEFI support for confidential\nvirtual  machines.   The  TDX  module  measures  the  OVMF  code  and  records  its  cryptographic\ndigest in the MRTD register, with the hypervisor’s integrity guaranteed by the TEE hardware\nitself.\n7\nFigure 5:  The architecture of Dstack-OS establishes a secure and verifiable startup chain from TEE hardware\nthrough to user applications.\n•  Open Virtual Machine Firmware (OVMF): The OVMF configures virtual machine hard-\nware  specifications  (CPU,  memory,  and  device  configurations)  and  records  the  configuration\nmeasurement  to  the  RTMR0  register.   It  then  loads  the  Linux  kernel  and  records  the  kernel\nimage measurement to the RTMR1 register.\n•  Kernel:  The kernel first loads an initial ramdisk (initrd) — a temporary in-memory filesystem\ncontaining  minimal  command-line  tools  and  disk  encryption  libraries.   The  initrd  mounts  the\nroot filesystem and records this measurement in the RTMR2 register.\n•  Root Filesystem: The root filesystem (RootFs) is a read-only environment containing essential\nsystem libraries and tools.  It manages the entire lifecycle of deployed applications, measuring\napplication images along with their associated key management system and storing these mea-\nsurements  in  the  RTMR3  register.   The  RootFs  serves  two  primary  functions:  (1)  providing\nthe runtime environment for user-level container images, and (2) managing application data en-\ncryption.   It  interfaces  with  Dstack-KMS  to  acquire  encryption  secrets  and  implements  Linux\nUnified Key Setup (LUKS) to encrypt application data in isolated volumes.  Data integrity is\nensured through dm-verity, a Merkle-tree-based block-level verification tool.  Finally, the RootFs\nconfigures network ingress for the application and initiates execution.\nRather than adapting existing system images, we built Dstack-OS from scratch to ensure only es-\nsential components are included in both the initrd and RootFs.  A comprehensive component inventory\nis provided in Appendix ?? for transparency and review.  Generally,  Dstack-OS includes only basic\nutilities (busybox), filesystem support, and container runtime components.  By implementing Docker\nsupport  while  delegating  orchestration  to  the  application  level,  we  maintain  a  minimal  base  image\nfootprint.\nTo ensure comprehensive verifiability, Dstack-OS is fully open-sourced and supports reproducible\nbuilds,  allowing  anyone  to  review  the  code  and  generate  identical  artifacts  for  verification.   This\napproach provides significant benefits for applications requiring security reviews,  as evaluators need\nonly review the application code rather than the entire system image.\nData Backup and Defense against Rollback Attacks    A critical challenge in confidential com-\nputing is ensuring data durability and integrity, particularly against rollback attacks where adversaries\nattempt to revert applications to previous states to bypass security checks or reuse expired secrets.\nOur architecture provides robust secure data backup support and implements robust anti-rollback\nmechanisms that application developers can integrate:\n•  Secure Backup:  Application data is encrypted using keys derived from Dstack-KMS and can\nbe backed up to external storage providers.  Since encryption keys are not bound to specific TEE\n8\ninstances, data can be restored on any authorized TEE, supporting true portability and disaster\nrecovery.\n•  Monotonic Counters: To prevent rollback attacks, developers can implement monotonic coun-\nters that increment with each critical data update, incorporating the counter value into the en-\ncrypted data.  During restoration, applications verify that the counter value equals or exceeds\nthe last known value, preventing replay of outdated snapshots.\nBy combining these techniques,  Dstack ensures both the recoverability and integrity of confidential\ndata across portable container migrations and backup scenarios.\nTogether, Dstack-KMS and Dstack-OS provide the foundational infrastructure for truly portable\nconfidential containers that maintain security and integrity across heterogeneous TEE environments\nwhile eliminating vendor lock-in and supporting comprehensive verifiability.\n2.2    Decentralized Code Management\nA core principle of Zero Trust platforms is the enforcement of “Code is Law”, ensuring that application\ncode  operates  as  intended  without  unexpected  modifications.   While  TEE  hardware  provides  code\nintegrity guarantees during execution, it cannot independently prevent administrators from deploying\nmalicious code or making unauthorized modifications.  Conversely, smart contracts have established\nrobust methodologies for implementing programmable governance over code lifecycle management —\nsuch as multi-signature requirements that prevent single-actor manipulation.\nOur  decentralized  code  management  framework  bridges  these  two  worlds  by  placing  TEE  ap-\nplication governance under smart contract control,  creating a transparent and auditable system for\napplication deployment and updates that aligns with Web3 principles.\nFigure 6:  The architecture of decentralized code management integrates on-chain governance contracts with\noff-chain TEE through Dstack-KMS.\nAs illustrated in Figure 6, our architecture consists of two complementary components:  on-chain\ngovernance  smart  contracts  and  off-chain  TEE  execution  environments  connected  through  Dstack-\nKMS. This design establishes the on-chain contracts as the definitive root-of-trust for the entire system.\nEvery operation — from initial deployment to code upgrades — must first be initiated and authorized\nthrough the governance contracts before off-chain TEE instances can execute these operations.\nThe governance framework implements a two-tier structure:\n•  KmsAuth Contract:  Serves as the global authority controlling Dstack-KMS operations.  This\ncontract maintains the registry of authorized applications and their governance parameters, en-\nforcing system-wide policies for TEE deployment.  By controlling whether Dstack-KMS shares\n9\napplication  secrets  with  specific  TEE  instances,  the  KmsAuth  contract  effectively  determines\nwhether applications can decrypt their data, thus controlling their complete lifecycle.\n•  AppAuth Contracts:  Individual governance contracts deployed for each application that de-\nfine  application-specific  management  rules.   These  contracts  specify  permissible  code  versions\n(through cryptographic hashes), authorized TEE instance identities, and upgrade approval re-\nquirements.  This modular approach enables customized governance models ranging from tradi-\ntional multi-signature schemes to complex DAO voting mechanisms, allowing each application\nto implement governance appropriate to its requirements.\nThe enforcement mechanism operates through Dstack-KMS, which will only provide application\nsecrets  to  TEE  instances  running  code  versions  explicitly  authorized  by  the  governance  contracts.\nThis creates a cryptographically enforced governance system where unauthorized code versions cannot\naccess application data, regardless of administrative privileges.\nTo  illustrate  this  mechanism,  consider  a  code  upgrade  process  for  an  application  using  a  multi-\nsignature AppAuth contract in Figure 6:\n1.  Developers  publish  the  new  code  version  and  submit  its  cryptographic  hash  to  the  AppAuth\ncontract.\n2.  The  contract  initiates  the  approval  process,  requiring  signatures  from  designated  key  holders\n(e.g., core developers, security auditors, and community representatives).\n3.  Each signature is recorded on-chain, creating an immutable audit trail of the approval process.\n4.  Once the required signature threshold is reached, the AppAuth contract updates its registry of\nauthorized code versions.\n5.  The  KmsAuth  contract,  monitoring  the  AppAuth  contract,  updates  its  authorization  records\naccordingly.\n6.  Dstack-KMS,  which  continuously  synchronizes  with  the  KmsAuth  contract,  begins  providing\napplication secrets to TEE instances running the newly approved code version.\n7.  TEE instances can now deploy the new code with full access to encrypted application data.\nThis process ensures that every code change follows predefined governance rules with complete trans-\nparency.  The on-chain approval records create an immutable audit trail that allows users to verify\nthe entire history of application changes, while the cryptographic enforcement through Dstack-KMS\nguarantees that only properly authorized code can access application data.\nBy combining the code integrity guarantees of TEEs with the transparent governance capabilities\nof  smart  contracts,  our  decentralized  code  management  framework  ensures  that  applications  truly\nembody the ”Code is Law” principle. Every aspect of the application lifecycle—from initial deployment\nto  version  updates  and  potential  retirement—follows  predefined,  transparent  rules  that  cannot  be\ncircumvented by any single entity, including the platform operators themselves.\n2.3    Verifiable Domain Management\nA  complete  Zero  Trust  platform  must  enable  seamless  verification  for  users  across  both  Web3  and\ntraditional  Web2  environments.   Our  Verifiable  Domain  Management  system  completes  the  chain-\nof-trust  by  allowing  standard  Web  browsers  to  cryptographically  verify  TEE  applications  without\nrequiring any client-side modifications or specialized knowledge.\nThis  capability  is  critical  for  mainstream  adoption,  as  it  allows  users  to  interact  with  confiden-\ntial applications using familiar tools while maintaining the same security guarantees provided by the\nunderlying TEE infrastructure.  We implement this through two complementary components—Dstack-\nIngress and Dstack-Gateway—both leveraging our novel Zero Trust TLS (ZT-TLS) protocol.\nThe  fundamental  innovation  in  ZT-TLS  is  establishing  cryptographic  proof  that  a  specific  TLS\ncertificate  (and  therefore  a  domain)  is  exclusively  controlled  by  a  verified  TEE  application.   This\ncreates a verification chain extending from the blockchain to standard HTTPS connections, enabling\nusers to confirm application authenticity through familiar security indicators in their browsers.\n10\nFigure  7:   The  Zero  Trust  TLS  architecture  establishes  a  cryptographically  verifiable  connection  between\nstandard web browsers and TEE applications through blockchain-anchored certificate management.\n2.3.1    Zero Trust TLS Protocol\nThe  ZT-TLS  protocol  addresses  a  critical  challenge:  how  to  cryptographically  bind  a  domain  to  a\nspecific TEE application in a way that prevents unauthorized certificate issuance or domain hijacking.\nOur solution integrates three key components:\n•  TEE-Generated Certificates:  The TEE application (specifically Dstack-Gateway) generates\nits TLS certificate using application secrets derived from Dstack-KMS. This ensures the private\nkey  never  exists  outside  the  TEE  environment  and  creates  a  cryptographic  link  between  the\non-chain governance and the TLS certificate.\n•  Certificate  Authority  Authorization  (CAA):  We  leverage  DNS  CAA  records  to  restrict\nwhich  certificate authorities can  issue certificates  for managed  domains.  By  configuring CAA\nrecords  to  only  authorize  certificates  from  specific  issuers  (which  verify  TEE  attestation),  we\nprevent unauthorized certificate issuance through alternative validation methods.\n•  Certificate Transparency (CT) Monitoring:  To protect against unauthorized DNS record\nmodifications, we implement continuous monitoring of Certificate Transparency logs.  This allows\ndetection of any unauthorized certificates and provides an immutable audit trail of certificate\nissuance history.\n2.3.2    Implementation Components\nWe provide two complementary implementations to accommodate different application requirements:\n•  Dstack-Gateway:  A fully managed reverse proxy running within a TEE that provides imme-\ndiate domain verification with zero application code changes.  Applications register with Dstack-\nGateway through a simple API call, during which Dstack-Gateway verifies the application’s re-\nmote attestation report.  Once verified, applications receive a subdomain under a pre-registered\nwildcard domain (e.g., app-id.Dstack.com), with all TLS termination and certificate manage-\nment handled automatically.\n•  Dstack-Ingress:   A  more  flexible  solution  for  applications  requiring  custom  domain  names.\nDstack-Ingress provides libraries and services that enable applications to manage their own TLS\ncertificates while maintaining the same verification guarantees.  This approach requires minimal\nintegration work while supporting application-specific domain requirements.\n11\nBoth implementations ensure that certificates are cryptographically bound to verified TEE environ-\nments, with the verification chain extending from the blockchain governance contracts through to the\nTLS certificates presented to users’ browsers.\n2.3.3    Security Guarantees and Protections\nOur Verifiable Domain Management system provides several critical security guarantees:\n•  Certificate Provenance Verification:  Users can verify that the TLS certificate presented by\nan application was issued to a legitimate TEE environment by checking the certificate against\non-chain records.\n•  Domain Binding Integrity:  The combination of CAA records and Certificate Transparency\nmonitoring ensures that domains remain bound to their designated TEE applications, preventing\nunauthorized certificate issuance.\n•  Tamper-Evident Certificate Changes:  Any unauthorized attempts to modify domain con-\nfigurations or issue alternative certificates are detected through Certificate Transparency moni-\ntoring, with alerts propagated to clients.\nWhile we cannot technically prevent all attacks against centralized DNS infrastructure, our multi-\nlayered approach creates a tamper-evident system where unauthorized changes are quickly detected\nand rejected by client verification processes.  This approach aligns with the ”Assume Breach” principle\nby implementing defense-in-depth strategies that maintain security even when individual components\nare compromised.\nBy extending the verification chain from blockchain governance through TEE attestation to stan-\ndard TLS certificates, our Verifiable Domain Management system enables seamless integration of Zero\nTrust  applications  into  existing  web  infrastructure.   This  creates  a  practical  path  for  mainstream\nadoption without requiring specialized knowledge or tools from end users, while maintaining the com-\nprehensive security guarantees that define true Zero Trust platforms.\n3    Verifying TEE Applications:  A Practical Walkthrough\nTo demonstrate how Dstack fulfills the Zero Trust principles and addresses the challenges outlined in\nSection 1,  we present a practical end-to-end verification scenario.  This walkthrough illustrates how\nthe architectural components described in Section 2 work together to provide a comprehensive chain\nof trust for real-world Web3 applications.\nTraditional  Zero  Trust  programs  like  smart  contracts  achieve  verifiability  through  transparent\nsource  code  and  inputs.   However,  extending  similar  verifiability  to  real-world  applications  presents\nunique  challenges,  particularly  in  maintaining  privacy  and  compatibility  with  existing  development\npractices.   Dstack  addresses  these  challenges  through  a  comprehensive  verification  framework  that\nrequires minimal code changes.\nThis section demonstrates Dstack’s complete chain of trust through a practical example:  verifying\nthat  a  cryptographic  key  was  genuinely  generated  within  a  TEE  environment.   This  scenario  is  es-\npecially relevant for Web3 and AI Agent applications where cryptographic keys establish application\nidentity and authority.\n3.1    Threat Model\nOur verification framework assumes the correct implementation and integrity of core Dstack compo-\nnents (Dstack-OS, Dstack-KMS, Dstack-Gateway, and governance contracts). While these components’\nsecurity guarantees are detailed in later sections, we explicitly consider developers and administrators\nas potential adversaries.\nPotential attack vectors include:\n•  Application-Level Attacks\n–  Deployment of unauthorized or malicious code through falsified Docker images\n12\n–  Introduction of malicious dependencies through supply chain attacks\n–  Unauthorized application updates that bypass governance controls\n•  Infrastructure-Level Attacks\n–  Tampering with Dstack-OS to circumvent security controls\n–  Deployment of compromised key management services\n–  Operation of unpatched or vulnerable TEE firmware\n–  Execution of applications on non-TEE hardware with spoofed attestation\n•  Network-Level Attacks\n–  DNS hijacking to redirect traffic to unauthorized applications\n–  Man-in-the-middle attacks on communication channels\nDirect attacks on TEE hardware security (e.g., exploitation of hardware vulnerabilities) are con-\nsidered out of scope for this discussion and addressed separately.\n3.2    The Reproducibility Challenge\nA  fundamental  challenge  in  TEE  attestation  lies  in  bridging  the  gap  between  source  code  and  the\nactual  artifacts  (binaries  or  container  images)  running  inside  enclaves.   While  TEE  attestation  can\nprove that a specific artifact runs within a secure environment, it cannot independently verify that the\nartifact accurately represents its claimed source code.\nThis limitation creates several security risks:\n•  Source Code Manipulation:  Developers could intentionally deploy artifacts that differ from\npublicly reviewed source code\n•  Build Process Compromise:  Supply chain attacks could inject malicious code during artifact\ncreation\n•  Toolchain  Vulnerabilities:   As  demonstrated  by  the  Ken  Thompson  Hack,  even  compiler\ntoolchains could be compromised to inject malicious behavior\nTEE  quotes  only  attest  to  measurements  (cryptographic  hashes)  of  running  artifacts.   Without\nguarantees that these artifacts accurately represent reviewed source code, users cannot fully trust ap-\nplications even when running in secure enclaves.  This challenge affects all TEE applications, including\nDstack’s core components.\nFigure 8:  Comprehensive verification chain from source code to running TEE applications\nEstablishing a complete verification chain requires three key elements:\n13\n•  Source Code Verification:  Open-source code or trusted third-party review ensuring no back-\ndoors exist\n•  Build Process Integrity:  Reproducible builds allowing independent verification of artifacts\n•  Runtime Attestation:  TEE quotes proving that verified artifacts are actually running\nTraditional reproducible builds, while ideal, often introduce significant complexity through special-\nized  toolchains  and  build  scripts.   The  following  section  introduces  an  alternative  approach, In-CC\nBuild, that achieves similar guarantees with improved practicality.\n3.3    Dstack Component Verifiability\nEach  core  Dstack  component  implements  specific  verifiability  mechanisms  anchored  in  transparent,\nimmutable records.  Table 1 summarizes these mechanisms:\nComponentSourceBuild MethodRegistryVerification\nDstack-OSOpenReproducibleKmsAuthOS Digest\nDstack-KMSOpenIn-CCKmsAuthImage Hash, Root PubKey\nDstack-GatewayOpenIn-CCAppAuthImage Hash\nTable 1:  Verifiability mechanisms and trust anchors for Dstack components\nAll components maintain open-source codebases with comprehensive documentation. Dstack-OS, as\nthe foundational component, undergoes third-party security audits and implements fully reproducible\nbuilds.\nThe governance smart contracts serve as authoritative registries, anchoring each component’s trust\nbase:\n•  Dstack-OS digests are registered in KmsAuth and managed through multi-signature governance\n•  Dstack-KMS measurements and root public keys are recorded in KmsAuth\n•  Dstack-Gateway artifacts are verified through dedicated AppAuth contracts\nIn-ConfidentialContainer Build    While reproducible builds represent the gold standard for arti-\nfact verification, they often prove impractical for complex applications.  Dstack addresses this through\nIn-CC Build,  leveraging  the  verified  Dstack-OS  as  a  trusted  foundation.   The  In-CC  Build  process\nexecutes entirely within Dstack-OS environment, encompassing code fetching, compilation, and arti-\nfact creation.  By specifying precise source references (e.g., a snapshot of the codebase), the system\nproduces verifiable artifacts with measurements attested in TEE quotes.  This approach minimizes the\ntrusted computing base while eliminating the complexity of traditional reproducible builds.\n3.4    End-to-End Verification Walkthrough\nFrom a user’s perspective, verifying a TEE application in Dstack requires validating a chain of mea-\nsurements against authoritative registries,  encompassing the user application,  runtime data,  Dstack\ncomponents, and network infrastructure.  This section walks through the verification process, demon-\nstrating how each step builds upon the previous one to create a comprehensive chain of trust.\nAs shown in Figure 9, the verification chain begins with the KmsAuth smart contract, which serves\nas the root of trust for the entire system, and concludes with the key generation application running\nin a TEE. We explain the verification steps as follows.\nFirst,  the address of the Dstack-KMS governance contract (i.e.,  KmsAuth) is publicly available.\nThe KMS governance contract serves as the authoritative registry for (1) off-chain KMS nodes and\n(2) dedicated governance contracts (i.e., AppAuth) for TEE applications.  It is worth noting that the\nDstack-Gateway can be regarded as a special TEE application that attests and forwards requests to\nother user applications while maintaining consistent verification procedures.\nThe  KmsAuth  contract  records  both  the  measurements  of  off-chain  KMS  node  programs  (KMS\ndigest, which is the hash of the docker compose file and the images used in In-CC Build) and the TDX\n14\nFigure 9:  The verification chain from authoritative registries to runtime measurements\nQuote of the first KMS node, which acts as the primary key generator.  The identities of subsequent\nKMS  nodes  must  first  be  registered  in  KmsAuth  and  verified  by  the  first  KMS  node  before  they\ncan participate in key generation.  These data, together with the open-source Dstack-KMS codebase,\nallow users to verify the integrity of the KMS nodes and their code correctness.  Subsequently,  the\noff-chain KMS nodes can be considered trusted extensions and used to verify Quotes from other TEE\napplications,  which  cannot  be  achieved  by  the  on-chain  governance  contract  alone.   The  off-chain\nKMS nodes are responsible for generating and managing cryptographic keys (i.e., the root key) and\nthe corresponding certificates (explained in Section 2.3.1), which are further used to authorize TEE\napplications after they are verified, thereby avoiding redundant verification.\nSecond, users can verify the validity of Dstack-Gateway.  By default, this is delegated to the off-\nchain  KMS  nodes  during  gateway  registration,  although  users  can  always  request  the  Quote  of  the\ngateway and check the digest of its docker compose file in its governance contract and the codebase.\nAfter the KMS nodes verify the gateway, it will generate its application root key along with a certificate\nchain ending with the root certificate.\nNext, users can access the TEE application through Dstack-Gateway forwarding.  In this case, users\neffectively delegate the verification of the key generation application to the gateway.  The deployment\nof the key generation application starts from the KmsAuth contract.  The deployer first registers it\nand stores the digest (the hash of the docker compose file and the images) on the dedicated AppAuth\ncontract.  Then, as in the previous step, the off-chain KMS nodes verify the Quote of the application\nafter  it  is  deployed  to  the  TEE  and  ensure  it  matches  the  registered  digest.   Only  after  successful\nverification will the key be generated along with the certificate chain.  To be forwarded by the gateway,\nthe application must also register with it.  In this case, the gateway verifies the application’s certificate\nchain and ensures it shares the same root certificate, indicating authorization by the same KMS.\nFinally, the user can invoke the application and request proof of the key it generated.  The applica-\ntion can generate a Quote on demand, with the generated public key included as custom data in the\nQuote.\n15\n3.5    Security Analysis:  Mitigating Threats\nOur key generation example demonstrates Dstack’s comprehensive approach to security across multiple\nattack surfaces.  At the application level, the system prevents unauthorized code deployment through\nrigorous  measurement  verification  against  the  AppAuth  registry.   The  In-CC  Build  process  ensures\nall dependencies originate from verified sources,  while any updates require new registry entries and\ncomplete re-verification.  It is important to note, however, that code audit and review processes remain\nessential for ensuring application code correctness, as the In-CC Build only guarantees the integrity of\nthe build process.\nInfrastructure security is maintained through multiple mechanisms.  TDX Quotes verify Dstack-OS\nintegrity, preventing OS-level tampering.  KMS updates require multi-signature governance approval,\nsafeguarding against unauthorized changes to key management services.  The Quote verification pro-\ncess  includes  firmware  version  validation,  ensuring  applications  run  on  up-to-date  TEE  hardware.\nHardware-backed TDX Quotes effectively prevent attestation spoofing attempts.\nNetwork-level threats are mitigated through the certificate chain validation system.  This prevents\nboth  DNS  hijacking  and  man-in-the-middle  attacks  by  ensuring  authentic  application  identity  and\nenabling end-to-end encryption with verified certificates.  The combination of these security measures\nensures that cryptographic keys maintain their integrity guarantees even when confronted with sophis-\nticated attacks targeting different system layers.\nReferences\n16"
      }
    ]
  },
  {
    "role": "assistant",
    "content": "# Project Proposal Template\n\n## General Information\n1.1. Name of Project\nDstack\n\n1.2. Project Description (what it does, why it is valuable, origin and history)\nDstack is a developer-friendly and security-first SDK that simplifies the deployment of arbitrary containerized applications into Trusted Execution Environments (TEEs). It enables developers to securely deploy containerized applications in TEEs in minutes using familiar tools like docker-compose.yaml. Dstack provides safe management of secrets and sensitive data, along with built-in TLS termination for exposed services.\n\nThe project was built by Kevin Wang and others from Phala Network, inspired by Andrew Miller (Flashbots & Teleport), and has received contributions from Nethermind and many others. Dstack addresses the gap between raw TEE technology and Zero Trust platform requirements by providing portable confidential containers, decentralized code management, and verifiable domain management.\n\n1.3. How does this project align with the Consortium's Mission Statement\n[blank]\n\n1.4. Project website URL\nhttps://docs.phala.network/dstack/overview (inferred from documentation references)\n\n1.5. Social media accounts\n[blank]\n\n## Legal Information\n2.1. Project Logo URL or attachment (Vector Graphic: SVG, EPS).\n[blank]\n\n2.2. Project license. We recommend an OSI-approved license, so if the license is not one on the list, explain why.\nApache License, Version 2.0\n\n2.3. Existing financial sponsorship.\n[blank]\n\n2.4. Trademark status.\n[blank]\n\n## Technical Information\n3.1. High level assessment of project synergy with existing projects under the CCC, including how the project compliments/overlaps with existing projects, and potential ways to harmonize over time. Responses may be included both inline and/or in accompanying documentation.\n[blank]\n\n3.2. Describe the Trusted Computing Base (TCB) of the project. If the project supports multiple environments please describe each TCB. Also identify if dependencies of other project (both CCC or non-CCC) TCBs are taken.\nDstack's TCB includes:\n- Dstack-OS: A minimized operating system image that serves as a hardware abstraction layer\n- OVMF (Open Virtual Machine Firmware): Configures VM hardware specifications\n- Linux kernel with initial ramdisk (initrd)\n- Root filesystem with essential system libraries and tools\n- Intel TDX or equivalent TEE hardware as the foundation\n\nThe system establishes a secure and verifiable startup chain from TEE hardware through to user applications, with each component measuring the next and recording measurements in hardware registers that are incorporated into TEE attestation reports.\n\n3.3. Project Code of Conduct URL. We recommend a Contributor Covenant v2.0 based Code of Conduct, so if the Code of Conduct is not based on that, explain why.\n[blank]\n\n3.4. Source control URL\nhttps://github.com/Dstack-TEE/dstack\n\n3.5. Issue tracker URL\nhttps://github.com/Dstack-TEE/dstack/issues (inferred)\n\n3.6. External dependencies (including licenses, and indicate whether each is a build time or runtime dependency)\n- Intel TDX or equivalent TEE hardware (runtime)\n- Linux kernel (runtime)\n- Docker/container runtime (runtime)\n- Busybox (runtime)\n- LUKS for encryption (runtime)\n- Wireguard-tools (build time)\n- Build-essential, chrpath, diffstat, lz4, xorriso (build time)\n- Rust (build time)\n\n3.7. Standards implemented by the project, if any. Include links to any such standards.\n- TLS/HTTPS for secure communications\n- Certificate Transparency (CT) for certificate monitoring\n- Certificate Authority Authorization (CAA) for domain security\n- Remote Attestation for TEE verification\n\n3.8. Release methodology and mechanics\n[blank]\n\n3.9. Names of initial committers, if different from those submitting proposal\nInitial committers include:\n- Kevin Wang (kvinwang)\n- Shelven Zhou (shelvenzhou)\n- Leechael\n\n3.10. List of project's official communication channels (slack, irc, mailing lists)\n[blank]\n\n3.11. Project Security Response Policy\n[blank]\n\n3.12. Preferred maturity level (Incubation, Graduation, or Emeritus)\n[blank]\n\n3.13. Any additional information the TAC and Board should take into consideration when reviewing your proposal.\nDstack includes several key components:\n- dstack-vmm: Service running on bare TDX host to manage CVMs\n- dstack-gateway: Reverse proxy to forward TLS connections to CVMs\n- dstack-kms: KMS server to generate keys for CVMs\n- dstack-guest-agent: Service in CVM to serve containers' key derivation and attestation requests\n- meta-dstack: Yocto meta layer to build CVM guest images\n\nThe project provides innovative solutions for portable confidential containers, decentralized code management, and verifiable domain management, addressing critical limitations in current TEE implementations for Web3 contexts."
  },
  {
    "role": "user",
    "content": "This is the Mission Statement, fill in 1.3 with it\n\n```\nThe purpose of the Confidential Computing Consortium is to raise, budget and spend funds in support of various open source and/or open standards projects relating to:\n\ndefining confidential computing and accelerating acceptance and adoption in the market.\ndeveloping open enterprise-grade building blocks (e.g., open specifications and open source licensed projects), including a Confidential Computing portfolio and development experience, to enable easy development and management of enterprise-grade Confidential Computing applications, and\ndefining foundational services and frameworks that are Confidential Computing aware and minimize the need for trust.\n```"
  },
  {
    "role": "assistant",
    "content": "## General Information\n1.3. How does this project align with the Consortium's Mission Statement\nDstack directly aligns with the Confidential Computing Consortium's mission by providing enterprise-grade building blocks for confidential computing applications. It accelerates adoption by making TEE deployment developer-friendly through familiar tools like docker-compose, lowering the barrier to entry. Dstack defines foundational services and frameworks that are Confidential Computing aware through its comprehensive architecture (Dstack-OS, Dstack-KMS, Dstack-Gateway). The project minimizes the need for trust by implementing Zero Trust principles with portable confidential containers, decentralized code management, and verifiable domain management. By enabling seamless deployment of containerized applications in TEEs, Dstack contributes significantly to the development experience and practical adoption of confidential computing in real-world scenarios."
  },
  {
    "role": "user",
    "content": "Trademark status.一般的候选项有哪些"
  }
]

Response:

## Legal Information 2.4. Trademark status. Common options for trademark status include: - Registered Trademark (®) - Unregistered/Common Law Trademark (™) - Trademark Application Pending - No Trademark Protection - Trademark Owned by Third Party - Shared Trademark (through license agreement) - Trademark Under Review - Not Applicable (No trademark claims)

Model: claude-3-7-sonnet-202502192025-06-25 13:06:25

Context:

[
  {
    "role": "user",
    "content": [
      {
        "type": "text",
        "text": "Help me fill in the follow template given the project whitepaper and README file.\n\nFor fields with not enough info, leave it \"[blank]\".\n\n```\nProject Proposal Template\n\nGeneral Information\n1.1. Name of Project\n1.2. Project Description (what it does, why it is valuable, origin and history)\n1.3. How does this project align with the Consortium's Mission Statement\n1.4. Project website URL\n1.5. Social media accounts\n\nLegal Information\n2.1. Project Logo URL or attachment (Vector Graphic: SVG, EPS).\n2.2. Project license. We recommend an OSI-approved license, so if the license is not one on the list, explain why.\n2.3. Existing financial sponsorship.\n2.4. Trademark status.\n\nTechnical Information\n3.1. High level assessment of project synergy with existing projects under the CCC, including how the project compliments/overlaps with existing projects, and potential ways to harmonize over time. Responses may be included both inline and/or in accompanying documentation.\n3.2. Describe the Trusted Computing Base (TCB) of the project. If the project supports multiple environments please describe each TCB. Also identify if dependencies of other project (both CCC or non-CCC) TCBs are taken.\n3.3. Project Code of Conduct URL. We recommend a Contributor Covenant v2.0 based Code of Conduct, so if the Code of Conduct is not based on that, explain why.\n3.4. Source control URL\n3.5. Issue tracker URL\n3.6. External dependencies (including licenses, and indicate whether each is a build time or runtime dependency)\n3.7. Standards implemented by the project, if any. Include links to any such standards.\n3.8. Release methodology and mechanics\n3.9. Names of initial committers, if different from those submitting proposal\n3.10. List of project's official communication channels (slack, irc, mailing lists)\n3.11. Project Security Response Policy\n3.12. Preferred maturity level (Incubation, Graduation, or Emeritus) 3.13. Any additional information the TAC and Board should take into consideration when reviewing your proposal.\n```"
      },
      {
        "type": "text",
        "text": "README.md\n# Dstack\n\n[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/Dstack-TEE/dstack)\n\nDstack is a **developer friendly** and **security first** SDK to simplify the deployment of arbitrary containerized apps into TEE.\n\nMain features:\n\n- 🔒 Deploy containerized apps securely in TEE in minutes\n- 🛠️ Use familiar tools - just write a docker-compose.yaml\n- 🔑 Safely manage secrets and sensitive data\n- 📡 Expose services via built-in TLS termination\n\nDstack is community driven. Open sourced and built by [Kevin Wang](https://github.com/kvinwang) and many others from [Phala Network](https://github.com/Phala-Network), inspired by [Andrew Miller](https://github.com/amiller) (Flashbots & Teleport), and contributed by [Nethermind](https://github.com/NethermindEth/nethermind) and [many others](#contributors).\n\n![Alt](https://repobeats.axiom.co/api/embed/0a001cc3c1f387fae08172a9e116b0ec367b8971.svg \"Repobeats analytics image\")\n\n# Overview\n\nComponents in Dstack:\n\n- `dstack-vmm`: A service running in bare TDX host to manage CVMs\n- `dstack-gateway`: A reverse proxy to forward TLS connections to CVMs\n- `dstack-kms`: A KMS server to generate keys for CVMs\n- `dstack-guest-agent`: A service running in CVM to serve containers' key derivation and attestation requests\n- `meta-dstack`: A Yocto meta layer to build CVM guest images\n\nThe overall architecture is shown below:\n![arch](./docs/assets/arch.png)\n\n# Directory structure\n\n```text\ndstack/\n    kms/                         A prototype KMS server\n    guest-agent/                 A service running in CVM to serve containers' key derivation and attestation requests.\n    dstack-util/                 A CLI tool in the guest setting up the system, getting TDX quote, extending RTMR, generating cert for RA-TLS, etc.\n    vmm/                         A service running in bare TDX host to manage CVMs\n    gateway/                     A reverse proxy to forward TLS connections to CVMs\n    certbot/                     A tool to automatically obtain and renew TLS certificates for dstack-gateway\n    ra-rpc/                      RA-TLS support for pRPC\n    ra-tls/                      RA-TLS support library\n    tdx-attest/                  Guest library for getting TDX quote and extending RTMR\n```\n\n# Build and play locally\n\n## Prerequisites\n\n- A bare metal TDX server setup following [canonical/tdx](https://github.com/canonical/tdx)\n- Public IPv4 address assigned to the machine\n- At least 16GB RAM, 100GB free disk space.\n- A domain with DNS access if you want to set up `dstack-gateway` for Zero Trust HTTPS\n\n> [!NOTE]\n>\n> This doc assumes you have access to a compatible Intel TDX Server ready to be configured with Dstack. Check the [Hardware Requirements](https://docs.phala.network/dstack/hardware-requirements) for more information on buying a bare metal server or renting a server from OVH. To start learning about Dstack check out the [docs](https://docs.phala.network/dstack/overview).\n>\n> If you are looking to deploy a CVM in minutes, go to the docs to learn how to [sign-up for a Phala Cloud Account](https://docs.phala.network/phala-cloud/getting-started/sign-up-for-cloud-account) and [deploy your first CVM on Dstack]((https://docs.phala.network/phala-cloud/getting-started/start-from-cloud-ui)).\n\n## Install dependencies\n\n```bash\n# for Ubuntu 24.04\nsudo apt install -y build-essential chrpath diffstat lz4 wireguard-tools xorriso\n# install rust\ncurl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh\n```\n\n## Build and run for local development\n\n### Build the artifacts\n```bash\ngit clone https://github.com/Dstack-TEE/meta-dstack.git --recursive\ncd meta-dstack/\n\nmkdir build\ncd build\n../build.sh hostcfg\n# This outputs the following message:\n# Config file ../build-config.sh created, please edit it to configure the build\n\nvim ./build-config.sh\n```\n\nReview and customize the `build-config.sh` configuration file according to your environment requirements. The file contains network ports, domain settings, and other important parameters. Once configured, run the build script again to generate the necessary artifacts:\n\n```bash\n../build.sh hostcfg\n\n# If everything is okay, you should see the built artifacts in the `build` directory.\n$ ls\ncerts  images  dstack-kms  kms.toml  run  dstack-vmm  vmm.toml  dstack-gateway  gateway.toml\n```\n\n### Download guest image or build guest image from source\n\n```bash\n# This will download the guest image from the release page.\n../build.sh dl 0.5.2\n```\n\nOr build guest image from source:\n\n```bash\n# This will build the guest image from source using the yocto meta layer. This will take a while.\n../build.sh guest\n```\n\n> **Note on Reproducible Builds**: The build command above does not guarantee reproducibility. For reproducible builds across different build environments, please refer to the [reproducible build instructions](https://github.com/Dstack-TEE/meta-dstack?tab=readme-ov-file#reproducible-build-the-guest-image) in the meta-dstack repository.\n\n### Run components\nNow you can open 3 terminals to start the components:\n\n1. Run `./dstack-kms -c kms.toml`\n2. Run `sudo ./dstack-gateway -c gateway.toml`\n3. Run `./dstack-vmm -c vmm.toml`\n\n⚠️ *Warning: this is for local development, and the kms is not secure, so you should not use it in production.*\nFor production, you should follow the [deployment guide](./docs/deployment.md) and read the [security guide](./docs/security-guide/security-guide.md).\n\n## Deploy an App\nOpen the dstack-vmm webpage [http://localhost:9080](http://localhost:9080)(change the port according to your configuration) on your local machine to deploy a `docker-compose.yaml` file:\n\n![vmm](./docs/assets/vmm.png)\n\nAfter the container deployed, it should need some time to start the CVM and the containers. Time would be vary depending on your workload.\n\n- Click the [Logs] button to see the logs of the CVM, you can see if the container is finished starting there.\n\n- Once the container is running, you can click the [Dashboard] button to see some information of the container. And the logs of the containers can be seen in the [Dashboard] page.\n\n    ![dstack-guest-agent](./docs/assets/guest-agent.png)\n\n- You can open dstack-gateway's dashboard at [https://localhost:9070](https://localhost:9070) to see the CVM's wireguard ip address, as shown below:\n\n![dstack-gateway](./docs/assets/gateway.png)\n\n## Pass Secrets to Apps\nWhen deploying a new App, you can pass private data via Encrypted Environment Variables. These variables can be referenced in the docker-compose.yaml file as shown below:\n\n![secret](./docs/assets/secret.png)\n\nThe environment variables will be encrypted in the client-side and decrypted in the CVM before being passed to the containers.\n\n## Access the App\n\nOnce the app is deployed and listening on an HTTP port, you can access the HTTP service via dstack-gateway's public domain. The ingress mapping rules are:\n\n- `<id>[s].<base_domain>` maps to port `80` or `443` if with `s` in the CVM.\n- `<id>-<port>[s].<base_domain>` maps to port `<port>` in the CVM.\n\nFor example, `3327603e03f5bd1f830812ca4a789277fc31f577-8080.app.kvin.wang` maps to port `8080` in the CVM.\n\nWhere the `<id>` can be either the app id or the instance id. If the app id is used, one of the instances will be selected by the load balancer.\nIf the `id-port` part ends with `s`, it means the TLS connection will be passthrough to the app rather than terminating at dstack-gateway.\n\nYou can also ssh into the CVM to inspect more information, if your deployment uses the image `dstack-x.x.x-dev`:\n\n```bash\n# The IP address of the CVM can be found in the dstack-gateway dashboard.\nssh [email protected]\n```\n\n## Getting TDX quote in docker container\n\nTo get a TDX quote within app containers:\n\n1. Mount `/var/run/dstack.sock` to the target container in `docker-compose.yaml`\n\n    ```yaml\n    version: '3'\n    services:\n    nginx:\n        image: nginx:latest\n        volumes:\n        - /var/run/dstack.sock:/var/run/dstack.sock\n        ports:\n        - \"8080:80\"\n        restart: always\n    ```\n\n2. Execute the quote request command in the container.\n\n    ```bash\n    # The argument report_data accepts binary data encoding in hex string.\n    # The actual report_data passing the to the underlying TDX driver is sha2_256(report_data).\n    curl --unix-socket /var/run/dstack.sock http://localhost/GetQuote?report_data=0x1234deadbeef | jq .  \n    ```\n\n## Container logs\n\nContainer logs can be obtained from the CVM's `dashboard` page or by curl:\n\n```bash\ncurl 'http://<appid>.app.kvin.wang:9090/logs/<container name>?since=0&until=0&follow=true&text=true&timestamps=true&bare=true'\n```\n\nReplace `<appid>` and `<container name>` with actual values. Available parameters:\n\n- since=0: Starting Unix timestamp for log retrieval\n- until=0: Ending Unix timestamp for log retrieval\n- follow: Enables continuous log streaming\n- text: Returns human-readable text instead of base64 encoding\n- timestamps: Adds timestamps to each log line\n- bare: Returns the raw log lines without json format\n\nThe response of the RPC looks like:\n```\n$ curl 'http://0.0.0.0:9190/logs/zk-provider-server?text&timestamps'\n{\"channel\":\"stdout\",\"message\":\"2024-09-29T03:05:45.209507046Z Initializing Rust backend...\\n\"}\n{\"channel\":\"stdout\",\"message\":\"2024-09-29T03:05:45.209543047Z Calling Rust function: init\\n\"}\n{\"channel\":\"stdout\",\"message\":\"2024-09-29T03:05:45.209544957Z [2024-09-29T03:05:44Z INFO  rust_prover] Initializing...\\n\"}\n{\"channel\":\"stdout\",\"message\":\"2024-09-29T03:05:45.209546381Z [2024-09-29T03:05:44Z INFO  rust_prover::groth16] Starting setup process\\n\"}\n```\n\n## TLS Passthrough with Custom Domain\n\ndstack-gateway supports TLS passthrough for custom domains.\n\nSee the example [here](https://github.com/Dstack-TEE/dstack-examples/tree/main/custom-domain/dstack-ingress) for more details.\n\n## Upgrade an App\n\nGot to the dstack-vmm webpage, click the [Upgrade] button, select or paste the compose file you want to upgrade to, and click the [Upgrade] button again.\nThe app id does not change after the upgrade. Stop and start the app to apply the upgrade.\n\n## HTTPS Certificate Transparency\n\nIn the tutorial above, we used a TLS certificate with a private key external to the TEE. To establish trust, we need to generate and maintain the certificate's private key within the TEE and provide evidence that all TLS certificates for the domain were originate solely from dstack-gateway CVM.\n\nBy combining Certificate Transparency Logs and CAA DNS records, we can make best effort to minimize security risks. Here's our approach:\n\n- Set CAA records to allow only the account created in dstack-gateway CVM to request Certificates.\n- Launch a program to monitor Certificate Transparency Log and give alarm once any certificate issued to a pubkey that isn’t generated by dstack-gateway CVM.\n\n### Configurations\n\nTo launch Certbot, you need to own a domain hosted on Cloudflare. Obtain an API token with DNS operation permissions from the Cloudflare dashboard. Configure it in the `build-config.sh`:\n\n```bash\n# The directory to store the auto obtained TLS certificate and key\nGATEWAY_CERT=${CERBOT_WORKDIR}/live/cert.pem\nGATEWAY_KEY=${CERBOT_WORKDIR}/live/key.pem\n\n# for certbot\nCF_ZONE_ID=cc0a40...\nCF_API_TOKEN=g-DwMH...\n# ACME_URL=https://acme-v02.api.letsencrypt.org/directory\nACME_URL=https://acme-staging-v02.api.letsencrypt.org/directory\n```\n\nThen re-run the ../build.sh:\n\n```bash\n../build.sh\n```\n\n### Launch certbot\n\nThen run the certbot in the `build/` and you will see the following log:\n```text\n$ RUST_LOG=info,certbot=debug ./certbot renew -c certbot.toml\n2024-10-25T07:41:00.682990Z  INFO certbot::bot: creating new ACME account\n2024-10-25T07:41:00.869246Z  INFO certbot::bot: created new ACME account: https://acme-staging-v02.api.letsencrypt.org/acme/acct/168601853\n2024-10-25T07:41:00.869270Z  INFO certbot::bot: setting CAA records\n2024-10-25T07:41:00.869276Z DEBUG certbot::acme_client: setting guard CAA records for app.kvin.wang\n2024-10-25T07:41:01.740767Z DEBUG certbot::acme_client: removing existing CAA record app.kvin.wang 0 issuewild \"letsencrypt.org;validationmethods=dns-01;accounturi=https://acme-staging-v02.api.letsencrypt.org/acme/acct/168578683\"\n2024-10-25T07:41:01.991298Z DEBUG certbot::acme_client: removing existing CAA record app.kvin.wang 0 issue \"letsencrypt.org;validationmethods=dns-01;accounturi=https://acme-staging-v02.api.letsencrypt.org/acme/acct/168578683\"\n2024-10-25T07:41:02.216751Z DEBUG certbot::acme_client: setting CAA records for app.kvin.wang, 0 issue \"letsencrypt.org;validationmethods=dns-01;accounturi=https://acme-staging-v02.api.letsencrypt.org/acme/acct/168601853\"\n2024-10-25T07:41:02.424217Z DEBUG certbot::acme_client: setting CAA records for app.kvin.wang, 0 issuewild \"letsencrypt.org;validationmethods=dns-01;accounturi=https://acme-staging-v02.api.letsencrypt.org/acme/acct/168601853\"\n2024-10-25T07:41:02.663824Z DEBUG certbot::acme_client: removing guard CAA records for app.kvin.wang\n2024-10-25T07:41:03.095564Z DEBUG certbot::acme_client: generating new cert key pair\n2024-10-25T07:41:03.095678Z DEBUG certbot::acme_client: requesting new certificates for *.app.kvin.wang\n2024-10-25T07:41:03.095699Z DEBUG certbot::acme_client: creating new order\n2024-10-25T07:41:03.250382Z DEBUG certbot::acme_client: order is pending, waiting for authorization\n2024-10-25T07:41:03.283600Z DEBUG certbot::acme_client: creating dns record for app.kvin.wang\n2024-10-25T07:41:04.027882Z DEBUG certbot::acme_client: challenge not found, waiting 500ms tries=2 domain=\"_acme-challenge.app.kvin.wang\"\n2024-10-25T07:41:04.600711Z DEBUG certbot::acme_client: challenge not found, waiting 1s tries=3 domain=\"_acme-challenge.app.kvin.wang\"\n2024-10-25T07:41:05.642300Z DEBUG certbot::acme_client: challenge not found, waiting 2s tries=4 domain=\"_acme-challenge.app.kvin.wang\"\n2024-10-25T07:41:07.715947Z DEBUG certbot::acme_client: challenge not found, waiting 4s tries=5 domain=\"_acme-challenge.app.kvin.wang\"\n2024-10-25T07:41:11.724831Z DEBUG certbot::acme_client: challenge not found, waiting 8s tries=6 domain=\"_acme-challenge.app.kvin.wang\"\n2024-10-25T07:41:19.815990Z DEBUG certbot::acme_client: challenge not found, waiting 16s tries=7 domain=\"_acme-challenge.app.kvin.wang\"\n2024-10-25T07:41:35.852790Z DEBUG certbot::acme_client: setting challenge ready for https://acme-staging-v02.api.letsencrypt.org/acme/chall-v3/14584884443/mQ-I2A\n2024-10-25T07:41:35.934425Z DEBUG certbot::acme_client: challenges are ready, waiting for order to be ready\n2024-10-25T07:41:37.972434Z DEBUG certbot::acme_client: order is ready, uploading csr\n2024-10-25T07:41:38.052901Z DEBUG certbot::acme_client: order is processing, waiting for challenge to be accepted\n2024-10-25T07:41:40.088190Z DEBUG certbot::acme_client: order is valid, getting certificate\n2024-10-25T07:41:40.125988Z DEBUG certbot::acme_client: removing dns record 6ab5724e8fa7e3e8f14e93333a98866a\n2024-10-25T07:41:40.377379Z DEBUG certbot::acme_client: stored new cert in /home/kvin/codes/meta-dstack/dstack/build/run/certbot/backup/2024-10-25T07:41:40.377174477Z\n2024-10-25T07:41:40.377472Z  INFO certbot::bot: checking if certificate needs to be renewed\n2024-10-25T07:41:40.377719Z DEBUG certbot::acme_client: will expire in Duration { seconds: 7772486, nanoseconds: 622281542 }\n2024-10-25T07:41:40.377752Z  INFO certbot::bot: certificate /home/kvin/codes/meta-dstack/dstack/build/run/certbot/live/cert.pem is up to date\n```\n\nWhere the command did are:\n\n- Registered to letsencrypt and got a new account `https://acme-staging-v02.api.letsencrypt.org/acme/acct/168601853`\n- Auto set CAA records for the domain on cloudflare, you can open the CF dashboard to see the record:\n\n    ![certbot-caa](./docs/assets/certbot-caa.png)\n\n- Auto requested a new certificate from Let's Encrypt. Automatically renews the certificate to maintain its validity\n\n### Launch dstack-gateway\n\nExecute dstack-gateway with `sudo ./dstack-gateway -c gateway.toml`, then access the web portal to check the dstack-gateway CVM managed Let's Encrypt account. The account's private key remains securely sealed within the TEE.\n\n![gateway-accountid](./docs/assets/gateway-accountid.png)\n\n## Certificate transparency log monitor\n\nTo enhance security, we've limited TLS certificate issuance to dstack-gateway via CAA records. However, since these records can be modified through Cloudflare's domain management, we need to implement global CA certificate monitoring to maintain security oversight.\n\n`ct_monitor` tracks Certificate Transparency logs via [https://crt.sh](https://crt.sh/?q=app.kvin.wang), comparing their public key with the ones got from dstack-gateway RPC. It immediately alerts when detecting unauthorized certificates not issued through dstack-gateway:\n\n```text\n$ ./ct_monitor -t https://localhost:9010/prpc -d app.kvin.wang\n2024-10-25T08:12:11.366463Z  INFO ct_monitor: monitoring app.kvin.wang...\n2024-10-25T08:12:11.366488Z  INFO ct_monitor: fetching known public keys from https://localhost:9010/prpc\n2024-10-25T08:12:11.566222Z  INFO ct_monitor: got 2 known public keys\n2024-10-25T08:12:13.142122Z  INFO ct_monitor: ✅ checked log id=14705660685\n2024-10-25T08:12:13.802573Z  INFO ct_monitor: ✅ checked log id=14705656674\n2024-10-25T08:12:14.494944Z ERROR ct_monitor: ❌ error in CTLog { id: 14666084839, issuer_ca_id: 295815, issuer_name: \"C=US, O=Let's Encrypt, CN=R11\", common_name: \"kvin.wang\", name_value: \"*.app.kvin.wang\", not_before: \"2024-09-24T02:23:15\", not_after: \"2024-12-23T02:23:14\", serial_number: \"03ae796f56a933c8ff7e32c7c0d662a253d4\", result_count: 1, entry_timestamp: \"2024-09-24T03:21:45.825\" }\n2024-10-25T08:12:14.494998Z ERROR ct_monitor: error: certificate has issued to unknown pubkey: 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\n```\n\n# Troubleshooting\n\n### Error from dstack-vmm: qemu-system-x86_64: -device vhost-vsock-pci,guest-cid=<id>: vhost-vsock: unable to set guest cid: Address already in use\n\n`dstack-vmm` may throw this error when creating a new VM if the [Unix Socket CID](https://man7.org/linux/man-pages/man7/vsock.7.html) is occupied. To solve the problem, first, you should list the occupied CID:\n\n```bash\nps aux | grep 'guest-cid='\n```\n\nThen choose a new range of the CID not conflicting with the CID in use. You can change `build/vmm.toml` file and restart `dstack-vmm`. This error should disappear. For example, you may find 33000-34000 free to use:\n\n```toml\n[cvm]\ncid_start = 33000\ncid_pool_size = 1000\n```\n\nWhen building the dstack from scratch, you should change the CID configs in `build-config.sh` instead, because `vmm.toml` file is generated by `build.sh`. Its content is derived from `build-config.sh`.\n\nYou may encounter this problem when upgrading from an older version of dstack, because CID was introduced in `build-config.sh` in later versions. In such case, please follow the docs to add the missing entries in `build-config.sh` and rebuild dstack.\n\n### Error: Operation not permitted when building guest image\n\nWhen running `../build.sh guest`, you might encounter this error:\n\n```\nTraceback (most recent call last):\n  File \"/meta-dstack/poky/bitbake/bin/bitbake-worker\", line 278, in child\n    bb.utils.disable_network(uid, gid)\n  File \"/meta-dstack/poky/bitbake/lib/bb/utils.py\", line 1696, in disable_network\n    with open(\"/proc/self/uid_map\", \"w\") as f:\nPermissionError: [Errno 1] Operation not permitted\n```\n\nThis error occurs because Ubuntu 23.10 and later versions restrict unprivileged user namespaces by default. To fix this, run:\n\n```bash\nsudo sysctl kernel.apparmor_restrict_unprivileged_userns=0\n```\n\nThen try building again. For more information about this restriction, see the [Ubuntu discourse post](https://discourse.ubuntu.com/t/spec-unprivileged-user-namespace-restrictions-via-apparmor-in-ubuntu-23-10/37626).\n\n\n# Contributors\n\nDstack is proudly built by open source and Pi-rateship contributors:\n\n- Phala Network: [Kevin Wang](https://github.com/kvinwang), [Shelven Zhou](https://github.com/shelvenzhou), [Leechael](https://github.com/leechael)\n- Teleport: [Andrew Miller](https://github.com/amiller), [Sxy Sun](https://github.com/sxysun)\n- Flashbots: [Tina](https://github.com/CarboClanC), [Mateusz](https://github.com/Ruteri), [Dmarz](https://github.com/dmarzzz), [Moe](https://github.com/MoeMahhouk)\n- Ithaca: [Georgios](https://github.com/gakonst)\n- Fabric: [@gaoist](https://x.com/gaoist)\n- And many more...\n\nThe inspiration for this work stems from [Andrew Miller](https://github.com/amiller)’s pioneering concept of a [Docker-based P2P TEE SDK](https://collective.flashbots.net/t/dstack-speedrunning-a-p2p-confidential-vm/3876).\n\nThis project cannot be built without standing on the shoulders of giants:\n\n- [konvera/meta-confidential-compute](https://github.com/konvera/meta-confidential-compute)\n\nSpecial acknowledgment to [Flashbots](https://github.com/flashbots) for building a community around TEE. The TEE Hacker House initiative, organized by [Flashbots](https://github.com/flashbots) and led by [Tina](https://github.com/CarboClanC), has brought together TEE builders to develop tools for TEE-Web3 integration. This collaborative journey has generated invaluable insights for advancing secure, confidential environments within Web3.\n\nTogether, we’re shaping the future of TEE in Web3, paving the way for more secure and developer-accessible confidential computing!\n\nFor a full list of the direct contributors to this repo, see [Contributors](https://github.com/Dstack-TEE/dstack/contributors) on GitHub.\n\n\n# License\n\nCopyright 2024 Phala Network and Contributors.\n\nLicensed under the Apache License, Version 2.0 (the \"License\"); you may not use this file except in compliance with the License. You may obtain a copy of the License at\n\n[http://www.apache.org/licenses/LICENSE-2.0](http://www.apache.org/licenses/LICENSE-2.0)"
      },
      {
        "type": "text",
        "text": "main.pdf\nDstack:  A Zero Trust Framework for Confidential Containers\nJune 23, 2025\nAbstract\nWeb3 applications require execution platforms that maintain confidentiality and integrity with-\nout relying on centralized trust authorities.  While Trusted Execution Environments (TEEs) offer\npromising capabilities for confidential computing, current implementations face significant limita-\ntions in security reliability, censorship resistance, and vendor independence when applied to Web3\ncontexts.  This paper presents Dstack, a comprehensive framework that transforms raw TEE tech-\nnology  into  a  true  Zero  Trust  platform  aligned  with  Web3  principles.   We  introduce  three  key\ninnovations:  (1) Portable Confidential Containers that enable seamless workload migration across\nheterogeneous TEE environments while maintaining security guarantees, (2) Decentralized Code\nManagement that leverages smart contracts for transparent governance of TEE applications, and\n(3) Verifiable Domain Management that ensures secure and verifiable application identity without\ncentralized authorities. Through these innovations, implemented via Dstack-OS, Dstack-KMS, and\nDstack-Gateway components, we demonstrate how to achieve both the performance advantages of\nVM-level TEE solutions and the trustless guarantees required by Web3 applications.  Our evalu-\nation shows that Dstack provides comprehensive security guarantees while maintaining practical\nusability for real-world applications.\n1    Introduction\nThe Web3 ecosystem represents a paradigm shift in digital trust models, fundamentally transforming\nthe relationship between users and application developers.  Unlike traditional systems, Web3 empowers\nusers with unprecedented control over their data through the principle of ”Code is Law” - once deployed,\ncode  operates  autonomously  and  independently  of  external  control.   This  transformation  demands\nrobust execution platforms that maintain confidentiality and integrity without relying on centralized\ntrust authorities.\nFigure 1:  The evolution of trust models from Web2 to Web3, highlighting the shift from centralized control\nto decentralized governance and execution.\nThe contrast between Web2 and Web3 architectures in Figure 1 illustrates this fundamental shift.\nIn Web2 systems, developers maintain complete control through proprietary applications and central-\nized servers, retaining administrative privileges to access and modify user data at will.  Web3’s smart\n1\ncontracts,  however,  represent  the  first  significant  step  toward  true  trustlessness  by  executing  pro-\ngrams on decentralized platforms (blockchains).  Once deployed, administrators cannot influence pro-\ngram execution, and lifecycle management (e.g., code updates) follows predefined agreements through\ndemocratic governance mechanisms like multi-signature wallets and Decentralized Autonomous Orga-\nnizations (DAOs).  This emerging trust model extends beyond basic applications to mission-critical\nscenarios such as AI model training, where data providers and model developers often have competing\ninterests,  and  autonomous  AI  agents  designed  to  operate  independently  of  human  intervention.   In\nthese  contexts,  Zero  Trust  platforms  become  essential  to  host  applications  and  enforce  verification\nmechanisms that appropriately constrain developer authority.\nA Zero Trust platform must enforce the following key principles:\n•  Code is Law: This manifests in two dimensions: (1) the application logic, once deployed, cannot\nbe  changed  unexpectedly;  and  (2)  the  lifecycle  management  of  code—including  deployment,\nupgrades, and deletion—follows predefined governance rules.\n•  Censorship Resistance:  User data remains beyond the control of any single entity, with data\navailability protected against Denial-of-Service attacks.\n•  Full Chain-of-Trust:  When users interact with applications on a Zero Trust platform,  they\nmust be able to verify all aspects of that application, including network setup, application identity\nand code logic, underlying hardware, and execution environment.\n•  Assume Breach:  The platform operates under the assumption that compromises will occur,\nimplementing  mechanisms  for  damage  containment,  rapid  recovery,  and  minimization  of  data\nexposure during security incidents.\nConfidential Computing, particularly through Trusted Execution Environments (TEEs), has emerged\nas a promising foundation for extending blockchain capabilities to support complex computational tasks\nwith confidentiality guarantees.  Recent advances in VM-level TEE solutions, including Intel TDX and\nAMD SEV, have demonstrated substantial performance improvements and developer-friendly inter-\nfaces,  making  them  compelling  candidates  for  Web3  deployment.   The  integration  of  GPUs  within\nTEEs [?] now enables verifiable execution of both Large Language Models and AI agents, providing\ncryptographic guarantees of computational integrity.\nHowever, a significant gap exists between raw TEE technology and the requirements of a true Zero\nTrust platform.  Current TEE implementations face several critical limitations when applied to Web3\ncontexts:\n•  Security Reliability:  Recent vulnerability discoveries in TEE systems have raised significant con-\ncerns  about  their  effectiveness  as  trust  anchors.   The  persistence  of  side-channel  attacks  and\nmicro-architectural vulnerabilities undermines confidence in TEE security guarantees, particu-\nlarly for high-value Web3 applications where a single compromise could lead to catastrophic data\nexposure.\n•  Censorship Vulnerability:  Conventional TEE encryption schemes bind encryption keys to spe-\ncific  hardware  instances,  creating  single  points  of  failure  that  contradict  Web3’s  requirement\nfor censorship resistance.  This architectural limitation means that data availability cannot be\nguaranteed if specific hardware instances are compromised or become unavailable.\n•  Vendor Dependencies:  Current trust models heavily rely on centralized hardware manufacturers\nand verification processes, introducing risks of vendor lock-in and potential censorship vectors.\nThis centralization contradicts Web3’s core principles of decentralization and trustlessness.\n•  Incomplete Verifiability:  While TEEs provide Remote Attestation capabilities to verify applica-\ntion and hardware identity, they fail to deliver the comprehensive chain of trust required in Zero\nTrust environments.  Users need guarantees that programs will process their data as expected\nand cannot be modified without proper authorization—capabilities beyond current attestation\nmechanisms.\nTo bridge this gap between raw TEE technology and Zero Trust requirements, we present Dstack,\na comprehensive framework for confidential containers that introduces three key innovations:\n2\n•  Portable Confidential Container: Our architecture enables seamless migration of confidential\nworkloads across different TEE instances and hardware vendors,  significantly reducing vendor\nlock-in risks while maintaining robust security guarantees.  This innovation directly addresses the\ncensorship vulnerability and vendor dependency limitations by providing hardware abstraction\nand state continuity across heterogeneous TEE environments.\n•  Decentralized Code Management:  We implement a comprehensive governance framework\nthat leverages smart contracts for transparent and decentralized management of TEE applica-\ntions.  This  system ensures verifiable deployment  and upgrade processes,  enforcing the  “Code\nis Law” principle by binding application lifecycles to on-chain governance decisions.  This inno-\nvation addresses the incomplete verifiability limitation by creating an immutable audit trail of\napplication changes.\n•  Verifiable Domain Management: Our novel approach to certificate management ensures that\nconfidential containers can exclusively control domains and provide native HTTPS support to\nTEE applications without relying on centralized authorities.  This system serves as a middleware\nbetween TEE applications and existing TLS-based networks, enabling users to establish end-to-\nend encrypted channels to TEE applications without modifications to client software.\nThese innovations are implemented through a cohesive system architecture comprising three core\ncomponents:\n•  Dstack-OS: A hardware abstraction layer with a minimized operating system image that elimi-\nnates differences in underlying TEE hardware while reducing the attack surface.  This component\nprovides a consistent, secure runtime environment across diverse TEE implementations.\n•  Dstack-KMS:  A  blockchain-controlled  key  management  service  that  replaces  hardware-based\nencryption schemas with an independent service for generating and managing secret keys.  This\ncomponent  enables  secure  data  migration  across  TEE  instances  and  supports  key  rotation  to\nprovide forward and backward data secrecy, mitigating the impact of potential TEE compromises.\n•  Dstack-Ingress and Dstack-Gateway: Complementary systems providing TEE-controlled domain\nmanagement through different approaches—Dstack-Ingress enables applications to specify cus-\ntom domains with minimal integration requirements, while Dstack-Gateway offers pre-registered\nwildcard domains requiring no application code changes.\nBy addressing the critical limitations of current TEE implementations, Dstack establishes a compre-\nhensive framework that transforms raw TEE technology into a true Zero Trust platform aligned with\nWeb3’s fundamental principles.  Our approach not only enhances the security and reliability of confi-\ndential computing but also provides a practical path toward truly decentralized, censorship-resistant\ninfrastructure for next-generation applications.\nThe remainder of this paper details the technical design of Dstack, evaluates its performance and\nsecurity characteristics, and demonstrates how our innovations collectively create a Zero Trust platform\nthat maintains the performance advantages of VM-level TEE solutions while addressing their inherent\nlimitations in Web3 contexts.\n2    System Design\n2.1    Portable Confidential Container\nContainerization has transformed cloud-native application deployment by providing unparalleled porta-\nbility and scalability through effective data separation.  These capabilities are particularly critical for\nTrusted Execution Environment (TEE) applications, as they directly address the inherent limitations\noutlined in Section 1:\n•  Security Reliability:  Containerized applications can be efficiently transferred from compro-\nmised TEE hardware to secure instances,  preserving code integrity.  Together with our secure\ndata migration mechanism that ensures both forward and backward secrecy, this approach sig-\nnificantly limits privacy leakage risks even when individual TEE instances are compromised.\n3\nFigure 2:  The architecture of Dstack, including Dstack-OS and Dstack-KMS. Dstack-OS provides a hardware\nabstraction layer with a minimized operating system image, while Dstack-KMS replaces the hardware-based\ndata encryption keys with a blockchain-controlled key management service.  TODO: redraw this to put the\ncomponents into solutions.\n•  Censorship Resistance: The architecture’s inherent scalability provides robust defense against\nDenial-of-Service attacks. Additionally, by decoupling data storage from execution environments,\nestablished  data  availability  solutions  can  be  readily  integrated  to  ensure  persistent  access  to\napplication data.\n•  Vendor  Independence:   Our  hardware  abstraction  layer  enables  confidential  containers  to\noperate across diverse TEE hardware platforms without modification, eliminating vendor lock-in\nwhile facilitating rapid adoption of emerging TEE technologies as they become available.\nHowever, implementing truly portable confidential containers presents substantial technical chal-\nlenges that differentiate them from conventional containerization.  Two fundamental obstacles must be\novercome:\nFirst, existing TEE implementations generate data sealing keys derived from hardware-bound root\nkeys unique to each TEE instance.  This architectural design creates an inherent barrier to portability\n— data encrypted by one TEE instance cannot be decrypted by any other, even when running identical\napplication code.  Prior research has largely circumvented this limitation by restricting TEEs to state-\nless applications, but this approach severely constrains their utility in complex real-world scenarios.\nSecond,  TEE implementations from different vendors impose disparate specifications for deploy-\nable programs.  This fragmentation forces developers to create and maintain multiple artifacts across\nplatforms, each requiring separate (and expensive) code reviews to verify functional equivalence — a\nprocess that undermines the trust guarantees central to Web3 applications.\nTo address these challenges comprehensively, we introduce two complementary components: Dstack-\nKMS and Dstack-OS.\n2.1.1    Dstack-KMS: Blockchain-Controlled Secret Derivation\nDstack-KMS  is  a  secret  derivation  service  that  fundamentally  transforms  how  encryption  keys  are\nmanaged in confidential computing environments.  Its primary function is to generate a unique and\nstable secret (the Root Key ) for each application based on its code and configurations.  This root key\n4\nserves as the foundation for deriving additional application-specific secrets used for data encryption\nand verifiable random number generation.\nUnlike hardware-based encryption approaches, Dstack-KMS deliberately decouples key generation\nfrom specific TEE hardware instances.  This architectural decision enables the critical capability of\nencrypted  data  migration  between  different  TEE  instances,  with  decryption  possible  after\nproper authorization.  This feature is essential for achieving true censorship resistance.\nGiven  its  position  as  the  root-of-trust  for  the  entire  system,  the  verifiability  and  availability  of\nDstack-KMS are paramount.  Unlike previous approaches [?] that assume TEE infallibility, our threat\nmodel explicitly acknowledges that TEEs can be compromised.  To address this reality, Dstack-\nKMS  implements  comprehensive  key  rotation  capabilities  that  provide  both  backward  and  forward\nsecrecy for application data. This ensures that even if a specific TEE hardware instance is compromised,\napplications can be migrated with limited data exposure.\nFigure 3:  The key derivation hierarchy of Intel SGX illustrates how conventional TEE implementations bind\nencryption keys to hardware.\nTo understand the limitations of conventional approaches, Figure 3 illustrates the key derivation\nhierarchy in Intel SGX. This design uses a hardware-bound key to both identify the TEE instance (for\nRemote Attestation) and generate encryption keys for data sealing.  While this approach effectively\nestablishes hardware identity, it fundamentally undermines censorship resistance:\n•  The root key cannot be updated, meaning a compromised TEE with a leaked root key remains\npermanently vulnerable even after patching the underlying vulnerability.\n•  Encrypted data becomes intrinsically bound to specific TEE hardware instances, creating single\npoints of failure that contradict Web3’s censorship resistance requirements.\nOur  Dstack-KMS  addresses  these  limitations  by  delegating  secret  generation  to  an  independent\nservice that ensures encrypted data remains portable across TEE instances.\nAs illustrated in Figure 4, Dstack-KMS comprises an on-chain governance smart contract coupled\nwith an off-chain peer-to-peer network where the actual secret derivation service operates.  To ensure\ncomprehensive verifiability of the Dstack-KMS program’s integrity and correctness, we implement a\nmulti-stage verification process:\n1.  The Dstack-KMS codebase is fully open-sourced [?], enabling thorough code and security reviews\nto verify key management logic and ensure the absence of backdoors.\n5\nFigure 4:  The architecture of Dstack-KMS combines on-chain governance through smart contracts with an\noff-chain P2P network of secret derivation service nodes.  This design ensures both verifiability and resilience\nagainst compromise.\n2.  Executable  binaries  are  produced  through  reproducible  build  processes,  allowing  verifiers  to\nconfirm that the runtime code matches the reviewed source code.\n3.  The cryptographic digest of valid executables is published through the governance smart contract,\ncreating an immutable reference for verification.\n4.  Each service node operates within its own TEE instance.  Critically, we rely on the TEE solely for\nmeasuring the executable and ensuring it matches the on-chain digest—not for the fundamental\nsecurity of the key management process.\nThis verification framework ensures that Dstack-KMS remains trustworthy to any third-party verifier\nwhile avoiding dependency on the absolute security of any single TEE instance.\nThe core logic of each Dstack-KMS service node is intentionally minimalist, focusing exclusively on\nthe generation and secure distribution of the root key, along with deriving encryption keys for TEE\napplications.  This simplicity enables the implementation of Multi-Party Computation (MPC) based\nthreshold key generation and derivation without concerning performance overhead.  We have developed\ntwo complementary implementations:\n•  Simple Duplication:  The first node in the P2P network generates a cryptographically secure\nrandom number as the root key, then shares it with other nodes after verifying their attestation\nreports.  All nodes maintain identical copies of the root key and derive consistent encryption keys\nfor  applications.   This  approach  maximizes  availability—as  long  as  at  least  one  node  remains\noperational, the root key can be recovered.\n•  MPC-Based Key Generation:  While simple duplication provides robust availability, it cre-\nates vulnerability to single-node compromises.  Our MPC implementation uses Shamir’s Secret\nSharing scheme [?] to distribute the root key across multiple nodes, ensuring that compromising\nany individual node (or even up tot− 1 nodes, wheret is the configured threshold) does not\nexpose  the  root  key.   This  approach  also  enables  advanced  features  like  key  rotation  without\nrequiring application reconfiguration.\nKey Derivation    Dstack-KMS implements a comprehensive key derivation framework to generate\napplication-specific keys from the root key:\n•  Application CA Key:  Derived from the root CA key using the application’s unique identifier\n(calculated as the hash of the application’s code and configuration).\n•  Disk Encryption Key:  Derived using a combination of the application identifier and instance\nidentifier, enabling secure storage with portability.\n6\n•  Environment Encryption Key: Derived using the application identifier alone, allowing secure\nenvironment variable management across instances.\n•  ECDSA Key:  Derived from the root ECDSA key, providing applications with consistent cryp-\ntographic identity for signing operations.\nEach derived key maintains cryptographic isolation while ensuring consistency across different TEE\ninstances running the same application.\nKey Rotation    A critical security feature of Dstack-KMS is its support for key rotation, which signif-\nicantly limits the exposure window during potential attacks while ensuring both forward and backward\nsecrecy for sealed data.  Key rotation procedures are initiated exclusively through the governance smart\ncontract, ensuring transparency and auditability.  We discuss two distinct rotation mechanisms:\n•  Root Key Share Rotation:  Our MPC-based implementation enables rotation of individual\nkey  shares  without  modifying  the  root  key  itself.   This  process  enhances  root  key  security  by\nregularly updating the distribution mechanism while remaining transparent to applications, as\nall derived application keys remain unchanged.\n•  Root Key Rotation:  In scenarios where the root key may have been compromised, we support\ncomplete root key rotation.  This process generates an entirely new root key and implements a\ncontrolled handover period during which both old and new keys remain valid.  This transition\nwindow  allows  applications  to  re-encrypt  their  data  with  keys  derived  from  the  new  root  key\nbefore the old root key is permanently destroyed, minimizing service disruption while enhancing\nsecurity.\nThrough these mechanisms, Dstack-KMS provides the foundation for truly portable confidential con-\ntainers by decoupling encryption from hardware dependencies while maintaining robust security guar-\nantees.\n2.1.2    Dstack-OS: Hardware Abstraction Layer\nDstack-OS provides a comprehensive hardware abstraction layer with a minimized operating system\nimage that bridges the gap between application containers and VM-level TEE implementations.  This\nlayer enables applications to deploy across diverse TEE environments without code modifications while\nmaintaining security integrity.  As a shared component across all TEE applications, Dstack-OS must be\nintrinsically secure and verifiable, with no administrative backdoors that could compromise program\ncode or user data.\nVM-level  TEE  solutions  typically  require  developers  to  provide  complete  system  images  encom-\npassing  bootloader,  kernel,  operating  system,  and  application  components.   This  requirement  not\nonly increases development complexity but also introduces potential security vulnerabilities through\nmisconfigured system components.  A secure and properly configured operating system environment\nfundamentally determines the security baseline for all TEE applications built upon it.\nFigure 5 illustrates how Dstack-OS establishes a secure and verifiable startup chain from the TEE\nhardware foundation through to user-provided container images.  Our modular design ensures that the\nmajority of the system can be reused across different TEE hardware implementations, substantially\nreducing the effort required for code review and security auditing.  Combined with reproducible build\nprocesses, this approach enables comprehensive verification of Dstack-OS with minimal overhead while\nsupporting multiple TEE hardware platforms.\nUsing Intel TDX as an exemplar (with similar procedures applicable to other TEE implementa-\ntions like AMD SEV), Dstack-OS consists of the following components,  presented in boot sequence\norder.  During this process, each component measures the next one and records these measurements\nin hardware registers, which are ultimately incorporated into the TEE attestation report:\n•  Hypervisor: When application deployment initiates, the underlying hypervisor (the TDX mod-\nule) loads the Open Virtual Machine Firmware (OVMF), enabling UEFI support for confidential\nvirtual  machines.   The  TDX  module  measures  the  OVMF  code  and  records  its  cryptographic\ndigest in the MRTD register, with the hypervisor’s integrity guaranteed by the TEE hardware\nitself.\n7\nFigure 5:  The architecture of Dstack-OS establishes a secure and verifiable startup chain from TEE hardware\nthrough to user applications.\n•  Open Virtual Machine Firmware (OVMF): The OVMF configures virtual machine hard-\nware  specifications  (CPU,  memory,  and  device  configurations)  and  records  the  configuration\nmeasurement  to  the  RTMR0  register.   It  then  loads  the  Linux  kernel  and  records  the  kernel\nimage measurement to the RTMR1 register.\n•  Kernel:  The kernel first loads an initial ramdisk (initrd) — a temporary in-memory filesystem\ncontaining  minimal  command-line  tools  and  disk  encryption  libraries.   The  initrd  mounts  the\nroot filesystem and records this measurement in the RTMR2 register.\n•  Root Filesystem: The root filesystem (RootFs) is a read-only environment containing essential\nsystem libraries and tools.  It manages the entire lifecycle of deployed applications, measuring\napplication images along with their associated key management system and storing these mea-\nsurements  in  the  RTMR3  register.   The  RootFs  serves  two  primary  functions:  (1)  providing\nthe runtime environment for user-level container images, and (2) managing application data en-\ncryption.   It  interfaces  with  Dstack-KMS  to  acquire  encryption  secrets  and  implements  Linux\nUnified Key Setup (LUKS) to encrypt application data in isolated volumes.  Data integrity is\nensured through dm-verity, a Merkle-tree-based block-level verification tool.  Finally, the RootFs\nconfigures network ingress for the application and initiates execution.\nRather than adapting existing system images, we built Dstack-OS from scratch to ensure only es-\nsential components are included in both the initrd and RootFs.  A comprehensive component inventory\nis provided in Appendix ?? for transparency and review.  Generally,  Dstack-OS includes only basic\nutilities (busybox), filesystem support, and container runtime components.  By implementing Docker\nsupport  while  delegating  orchestration  to  the  application  level,  we  maintain  a  minimal  base  image\nfootprint.\nTo ensure comprehensive verifiability, Dstack-OS is fully open-sourced and supports reproducible\nbuilds,  allowing  anyone  to  review  the  code  and  generate  identical  artifacts  for  verification.   This\napproach provides significant benefits for applications requiring security reviews,  as evaluators need\nonly review the application code rather than the entire system image.\nData Backup and Defense against Rollback Attacks    A critical challenge in confidential com-\nputing is ensuring data durability and integrity, particularly against rollback attacks where adversaries\nattempt to revert applications to previous states to bypass security checks or reuse expired secrets.\nOur architecture provides robust secure data backup support and implements robust anti-rollback\nmechanisms that application developers can integrate:\n•  Secure Backup:  Application data is encrypted using keys derived from Dstack-KMS and can\nbe backed up to external storage providers.  Since encryption keys are not bound to specific TEE\n8\ninstances, data can be restored on any authorized TEE, supporting true portability and disaster\nrecovery.\n•  Monotonic Counters: To prevent rollback attacks, developers can implement monotonic coun-\nters that increment with each critical data update, incorporating the counter value into the en-\ncrypted data.  During restoration, applications verify that the counter value equals or exceeds\nthe last known value, preventing replay of outdated snapshots.\nBy combining these techniques,  Dstack ensures both the recoverability and integrity of confidential\ndata across portable container migrations and backup scenarios.\nTogether, Dstack-KMS and Dstack-OS provide the foundational infrastructure for truly portable\nconfidential containers that maintain security and integrity across heterogeneous TEE environments\nwhile eliminating vendor lock-in and supporting comprehensive verifiability.\n2.2    Decentralized Code Management\nA core principle of Zero Trust platforms is the enforcement of “Code is Law”, ensuring that application\ncode  operates  as  intended  without  unexpected  modifications.   While  TEE  hardware  provides  code\nintegrity guarantees during execution, it cannot independently prevent administrators from deploying\nmalicious code or making unauthorized modifications.  Conversely, smart contracts have established\nrobust methodologies for implementing programmable governance over code lifecycle management —\nsuch as multi-signature requirements that prevent single-actor manipulation.\nOur  decentralized  code  management  framework  bridges  these  two  worlds  by  placing  TEE  ap-\nplication governance under smart contract control,  creating a transparent and auditable system for\napplication deployment and updates that aligns with Web3 principles.\nFigure 6:  The architecture of decentralized code management integrates on-chain governance contracts with\noff-chain TEE through Dstack-KMS.\nAs illustrated in Figure 6, our architecture consists of two complementary components:  on-chain\ngovernance  smart  contracts  and  off-chain  TEE  execution  environments  connected  through  Dstack-\nKMS. This design establishes the on-chain contracts as the definitive root-of-trust for the entire system.\nEvery operation — from initial deployment to code upgrades — must first be initiated and authorized\nthrough the governance contracts before off-chain TEE instances can execute these operations.\nThe governance framework implements a two-tier structure:\n•  KmsAuth Contract:  Serves as the global authority controlling Dstack-KMS operations.  This\ncontract maintains the registry of authorized applications and their governance parameters, en-\nforcing system-wide policies for TEE deployment.  By controlling whether Dstack-KMS shares\n9\napplication  secrets  with  specific  TEE  instances,  the  KmsAuth  contract  effectively  determines\nwhether applications can decrypt their data, thus controlling their complete lifecycle.\n•  AppAuth Contracts:  Individual governance contracts deployed for each application that de-\nfine  application-specific  management  rules.   These  contracts  specify  permissible  code  versions\n(through cryptographic hashes), authorized TEE instance identities, and upgrade approval re-\nquirements.  This modular approach enables customized governance models ranging from tradi-\ntional multi-signature schemes to complex DAO voting mechanisms, allowing each application\nto implement governance appropriate to its requirements.\nThe enforcement mechanism operates through Dstack-KMS, which will only provide application\nsecrets  to  TEE  instances  running  code  versions  explicitly  authorized  by  the  governance  contracts.\nThis creates a cryptographically enforced governance system where unauthorized code versions cannot\naccess application data, regardless of administrative privileges.\nTo  illustrate  this  mechanism,  consider  a  code  upgrade  process  for  an  application  using  a  multi-\nsignature AppAuth contract in Figure 6:\n1.  Developers  publish  the  new  code  version  and  submit  its  cryptographic  hash  to  the  AppAuth\ncontract.\n2.  The  contract  initiates  the  approval  process,  requiring  signatures  from  designated  key  holders\n(e.g., core developers, security auditors, and community representatives).\n3.  Each signature is recorded on-chain, creating an immutable audit trail of the approval process.\n4.  Once the required signature threshold is reached, the AppAuth contract updates its registry of\nauthorized code versions.\n5.  The  KmsAuth  contract,  monitoring  the  AppAuth  contract,  updates  its  authorization  records\naccordingly.\n6.  Dstack-KMS,  which  continuously  synchronizes  with  the  KmsAuth  contract,  begins  providing\napplication secrets to TEE instances running the newly approved code version.\n7.  TEE instances can now deploy the new code with full access to encrypted application data.\nThis process ensures that every code change follows predefined governance rules with complete trans-\nparency.  The on-chain approval records create an immutable audit trail that allows users to verify\nthe entire history of application changes, while the cryptographic enforcement through Dstack-KMS\nguarantees that only properly authorized code can access application data.\nBy combining the code integrity guarantees of TEEs with the transparent governance capabilities\nof  smart  contracts,  our  decentralized  code  management  framework  ensures  that  applications  truly\nembody the ”Code is Law” principle. Every aspect of the application lifecycle—from initial deployment\nto  version  updates  and  potential  retirement—follows  predefined,  transparent  rules  that  cannot  be\ncircumvented by any single entity, including the platform operators themselves.\n2.3    Verifiable Domain Management\nA  complete  Zero  Trust  platform  must  enable  seamless  verification  for  users  across  both  Web3  and\ntraditional  Web2  environments.   Our  Verifiable  Domain  Management  system  completes  the  chain-\nof-trust  by  allowing  standard  Web  browsers  to  cryptographically  verify  TEE  applications  without\nrequiring any client-side modifications or specialized knowledge.\nThis  capability  is  critical  for  mainstream  adoption,  as  it  allows  users  to  interact  with  confiden-\ntial applications using familiar tools while maintaining the same security guarantees provided by the\nunderlying TEE infrastructure.  We implement this through two complementary components—Dstack-\nIngress and Dstack-Gateway—both leveraging our novel Zero Trust TLS (ZT-TLS) protocol.\nThe  fundamental  innovation  in  ZT-TLS  is  establishing  cryptographic  proof  that  a  specific  TLS\ncertificate  (and  therefore  a  domain)  is  exclusively  controlled  by  a  verified  TEE  application.   This\ncreates a verification chain extending from the blockchain to standard HTTPS connections, enabling\nusers to confirm application authenticity through familiar security indicators in their browsers.\n10\nFigure  7:   The  Zero  Trust  TLS  architecture  establishes  a  cryptographically  verifiable  connection  between\nstandard web browsers and TEE applications through blockchain-anchored certificate management.\n2.3.1    Zero Trust TLS Protocol\nThe  ZT-TLS  protocol  addresses  a  critical  challenge:  how  to  cryptographically  bind  a  domain  to  a\nspecific TEE application in a way that prevents unauthorized certificate issuance or domain hijacking.\nOur solution integrates three key components:\n•  TEE-Generated Certificates:  The TEE application (specifically Dstack-Gateway) generates\nits TLS certificate using application secrets derived from Dstack-KMS. This ensures the private\nkey  never  exists  outside  the  TEE  environment  and  creates  a  cryptographic  link  between  the\non-chain governance and the TLS certificate.\n•  Certificate  Authority  Authorization  (CAA):  We  leverage  DNS  CAA  records  to  restrict\nwhich  certificate authorities can  issue certificates  for managed  domains.  By  configuring CAA\nrecords  to  only  authorize  certificates  from  specific  issuers  (which  verify  TEE  attestation),  we\nprevent unauthorized certificate issuance through alternative validation methods.\n•  Certificate Transparency (CT) Monitoring:  To protect against unauthorized DNS record\nmodifications, we implement continuous monitoring of Certificate Transparency logs.  This allows\ndetection of any unauthorized certificates and provides an immutable audit trail of certificate\nissuance history.\n2.3.2    Implementation Components\nWe provide two complementary implementations to accommodate different application requirements:\n•  Dstack-Gateway:  A fully managed reverse proxy running within a TEE that provides imme-\ndiate domain verification with zero application code changes.  Applications register with Dstack-\nGateway through a simple API call, during which Dstack-Gateway verifies the application’s re-\nmote attestation report.  Once verified, applications receive a subdomain under a pre-registered\nwildcard domain (e.g., app-id.Dstack.com), with all TLS termination and certificate manage-\nment handled automatically.\n•  Dstack-Ingress:   A  more  flexible  solution  for  applications  requiring  custom  domain  names.\nDstack-Ingress provides libraries and services that enable applications to manage their own TLS\ncertificates while maintaining the same verification guarantees.  This approach requires minimal\nintegration work while supporting application-specific domain requirements.\n11\nBoth implementations ensure that certificates are cryptographically bound to verified TEE environ-\nments, with the verification chain extending from the blockchain governance contracts through to the\nTLS certificates presented to users’ browsers.\n2.3.3    Security Guarantees and Protections\nOur Verifiable Domain Management system provides several critical security guarantees:\n•  Certificate Provenance Verification:  Users can verify that the TLS certificate presented by\nan application was issued to a legitimate TEE environment by checking the certificate against\non-chain records.\n•  Domain Binding Integrity:  The combination of CAA records and Certificate Transparency\nmonitoring ensures that domains remain bound to their designated TEE applications, preventing\nunauthorized certificate issuance.\n•  Tamper-Evident Certificate Changes:  Any unauthorized attempts to modify domain con-\nfigurations or issue alternative certificates are detected through Certificate Transparency moni-\ntoring, with alerts propagated to clients.\nWhile we cannot technically prevent all attacks against centralized DNS infrastructure, our multi-\nlayered approach creates a tamper-evident system where unauthorized changes are quickly detected\nand rejected by client verification processes.  This approach aligns with the ”Assume Breach” principle\nby implementing defense-in-depth strategies that maintain security even when individual components\nare compromised.\nBy extending the verification chain from blockchain governance through TEE attestation to stan-\ndard TLS certificates, our Verifiable Domain Management system enables seamless integration of Zero\nTrust  applications  into  existing  web  infrastructure.   This  creates  a  practical  path  for  mainstream\nadoption without requiring specialized knowledge or tools from end users, while maintaining the com-\nprehensive security guarantees that define true Zero Trust platforms.\n3    Verifying TEE Applications:  A Practical Walkthrough\nTo demonstrate how Dstack fulfills the Zero Trust principles and addresses the challenges outlined in\nSection 1,  we present a practical end-to-end verification scenario.  This walkthrough illustrates how\nthe architectural components described in Section 2 work together to provide a comprehensive chain\nof trust for real-world Web3 applications.\nTraditional  Zero  Trust  programs  like  smart  contracts  achieve  verifiability  through  transparent\nsource  code  and  inputs.   However,  extending  similar  verifiability  to  real-world  applications  presents\nunique  challenges,  particularly  in  maintaining  privacy  and  compatibility  with  existing  development\npractices.   Dstack  addresses  these  challenges  through  a  comprehensive  verification  framework  that\nrequires minimal code changes.\nThis section demonstrates Dstack’s complete chain of trust through a practical example:  verifying\nthat  a  cryptographic  key  was  genuinely  generated  within  a  TEE  environment.   This  scenario  is  es-\npecially relevant for Web3 and AI Agent applications where cryptographic keys establish application\nidentity and authority.\n3.1    Threat Model\nOur verification framework assumes the correct implementation and integrity of core Dstack compo-\nnents (Dstack-OS, Dstack-KMS, Dstack-Gateway, and governance contracts). While these components’\nsecurity guarantees are detailed in later sections, we explicitly consider developers and administrators\nas potential adversaries.\nPotential attack vectors include:\n•  Application-Level Attacks\n–  Deployment of unauthorized or malicious code through falsified Docker images\n12\n–  Introduction of malicious dependencies through supply chain attacks\n–  Unauthorized application updates that bypass governance controls\n•  Infrastructure-Level Attacks\n–  Tampering with Dstack-OS to circumvent security controls\n–  Deployment of compromised key management services\n–  Operation of unpatched or vulnerable TEE firmware\n–  Execution of applications on non-TEE hardware with spoofed attestation\n•  Network-Level Attacks\n–  DNS hijacking to redirect traffic to unauthorized applications\n–  Man-in-the-middle attacks on communication channels\nDirect attacks on TEE hardware security (e.g., exploitation of hardware vulnerabilities) are con-\nsidered out of scope for this discussion and addressed separately.\n3.2    The Reproducibility Challenge\nA  fundamental  challenge  in  TEE  attestation  lies  in  bridging  the  gap  between  source  code  and  the\nactual  artifacts  (binaries  or  container  images)  running  inside  enclaves.   While  TEE  attestation  can\nprove that a specific artifact runs within a secure environment, it cannot independently verify that the\nartifact accurately represents its claimed source code.\nThis limitation creates several security risks:\n•  Source Code Manipulation:  Developers could intentionally deploy artifacts that differ from\npublicly reviewed source code\n•  Build Process Compromise:  Supply chain attacks could inject malicious code during artifact\ncreation\n•  Toolchain  Vulnerabilities:   As  demonstrated  by  the  Ken  Thompson  Hack,  even  compiler\ntoolchains could be compromised to inject malicious behavior\nTEE  quotes  only  attest  to  measurements  (cryptographic  hashes)  of  running  artifacts.   Without\nguarantees that these artifacts accurately represent reviewed source code, users cannot fully trust ap-\nplications even when running in secure enclaves.  This challenge affects all TEE applications, including\nDstack’s core components.\nFigure 8:  Comprehensive verification chain from source code to running TEE applications\nEstablishing a complete verification chain requires three key elements:\n13\n•  Source Code Verification:  Open-source code or trusted third-party review ensuring no back-\ndoors exist\n•  Build Process Integrity:  Reproducible builds allowing independent verification of artifacts\n•  Runtime Attestation:  TEE quotes proving that verified artifacts are actually running\nTraditional reproducible builds, while ideal, often introduce significant complexity through special-\nized  toolchains  and  build  scripts.   The  following  section  introduces  an  alternative  approach, In-CC\nBuild, that achieves similar guarantees with improved practicality.\n3.3    Dstack Component Verifiability\nEach  core  Dstack  component  implements  specific  verifiability  mechanisms  anchored  in  transparent,\nimmutable records.  Table 1 summarizes these mechanisms:\nComponentSourceBuild MethodRegistryVerification\nDstack-OSOpenReproducibleKmsAuthOS Digest\nDstack-KMSOpenIn-CCKmsAuthImage Hash, Root PubKey\nDstack-GatewayOpenIn-CCAppAuthImage Hash\nTable 1:  Verifiability mechanisms and trust anchors for Dstack components\nAll components maintain open-source codebases with comprehensive documentation. Dstack-OS, as\nthe foundational component, undergoes third-party security audits and implements fully reproducible\nbuilds.\nThe governance smart contracts serve as authoritative registries, anchoring each component’s trust\nbase:\n•  Dstack-OS digests are registered in KmsAuth and managed through multi-signature governance\n•  Dstack-KMS measurements and root public keys are recorded in KmsAuth\n•  Dstack-Gateway artifacts are verified through dedicated AppAuth contracts\nIn-ConfidentialContainer Build    While reproducible builds represent the gold standard for arti-\nfact verification, they often prove impractical for complex applications.  Dstack addresses this through\nIn-CC Build,  leveraging  the  verified  Dstack-OS  as  a  trusted  foundation.   The  In-CC  Build  process\nexecutes entirely within Dstack-OS environment, encompassing code fetching, compilation, and arti-\nfact creation.  By specifying precise source references (e.g., a snapshot of the codebase), the system\nproduces verifiable artifacts with measurements attested in TEE quotes.  This approach minimizes the\ntrusted computing base while eliminating the complexity of traditional reproducible builds.\n3.4    End-to-End Verification Walkthrough\nFrom a user’s perspective, verifying a TEE application in Dstack requires validating a chain of mea-\nsurements against authoritative registries,  encompassing the user application,  runtime data,  Dstack\ncomponents, and network infrastructure.  This section walks through the verification process, demon-\nstrating how each step builds upon the previous one to create a comprehensive chain of trust.\nAs shown in Figure 9, the verification chain begins with the KmsAuth smart contract, which serves\nas the root of trust for the entire system, and concludes with the key generation application running\nin a TEE. We explain the verification steps as follows.\nFirst,  the address of the Dstack-KMS governance contract (i.e.,  KmsAuth) is publicly available.\nThe KMS governance contract serves as the authoritative registry for (1) off-chain KMS nodes and\n(2) dedicated governance contracts (i.e., AppAuth) for TEE applications.  It is worth noting that the\nDstack-Gateway can be regarded as a special TEE application that attests and forwards requests to\nother user applications while maintaining consistent verification procedures.\nThe  KmsAuth  contract  records  both  the  measurements  of  off-chain  KMS  node  programs  (KMS\ndigest, which is the hash of the docker compose file and the images used in In-CC Build) and the TDX\n14\nFigure 9:  The verification chain from authoritative registries to runtime measurements\nQuote of the first KMS node, which acts as the primary key generator.  The identities of subsequent\nKMS  nodes  must  first  be  registered  in  KmsAuth  and  verified  by  the  first  KMS  node  before  they\ncan participate in key generation.  These data, together with the open-source Dstack-KMS codebase,\nallow users to verify the integrity of the KMS nodes and their code correctness.  Subsequently,  the\noff-chain KMS nodes can be considered trusted extensions and used to verify Quotes from other TEE\napplications,  which  cannot  be  achieved  by  the  on-chain  governance  contract  alone.   The  off-chain\nKMS nodes are responsible for generating and managing cryptographic keys (i.e., the root key) and\nthe corresponding certificates (explained in Section 2.3.1), which are further used to authorize TEE\napplications after they are verified, thereby avoiding redundant verification.\nSecond, users can verify the validity of Dstack-Gateway.  By default, this is delegated to the off-\nchain  KMS  nodes  during  gateway  registration,  although  users  can  always  request  the  Quote  of  the\ngateway and check the digest of its docker compose file in its governance contract and the codebase.\nAfter the KMS nodes verify the gateway, it will generate its application root key along with a certificate\nchain ending with the root certificate.\nNext, users can access the TEE application through Dstack-Gateway forwarding.  In this case, users\neffectively delegate the verification of the key generation application to the gateway.  The deployment\nof the key generation application starts from the KmsAuth contract.  The deployer first registers it\nand stores the digest (the hash of the docker compose file and the images) on the dedicated AppAuth\ncontract.  Then, as in the previous step, the off-chain KMS nodes verify the Quote of the application\nafter  it  is  deployed  to  the  TEE  and  ensure  it  matches  the  registered  digest.   Only  after  successful\nverification will the key be generated along with the certificate chain.  To be forwarded by the gateway,\nthe application must also register with it.  In this case, the gateway verifies the application’s certificate\nchain and ensures it shares the same root certificate, indicating authorization by the same KMS.\nFinally, the user can invoke the application and request proof of the key it generated.  The applica-\ntion can generate a Quote on demand, with the generated public key included as custom data in the\nQuote.\n15\n3.5    Security Analysis:  Mitigating Threats\nOur key generation example demonstrates Dstack’s comprehensive approach to security across multiple\nattack surfaces.  At the application level, the system prevents unauthorized code deployment through\nrigorous  measurement  verification  against  the  AppAuth  registry.   The  In-CC  Build  process  ensures\nall dependencies originate from verified sources,  while any updates require new registry entries and\ncomplete re-verification.  It is important to note, however, that code audit and review processes remain\nessential for ensuring application code correctness, as the In-CC Build only guarantees the integrity of\nthe build process.\nInfrastructure security is maintained through multiple mechanisms.  TDX Quotes verify Dstack-OS\nintegrity, preventing OS-level tampering.  KMS updates require multi-signature governance approval,\nsafeguarding against unauthorized changes to key management services.  The Quote verification pro-\ncess  includes  firmware  version  validation,  ensuring  applications  run  on  up-to-date  TEE  hardware.\nHardware-backed TDX Quotes effectively prevent attestation spoofing attempts.\nNetwork-level threats are mitigated through the certificate chain validation system.  This prevents\nboth  DNS  hijacking  and  man-in-the-middle  attacks  by  ensuring  authentic  application  identity  and\nenabling end-to-end encryption with verified certificates.  The combination of these security measures\nensures that cryptographic keys maintain their integrity guarantees even when confronted with sophis-\nticated attacks targeting different system layers.\nReferences\n16"
      }
    ]
  },
  {
    "role": "assistant",
    "content": "# Project Proposal Template\n\n## General Information\n1.1. Name of Project\nDstack\n\n1.2. Project Description (what it does, why it is valuable, origin and history)\nDstack is a developer-friendly and security-first SDK that simplifies the deployment of arbitrary containerized applications into Trusted Execution Environments (TEEs). It enables developers to securely deploy containerized applications in TEEs in minutes using familiar tools like docker-compose.yaml. Dstack provides safe management of secrets and sensitive data, along with built-in TLS termination for exposed services.\n\nThe project was built by Kevin Wang and others from Phala Network, inspired by Andrew Miller (Flashbots & Teleport), and has received contributions from Nethermind and many others. Dstack addresses the gap between raw TEE technology and Zero Trust platform requirements by providing portable confidential containers, decentralized code management, and verifiable domain management.\n\n1.3. How does this project align with the Consortium's Mission Statement\n[blank]\n\n1.4. Project website URL\nhttps://docs.phala.network/dstack/overview (inferred from documentation references)\n\n1.5. Social media accounts\n[blank]\n\n## Legal Information\n2.1. Project Logo URL or attachment (Vector Graphic: SVG, EPS).\n[blank]\n\n2.2. Project license. We recommend an OSI-approved license, so if the license is not one on the list, explain why.\nApache License, Version 2.0\n\n2.3. Existing financial sponsorship.\n[blank]\n\n2.4. Trademark status.\n[blank]\n\n## Technical Information\n3.1. High level assessment of project synergy with existing projects under the CCC, including how the project compliments/overlaps with existing projects, and potential ways to harmonize over time. Responses may be included both inline and/or in accompanying documentation.\n[blank]\n\n3.2. Describe the Trusted Computing Base (TCB) of the project. If the project supports multiple environments please describe each TCB. Also identify if dependencies of other project (both CCC or non-CCC) TCBs are taken.\nDstack's TCB includes:\n- Dstack-OS: A minimized operating system image that serves as a hardware abstraction layer\n- OVMF (Open Virtual Machine Firmware): Configures VM hardware specifications\n- Linux kernel with initial ramdisk (initrd)\n- Root filesystem with essential system libraries and tools\n- Intel TDX or equivalent TEE hardware as the foundation\n\nThe system establishes a secure and verifiable startup chain from TEE hardware through to user applications, with each component measuring the next and recording measurements in hardware registers that are incorporated into TEE attestation reports.\n\n3.3. Project Code of Conduct URL. We recommend a Contributor Covenant v2.0 based Code of Conduct, so if the Code of Conduct is not based on that, explain why.\n[blank]\n\n3.4. Source control URL\nhttps://github.com/Dstack-TEE/dstack\n\n3.5. Issue tracker URL\nhttps://github.com/Dstack-TEE/dstack/issues (inferred)\n\n3.6. External dependencies (including licenses, and indicate whether each is a build time or runtime dependency)\n- Intel TDX or equivalent TEE hardware (runtime)\n- Linux kernel (runtime)\n- Docker/container runtime (runtime)\n- Busybox (runtime)\n- LUKS for encryption (runtime)\n- Wireguard-tools (build time)\n- Build-essential, chrpath, diffstat, lz4, xorriso (build time)\n- Rust (build time)\n\n3.7. Standards implemented by the project, if any. Include links to any such standards.\n- TLS/HTTPS for secure communications\n- Certificate Transparency (CT) for certificate monitoring\n- Certificate Authority Authorization (CAA) for domain security\n- Remote Attestation for TEE verification\n\n3.8. Release methodology and mechanics\n[blank]\n\n3.9. Names of initial committers, if different from those submitting proposal\nInitial committers include:\n- Kevin Wang (kvinwang)\n- Shelven Zhou (shelvenzhou)\n- Leechael\n\n3.10. List of project's official communication channels (slack, irc, mailing lists)\n[blank]\n\n3.11. Project Security Response Policy\n[blank]\n\n3.12. Preferred maturity level (Incubation, Graduation, or Emeritus)\n[blank]\n\n3.13. Any additional information the TAC and Board should take into consideration when reviewing your proposal.\nDstack includes several key components:\n- dstack-vmm: Service running on bare TDX host to manage CVMs\n- dstack-gateway: Reverse proxy to forward TLS connections to CVMs\n- dstack-kms: KMS server to generate keys for CVMs\n- dstack-guest-agent: Service in CVM to serve containers' key derivation and attestation requests\n- meta-dstack: Yocto meta layer to build CVM guest images\n\nThe project provides innovative solutions for portable confidential containers, decentralized code management, and verifiable domain management, addressing critical limitations in current TEE implementations for Web3 contexts."
  },
  {
    "role": "user",
    "content": "This is the Mission Statement, fill in 1.3 with it\n\n```\nThe purpose of the Confidential Computing Consortium is to raise, budget and spend funds in support of various open source and/or open standards projects relating to:\n\ndefining confidential computing and accelerating acceptance and adoption in the market.\ndeveloping open enterprise-grade building blocks (e.g., open specifications and open source licensed projects), including a Confidential Computing portfolio and development experience, to enable easy development and management of enterprise-grade Confidential Computing applications, and\ndefining foundational services and frameworks that are Confidential Computing aware and minimize the need for trust.\n```"
  }
]

Response:

## General Information 1.3. How does this project align with the Consortium's Mission Statement Dstack directly aligns with the Confidential Computing Consortium's mission by providing enterprise-grade building blocks for confidential computing applications. It accelerates adoption by making TEE deployment developer-friendly through familiar tools like docker-compose, lowering the barrier to entry. Dstack defines foundational services and frameworks that are Confidential Computing aware through its comprehensive architecture (Dstack-OS, Dstack-KMS, Dstack-Gateway). The project minimizes the need for trust by implementing Zero Trust principles with portable confidential containers, decentralized code management, and verifiable domain management. By enabling seamless deployment of containerized applications in TEEs, Dstack contributes significantly to the development experience and practical adoption of confidential computing in real-world scenarios.

Model: claude-3-7-sonnet-202502192025-06-25 13:03:39

Context:

[
  {
    "role": "user",
    "content": "翻译成中文 Expose services via built-in TLS termination\n"
  },
  {
    "role": "assistant",
    "content": "通过内置的 TLS 终止暴露服务"
  },
  {
    "role": "user",
    "content": "这里termination应该用的不对"
  },
  {
    "role": "assistant",
    "content": "您是对的，我的翻译不够准确。在网络和安全语境中，\"TLS termination\"通常翻译为\"TLS 卸载\"或\"TLS 终结\"，表示在某处结束加密连接并处理解密过程。\n\n更准确的翻译应为：\n\n通过内置的 TLS 卸载暴露服务\n\n或\n\n通过内置的 TLS 终结暴露服务"
  },
  {
    "role": "user",
    "content": "换回英语"
  }
]

Response:

Expose services via built-in TLS termination

Model: claude-3-7-sonnet-202502192025-06-25 13:03:24

Context:

[
  {
    "role": "user",
    "content": "翻译成中文 Expose services via built-in TLS termination\n"
  },
  {
    "role": "assistant",
    "content": "通过内置的 TLS 终止暴露服务"
  },
  {
    "role": "user",
    "content": "这里termination应该用的不对"
  }
]

Response:

您是对的，我的翻译不够准确。在网络和安全语境中，"TLS termination"通常翻译为"TLS 卸载"或"TLS 终结"，表示在某处结束加密连接并处理解密过程。更准确的翻译应为：通过内置的 TLS 卸载暴露服务或通过内置的 TLS 终结暴露服务

Model: gpt-4o-mini-2024-07-182025-06-25 13:02:57

Context:

[
  {
    "role": "system",
    "content": "You are an assistant who is good at conversation. You need to summarize the user's conversation into a title of 10 characters or less. It should be in the format of \"Action - Title\". Some examples:\n1. Learn - Bitcoin 2. Code - Web Server 3. Write - An Article"
  },
  {
    "role": "user",
    "content": "User: 翻译成中文 Expose services via built-in TLS termination\n\nAssistant: 通过内置的 TLS 终止暴露服务"
  }
]

Response:

Translate - TLS Termination

Model: claude-3-7-sonnet-202502192025-06-25 13:02:56

Context:

[
  {
    "role": "user",
    "content": "翻译成中文 Expose services via built-in TLS termination\n"
  }
]

Response:

通过内置的 TLS 终止暴露服务

Model: gpt-4o-mini-2024-07-182025-06-25 12:57:38

Context:

[
{
"role": "system",
"content": "You are an assistant who is good at conversation. You need to summarize the user's conversation into a title of 10 characters or less. It should be in the format of \"Action - Title\". Some examples:\n1. Learn - Bitcoin 2. Code - Web Server 3. Write - An Article"
},
{
"role": "user",
"content": "User: Help me fill in the follow template given the project whitepaper and README file.\n\nFor fields with not enough info, leave it \"[blank]\".\n\n```\nProject Proposal Template\n\nGeneral Information\n1.1. Name of Project\n1.2. Project Description (what it does, why it is valuable, origin and history)\n1.3. How does this project align with the Consortium's Mission Statement\n1.4. Project website URL\n1.5. Social media accounts\n\nLegal Information\n2.1. Project Logo URL or attachment (Vector Graphic: SVG, EPS).\n2.2. Project license. We recommend an OSI-approved license, so if the license is not one on the list, explain why.\n2.3. Existing financial sponsorship.\n2.4. Trademark status.\n\nTechnical Information\n3.1. High level assessment of project synergy with existing projects under the CCC, including how the project compliments/overlaps with existing projects, and potential ways to harmonize over time. Responses may be included both inline and/or in accompanying documentation.\n3.2. Describe the Trusted Computing Base (TCB) of the project. If the project supports multiple environments please describe each TCB. Also identify if dependencies of other project (both CCC or non-CCC) TCBs are taken.\n3.3. Project Code of Conduct URL. We recommend a Contributor Covenant v2.0 based Code of Conduct, so if the Code of Conduct is not based on that, explain why.\n3.4. Source control URL\n3.5. Issue tracker URL\n3.6. External dependencies (including licenses, and indicate whether each is a build time or runtime dependency)\n3.7. Standards implemented by the project, if any. Include links to any such standards.\n3.8. Release methodology and mechanics\n3.9. Names of initial committers, if different from those submitting proposal\n3.10. List of project's official communication channels (slack, irc, mailing lists)\n3.11. Project Security Response Policy\n3.12. Preferred maturity level (Incubation, Graduation, or Emeritus) 3.13. Any additional information the TAC and Board should take into consideration when reviewing your proposal.\n```\nAssistant: # Project Proposal Template\n\n## General Information\n1.1. Name of Project\nDstack\n\n1.2. Project Description (what it does, why it is valuable, origin and history)\nDstack is a developer-friendly and security-first SDK that simplifies the deployment of arbitrary containerized applications into Trusted Execution Environments (TEEs). It enables developers to securely deploy containerized applications in TEEs in minutes using familiar tools like docker-compose.yaml. Dstack provides safe management of secrets and sensitive data, along with built-in TLS termination for exposed services.\n\nThe project was built by Kevin Wang and others from Phala Network, inspired by Andrew Miller (Flashbots & Teleport), and has received contributions from Nethermind and many others. Dstack addresses the gap between raw TEE technology and Zero Trust platform requirements by providing portable confidential containers, decentralized code management, and verifiable domain management.\n\n1.3. How does this project align with the Consortium's Mission Statement\n[blank]\n\n1.4. Project website URL\nhttps://docs.phala.network/dstack/overview (inferred from documentation references)\n\n1.5. Social media accounts\n[blank]\n\n## Legal Information\n2.1. Project Logo URL or attachment (Vector Graphic: SVG, EPS).\n[blank]\n\n2.2. Project license. We recommend an OSI-approved license, so if the license is not one on the list, explain why.\nApache License, Version 2.0\n\n2.3. Existing financial sponsorship.\n[blank]\n\n2.4. Trademark status.\n[blank]\n\n## Technical Information\n3.1. High level assessment of project synergy with existing projects under the CCC, including how the project compliments/overlaps with existing projects, and potential ways to harmonize over time. Responses may be included both inline and/or in accompanying documentation.\n[blank]\n\n3.2. Describe the Trusted Computing Base (TCB) of the project. If the project supports multiple environments please describe each TCB. Also identify if dependencies of other project (both CCC or non-CCC) TCBs are taken.\nDstack's TCB includes:\n- Dstack-OS: A minimized operating system image that serves as a hardware abstraction layer\n- OVMF (Open Virtual Machine Firmware): Configures VM hardware specifications\n- Linux kernel with initial ramdisk (initrd)\n- Root filesystem with essential system libraries and tools\n- Intel TDX or equivalent TEE hardware as the foundation\n\nThe system establishes a secure and verifiable startup chain from TEE hardware through to user applications, with each component measuring the next and recording measurements in hardware registers that are incorporated into TEE attestation reports.\n\n3.3. Project Code of Conduct URL. We recommend a Contributor Covenant v2.0 based Code of Conduct, so if the Code of Conduct is not based on that, explain why.\n[blank]\n\n3.4. Source control URL\nhttps://github.com/Dstack-TEE/dstack\n\n3.5. Issue tracker URL\nhttps://github.com/Dstack-TEE/dstack/issues (inferred)\n\n3.6. External dependencies (including licenses, and indicate whether each is a build time or runtime dependency)\n- Intel TDX or equivalent TEE hardware (runtime)\n- Linux kernel (runtime)\n- Docker/container runtime (runtime)\n- Busybox (runtime)\n- LUKS for encryption (runtime)\n- Wireguard-tools (build time)\n- Build-essential, chrpath, diffstat, lz4, xorriso (build time)\n- Rust (build time)\n\n3.7. Standards implemented by the project, if any. Include links to any such standards.\n- TLS/HTTPS for secure communications\n- Certificate Transparency (CT) for certificate monitoring\n- Certificate Authority Authorization (CAA) for domain security\n- Remote Attestation for TEE verification\n\n3.8. Release methodology and mechanics\n[blank]\n\n3.9. Names of initial committers, if different from those submitting proposal\nInitial committers include:\n- Kevin Wang (kvinwang)\n- Shelven Zhou (shelvenzhou)\n- Leechael\n\n3.10. List of project's official communication channels (slack, irc, mailing lists)\n[blank]\n\n3.11. Project Security Response Policy\n[blank]\n\n3.12. Preferred maturity level (Incubation, Graduation, or Emeritus)\n[blank]\n\n3.13. Any additional information the TAC and Board should take into consideration when reviewing your proposal.\nDstack includes several key components:\n- dstack-vmm: Service running on bare TDX host to manage CVMs\n- dstack-gateway: Reverse proxy to forward TLS connections to CVMs\n- dstack-kms: KMS server to generate keys for CVMs\n- dstack-guest-agent: Service in CVM to serve containers' key derivation and attestation requests\n- meta-dstack: Yocto meta layer to build CVM guest images\n\nThe project provides innovative solutions for portable confidential containers, decentralized code management, and verifiable domain management, addressing critical limitations in current TEE implementations for Web3 contexts."
}
]

Response:

Fill - Proposal

Model: claude-3-7-sonnet-202502192025-06-25 12:57:37

Context:

[
  {
    "role": "user",
    "content": [
      {
        "type": "text",
        "text": "Help me fill in the follow template given the project whitepaper and README file.\n\nFor fields with not enough info, leave it \"[blank]\".\n\n```\nProject Proposal Template\n\nGeneral Information\n1.1. Name of Project\n1.2. Project Description (what it does, why it is valuable, origin and history)\n1.3. How does this project align with the Consortium's Mission Statement\n1.4. Project website URL\n1.5. Social media accounts\n\nLegal Information\n2.1. Project Logo URL or attachment (Vector Graphic: SVG, EPS).\n2.2. Project license. We recommend an OSI-approved license, so if the license is not one on the list, explain why.\n2.3. Existing financial sponsorship.\n2.4. Trademark status.\n\nTechnical Information\n3.1. High level assessment of project synergy with existing projects under the CCC, including how the project compliments/overlaps with existing projects, and potential ways to harmonize over time. Responses may be included both inline and/or in accompanying documentation.\n3.2. Describe the Trusted Computing Base (TCB) of the project. If the project supports multiple environments please describe each TCB. Also identify if dependencies of other project (both CCC or non-CCC) TCBs are taken.\n3.3. Project Code of Conduct URL. We recommend a Contributor Covenant v2.0 based Code of Conduct, so if the Code of Conduct is not based on that, explain why.\n3.4. Source control URL\n3.5. Issue tracker URL\n3.6. External dependencies (including licenses, and indicate whether each is a build time or runtime dependency)\n3.7. Standards implemented by the project, if any. Include links to any such standards.\n3.8. Release methodology and mechanics\n3.9. Names of initial committers, if different from those submitting proposal\n3.10. List of project's official communication channels (slack, irc, mailing lists)\n3.11. Project Security Response Policy\n3.12. Preferred maturity level (Incubation, Graduation, or Emeritus) 3.13. Any additional information the TAC and Board should take into consideration when reviewing your proposal.\n```"
      },
      {
        "type": "text",
        "text": "README.md\n# Dstack\n\n[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/Dstack-TEE/dstack)\n\nDstack is a **developer friendly** and **security first** SDK to simplify the deployment of arbitrary containerized apps into TEE.\n\nMain features:\n\n- 🔒 Deploy containerized apps securely in TEE in minutes\n- 🛠️ Use familiar tools - just write a docker-compose.yaml\n- 🔑 Safely manage secrets and sensitive data\n- 📡 Expose services via built-in TLS termination\n\nDstack is community driven. Open sourced and built by [Kevin Wang](https://github.com/kvinwang) and many others from [Phala Network](https://github.com/Phala-Network), inspired by [Andrew Miller](https://github.com/amiller) (Flashbots & Teleport), and contributed by [Nethermind](https://github.com/NethermindEth/nethermind) and [many others](#contributors).\n\n![Alt](https://repobeats.axiom.co/api/embed/0a001cc3c1f387fae08172a9e116b0ec367b8971.svg \"Repobeats analytics image\")\n\n# Overview\n\nComponents in Dstack:\n\n- `dstack-vmm`: A service running in bare TDX host to manage CVMs\n- `dstack-gateway`: A reverse proxy to forward TLS connections to CVMs\n- `dstack-kms`: A KMS server to generate keys for CVMs\n- `dstack-guest-agent`: A service running in CVM to serve containers' key derivation and attestation requests\n- `meta-dstack`: A Yocto meta layer to build CVM guest images\n\nThe overall architecture is shown below:\n![arch](./docs/assets/arch.png)\n\n# Directory structure\n\n```text\ndstack/\n    kms/                         A prototype KMS server\n    guest-agent/                 A service running in CVM to serve containers' key derivation and attestation requests.\n    dstack-util/                 A CLI tool in the guest setting up the system, getting TDX quote, extending RTMR, generating cert for RA-TLS, etc.\n    vmm/                         A service running in bare TDX host to manage CVMs\n    gateway/                     A reverse proxy to forward TLS connections to CVMs\n    certbot/                     A tool to automatically obtain and renew TLS certificates for dstack-gateway\n    ra-rpc/                      RA-TLS support for pRPC\n    ra-tls/                      RA-TLS support library\n    tdx-attest/                  Guest library for getting TDX quote and extending RTMR\n```\n\n# Build and play locally\n\n## Prerequisites\n\n- A bare metal TDX server setup following [canonical/tdx](https://github.com/canonical/tdx)\n- Public IPv4 address assigned to the machine\n- At least 16GB RAM, 100GB free disk space.\n- A domain with DNS access if you want to set up `dstack-gateway` for Zero Trust HTTPS\n\n> [!NOTE]\n>\n> This doc assumes you have access to a compatible Intel TDX Server ready to be configured with Dstack. Check the [Hardware Requirements](https://docs.phala.network/dstack/hardware-requirements) for more information on buying a bare metal server or renting a server from OVH. To start learning about Dstack check out the [docs](https://docs.phala.network/dstack/overview).\n>\n> If you are looking to deploy a CVM in minutes, go to the docs to learn how to [sign-up for a Phala Cloud Account](https://docs.phala.network/phala-cloud/getting-started/sign-up-for-cloud-account) and [deploy your first CVM on Dstack]((https://docs.phala.network/phala-cloud/getting-started/start-from-cloud-ui)).\n\n## Install dependencies\n\n```bash\n# for Ubuntu 24.04\nsudo apt install -y build-essential chrpath diffstat lz4 wireguard-tools xorriso\n# install rust\ncurl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh\n```\n\n## Build and run for local development\n\n### Build the artifacts\n```bash\ngit clone https://github.com/Dstack-TEE/meta-dstack.git --recursive\ncd meta-dstack/\n\nmkdir build\ncd build\n../build.sh hostcfg\n# This outputs the following message:\n# Config file ../build-config.sh created, please edit it to configure the build\n\nvim ./build-config.sh\n```\n\nReview and customize the `build-config.sh` configuration file according to your environment requirements. The file contains network ports, domain settings, and other important parameters. Once configured, run the build script again to generate the necessary artifacts:\n\n```bash\n../build.sh hostcfg\n\n# If everything is okay, you should see the built artifacts in the `build` directory.\n$ ls\ncerts  images  dstack-kms  kms.toml  run  dstack-vmm  vmm.toml  dstack-gateway  gateway.toml\n```\n\n### Download guest image or build guest image from source\n\n```bash\n# This will download the guest image from the release page.\n../build.sh dl 0.5.2\n```\n\nOr build guest image from source:\n\n```bash\n# This will build the guest image from source using the yocto meta layer. This will take a while.\n../build.sh guest\n```\n\n> **Note on Reproducible Builds**: The build command above does not guarantee reproducibility. For reproducible builds across different build environments, please refer to the [reproducible build instructions](https://github.com/Dstack-TEE/meta-dstack?tab=readme-ov-file#reproducible-build-the-guest-image) in the meta-dstack repository.\n\n### Run components\nNow you can open 3 terminals to start the components:\n\n1. Run `./dstack-kms -c kms.toml`\n2. Run `sudo ./dstack-gateway -c gateway.toml`\n3. Run `./dstack-vmm -c vmm.toml`\n\n⚠️ *Warning: this is for local development, and the kms is not secure, so you should not use it in production.*\nFor production, you should follow the [deployment guide](./docs/deployment.md) and read the [security guide](./docs/security-guide/security-guide.md).\n\n## Deploy an App\nOpen the dstack-vmm webpage [http://localhost:9080](http://localhost:9080)(change the port according to your configuration) on your local machine to deploy a `docker-compose.yaml` file:\n\n![vmm](./docs/assets/vmm.png)\n\nAfter the container deployed, it should need some time to start the CVM and the containers. Time would be vary depending on your workload.\n\n- Click the [Logs] button to see the logs of the CVM, you can see if the container is finished starting there.\n\n- Once the container is running, you can click the [Dashboard] button to see some information of the container. And the logs of the containers can be seen in the [Dashboard] page.\n\n    ![dstack-guest-agent](./docs/assets/guest-agent.png)\n\n- You can open dstack-gateway's dashboard at [https://localhost:9070](https://localhost:9070) to see the CVM's wireguard ip address, as shown below:\n\n![dstack-gateway](./docs/assets/gateway.png)\n\n## Pass Secrets to Apps\nWhen deploying a new App, you can pass private data via Encrypted Environment Variables. These variables can be referenced in the docker-compose.yaml file as shown below:\n\n![secret](./docs/assets/secret.png)\n\nThe environment variables will be encrypted in the client-side and decrypted in the CVM before being passed to the containers.\n\n## Access the App\n\nOnce the app is deployed and listening on an HTTP port, you can access the HTTP service via dstack-gateway's public domain. The ingress mapping rules are:\n\n- `<id>[s].<base_domain>` maps to port `80` or `443` if with `s` in the CVM.\n- `<id>-<port>[s].<base_domain>` maps to port `<port>` in the CVM.\n\nFor example, `3327603e03f5bd1f830812ca4a789277fc31f577-8080.app.kvin.wang` maps to port `8080` in the CVM.\n\nWhere the `<id>` can be either the app id or the instance id. If the app id is used, one of the instances will be selected by the load balancer.\nIf the `id-port` part ends with `s`, it means the TLS connection will be passthrough to the app rather than terminating at dstack-gateway.\n\nYou can also ssh into the CVM to inspect more information, if your deployment uses the image `dstack-x.x.x-dev`:\n\n```bash\n# The IP address of the CVM can be found in the dstack-gateway dashboard.\nssh [email protected]\n```\n\n## Getting TDX quote in docker container\n\nTo get a TDX quote within app containers:\n\n1. Mount `/var/run/dstack.sock` to the target container in `docker-compose.yaml`\n\n    ```yaml\n    version: '3'\n    services:\n    nginx:\n        image: nginx:latest\n        volumes:\n        - /var/run/dstack.sock:/var/run/dstack.sock\n        ports:\n        - \"8080:80\"\n        restart: always\n    ```\n\n2. Execute the quote request command in the container.\n\n    ```bash\n    # The argument report_data accepts binary data encoding in hex string.\n    # The actual report_data passing the to the underlying TDX driver is sha2_256(report_data).\n    curl --unix-socket /var/run/dstack.sock http://localhost/GetQuote?report_data=0x1234deadbeef | jq .  \n    ```\n\n## Container logs\n\nContainer logs can be obtained from the CVM's `dashboard` page or by curl:\n\n```bash\ncurl 'http://<appid>.app.kvin.wang:9090/logs/<container name>?since=0&until=0&follow=true&text=true&timestamps=true&bare=true'\n```\n\nReplace `<appid>` and `<container name>` with actual values. Available parameters:\n\n- since=0: Starting Unix timestamp for log retrieval\n- until=0: Ending Unix timestamp for log retrieval\n- follow: Enables continuous log streaming\n- text: Returns human-readable text instead of base64 encoding\n- timestamps: Adds timestamps to each log line\n- bare: Returns the raw log lines without json format\n\nThe response of the RPC looks like:\n```\n$ curl 'http://0.0.0.0:9190/logs/zk-provider-server?text&timestamps'\n{\"channel\":\"stdout\",\"message\":\"2024-09-29T03:05:45.209507046Z Initializing Rust backend...\\n\"}\n{\"channel\":\"stdout\",\"message\":\"2024-09-29T03:05:45.209543047Z Calling Rust function: init\\n\"}\n{\"channel\":\"stdout\",\"message\":\"2024-09-29T03:05:45.209544957Z [2024-09-29T03:05:44Z INFO  rust_prover] Initializing...\\n\"}\n{\"channel\":\"stdout\",\"message\":\"2024-09-29T03:05:45.209546381Z [2024-09-29T03:05:44Z INFO  rust_prover::groth16] Starting setup process\\n\"}\n```\n\n## TLS Passthrough with Custom Domain\n\ndstack-gateway supports TLS passthrough for custom domains.\n\nSee the example [here](https://github.com/Dstack-TEE/dstack-examples/tree/main/custom-domain/dstack-ingress) for more details.\n\n## Upgrade an App\n\nGot to the dstack-vmm webpage, click the [Upgrade] button, select or paste the compose file you want to upgrade to, and click the [Upgrade] button again.\nThe app id does not change after the upgrade. Stop and start the app to apply the upgrade.\n\n## HTTPS Certificate Transparency\n\nIn the tutorial above, we used a TLS certificate with a private key external to the TEE. To establish trust, we need to generate and maintain the certificate's private key within the TEE and provide evidence that all TLS certificates for the domain were originate solely from dstack-gateway CVM.\n\nBy combining Certificate Transparency Logs and CAA DNS records, we can make best effort to minimize security risks. Here's our approach:\n\n- Set CAA records to allow only the account created in dstack-gateway CVM to request Certificates.\n- Launch a program to monitor Certificate Transparency Log and give alarm once any certificate issued to a pubkey that isn’t generated by dstack-gateway CVM.\n\n### Configurations\n\nTo launch Certbot, you need to own a domain hosted on Cloudflare. Obtain an API token with DNS operation permissions from the Cloudflare dashboard. Configure it in the `build-config.sh`:\n\n```bash\n# The directory to store the auto obtained TLS certificate and key\nGATEWAY_CERT=${CERBOT_WORKDIR}/live/cert.pem\nGATEWAY_KEY=${CERBOT_WORKDIR}/live/key.pem\n\n# for certbot\nCF_ZONE_ID=cc0a40...\nCF_API_TOKEN=g-DwMH...\n# ACME_URL=https://acme-v02.api.letsencrypt.org/directory\nACME_URL=https://acme-staging-v02.api.letsencrypt.org/directory\n```\n\nThen re-run the ../build.sh:\n\n```bash\n../build.sh\n```\n\n### Launch certbot\n\nThen run the certbot in the `build/` and you will see the following log:\n```text\n$ RUST_LOG=info,certbot=debug ./certbot renew -c certbot.toml\n2024-10-25T07:41:00.682990Z  INFO certbot::bot: creating new ACME account\n2024-10-25T07:41:00.869246Z  INFO certbot::bot: created new ACME account: https://acme-staging-v02.api.letsencrypt.org/acme/acct/168601853\n2024-10-25T07:41:00.869270Z  INFO certbot::bot: setting CAA records\n2024-10-25T07:41:00.869276Z DEBUG certbot::acme_client: setting guard CAA records for app.kvin.wang\n2024-10-25T07:41:01.740767Z DEBUG certbot::acme_client: removing existing CAA record app.kvin.wang 0 issuewild \"letsencrypt.org;validationmethods=dns-01;accounturi=https://acme-staging-v02.api.letsencrypt.org/acme/acct/168578683\"\n2024-10-25T07:41:01.991298Z DEBUG certbot::acme_client: removing existing CAA record app.kvin.wang 0 issue \"letsencrypt.org;validationmethods=dns-01;accounturi=https://acme-staging-v02.api.letsencrypt.org/acme/acct/168578683\"\n2024-10-25T07:41:02.216751Z DEBUG certbot::acme_client: setting CAA records for app.kvin.wang, 0 issue \"letsencrypt.org;validationmethods=dns-01;accounturi=https://acme-staging-v02.api.letsencrypt.org/acme/acct/168601853\"\n2024-10-25T07:41:02.424217Z DEBUG certbot::acme_client: setting CAA records for app.kvin.wang, 0 issuewild \"letsencrypt.org;validationmethods=dns-01;accounturi=https://acme-staging-v02.api.letsencrypt.org/acme/acct/168601853\"\n2024-10-25T07:41:02.663824Z DEBUG certbot::acme_client: removing guard CAA records for app.kvin.wang\n2024-10-25T07:41:03.095564Z DEBUG certbot::acme_client: generating new cert key pair\n2024-10-25T07:41:03.095678Z DEBUG certbot::acme_client: requesting new certificates for *.app.kvin.wang\n2024-10-25T07:41:03.095699Z DEBUG certbot::acme_client: creating new order\n2024-10-25T07:41:03.250382Z DEBUG certbot::acme_client: order is pending, waiting for authorization\n2024-10-25T07:41:03.283600Z DEBUG certbot::acme_client: creating dns record for app.kvin.wang\n2024-10-25T07:41:04.027882Z DEBUG certbot::acme_client: challenge not found, waiting 500ms tries=2 domain=\"_acme-challenge.app.kvin.wang\"\n2024-10-25T07:41:04.600711Z DEBUG certbot::acme_client: challenge not found, waiting 1s tries=3 domain=\"_acme-challenge.app.kvin.wang\"\n2024-10-25T07:41:05.642300Z DEBUG certbot::acme_client: challenge not found, waiting 2s tries=4 domain=\"_acme-challenge.app.kvin.wang\"\n2024-10-25T07:41:07.715947Z DEBUG certbot::acme_client: challenge not found, waiting 4s tries=5 domain=\"_acme-challenge.app.kvin.wang\"\n2024-10-25T07:41:11.724831Z DEBUG certbot::acme_client: challenge not found, waiting 8s tries=6 domain=\"_acme-challenge.app.kvin.wang\"\n2024-10-25T07:41:19.815990Z DEBUG certbot::acme_client: challenge not found, waiting 16s tries=7 domain=\"_acme-challenge.app.kvin.wang\"\n2024-10-25T07:41:35.852790Z DEBUG certbot::acme_client: setting challenge ready for https://acme-staging-v02.api.letsencrypt.org/acme/chall-v3/14584884443/mQ-I2A\n2024-10-25T07:41:35.934425Z DEBUG certbot::acme_client: challenges are ready, waiting for order to be ready\n2024-10-25T07:41:37.972434Z DEBUG certbot::acme_client: order is ready, uploading csr\n2024-10-25T07:41:38.052901Z DEBUG certbot::acme_client: order is processing, waiting for challenge to be accepted\n2024-10-25T07:41:40.088190Z DEBUG certbot::acme_client: order is valid, getting certificate\n2024-10-25T07:41:40.125988Z DEBUG certbot::acme_client: removing dns record 6ab5724e8fa7e3e8f14e93333a98866a\n2024-10-25T07:41:40.377379Z DEBUG certbot::acme_client: stored new cert in /home/kvin/codes/meta-dstack/dstack/build/run/certbot/backup/2024-10-25T07:41:40.377174477Z\n2024-10-25T07:41:40.377472Z  INFO certbot::bot: checking if certificate needs to be renewed\n2024-10-25T07:41:40.377719Z DEBUG certbot::acme_client: will expire in Duration { seconds: 7772486, nanoseconds: 622281542 }\n2024-10-25T07:41:40.377752Z  INFO certbot::bot: certificate /home/kvin/codes/meta-dstack/dstack/build/run/certbot/live/cert.pem is up to date\n```\n\nWhere the command did are:\n\n- Registered to letsencrypt and got a new account `https://acme-staging-v02.api.letsencrypt.org/acme/acct/168601853`\n- Auto set CAA records for the domain on cloudflare, you can open the CF dashboard to see the record:\n\n    ![certbot-caa](./docs/assets/certbot-caa.png)\n\n- Auto requested a new certificate from Let's Encrypt. Automatically renews the certificate to maintain its validity\n\n### Launch dstack-gateway\n\nExecute dstack-gateway with `sudo ./dstack-gateway -c gateway.toml`, then access the web portal to check the dstack-gateway CVM managed Let's Encrypt account. The account's private key remains securely sealed within the TEE.\n\n![gateway-accountid](./docs/assets/gateway-accountid.png)\n\n## Certificate transparency log monitor\n\nTo enhance security, we've limited TLS certificate issuance to dstack-gateway via CAA records. However, since these records can be modified through Cloudflare's domain management, we need to implement global CA certificate monitoring to maintain security oversight.\n\n`ct_monitor` tracks Certificate Transparency logs via [https://crt.sh](https://crt.sh/?q=app.kvin.wang), comparing their public key with the ones got from dstack-gateway RPC. It immediately alerts when detecting unauthorized certificates not issued through dstack-gateway:\n\n```text\n$ ./ct_monitor -t https://localhost:9010/prpc -d app.kvin.wang\n2024-10-25T08:12:11.366463Z  INFO ct_monitor: monitoring app.kvin.wang...\n2024-10-25T08:12:11.366488Z  INFO ct_monitor: fetching known public keys from https://localhost:9010/prpc\n2024-10-25T08:12:11.566222Z  INFO ct_monitor: got 2 known public keys\n2024-10-25T08:12:13.142122Z  INFO ct_monitor: ✅ checked log id=14705660685\n2024-10-25T08:12:13.802573Z  INFO ct_monitor: ✅ checked log id=14705656674\n2024-10-25T08:12:14.494944Z ERROR ct_monitor: ❌ error in CTLog { id: 14666084839, issuer_ca_id: 295815, issuer_name: \"C=US, O=Let's Encrypt, CN=R11\", common_name: \"kvin.wang\", name_value: \"*.app.kvin.wang\", not_before: \"2024-09-24T02:23:15\", not_after: \"2024-12-23T02:23:14\", serial_number: \"03ae796f56a933c8ff7e32c7c0d662a253d4\", result_count: 1, entry_timestamp: \"2024-09-24T03:21:45.825\" }\n2024-10-25T08:12:14.494998Z ERROR ct_monitor: error: certificate has issued to unknown pubkey: 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\n```\n\n# Troubleshooting\n\n### Error from dstack-vmm: qemu-system-x86_64: -device vhost-vsock-pci,guest-cid=<id>: vhost-vsock: unable to set guest cid: Address already in use\n\n`dstack-vmm` may throw this error when creating a new VM if the [Unix Socket CID](https://man7.org/linux/man-pages/man7/vsock.7.html) is occupied. To solve the problem, first, you should list the occupied CID:\n\n```bash\nps aux | grep 'guest-cid='\n```\n\nThen choose a new range of the CID not conflicting with the CID in use. You can change `build/vmm.toml` file and restart `dstack-vmm`. This error should disappear. For example, you may find 33000-34000 free to use:\n\n```toml\n[cvm]\ncid_start = 33000\ncid_pool_size = 1000\n```\n\nWhen building the dstack from scratch, you should change the CID configs in `build-config.sh` instead, because `vmm.toml` file is generated by `build.sh`. Its content is derived from `build-config.sh`.\n\nYou may encounter this problem when upgrading from an older version of dstack, because CID was introduced in `build-config.sh` in later versions. In such case, please follow the docs to add the missing entries in `build-config.sh` and rebuild dstack.\n\n### Error: Operation not permitted when building guest image\n\nWhen running `../build.sh guest`, you might encounter this error:\n\n```\nTraceback (most recent call last):\n  File \"/meta-dstack/poky/bitbake/bin/bitbake-worker\", line 278, in child\n    bb.utils.disable_network(uid, gid)\n  File \"/meta-dstack/poky/bitbake/lib/bb/utils.py\", line 1696, in disable_network\n    with open(\"/proc/self/uid_map\", \"w\") as f:\nPermissionError: [Errno 1] Operation not permitted\n```\n\nThis error occurs because Ubuntu 23.10 and later versions restrict unprivileged user namespaces by default. To fix this, run:\n\n```bash\nsudo sysctl kernel.apparmor_restrict_unprivileged_userns=0\n```\n\nThen try building again. For more information about this restriction, see the [Ubuntu discourse post](https://discourse.ubuntu.com/t/spec-unprivileged-user-namespace-restrictions-via-apparmor-in-ubuntu-23-10/37626).\n\n\n# Contributors\n\nDstack is proudly built by open source and Pi-rateship contributors:\n\n- Phala Network: [Kevin Wang](https://github.com/kvinwang), [Shelven Zhou](https://github.com/shelvenzhou), [Leechael](https://github.com/leechael)\n- Teleport: [Andrew Miller](https://github.com/amiller), [Sxy Sun](https://github.com/sxysun)\n- Flashbots: [Tina](https://github.com/CarboClanC), [Mateusz](https://github.com/Ruteri), [Dmarz](https://github.com/dmarzzz), [Moe](https://github.com/MoeMahhouk)\n- Ithaca: [Georgios](https://github.com/gakonst)\n- Fabric: [@gaoist](https://x.com/gaoist)\n- And many more...\n\nThe inspiration for this work stems from [Andrew Miller](https://github.com/amiller)’s pioneering concept of a [Docker-based P2P TEE SDK](https://collective.flashbots.net/t/dstack-speedrunning-a-p2p-confidential-vm/3876).\n\nThis project cannot be built without standing on the shoulders of giants:\n\n- [konvera/meta-confidential-compute](https://github.com/konvera/meta-confidential-compute)\n\nSpecial acknowledgment to [Flashbots](https://github.com/flashbots) for building a community around TEE. The TEE Hacker House initiative, organized by [Flashbots](https://github.com/flashbots) and led by [Tina](https://github.com/CarboClanC), has brought together TEE builders to develop tools for TEE-Web3 integration. This collaborative journey has generated invaluable insights for advancing secure, confidential environments within Web3.\n\nTogether, we’re shaping the future of TEE in Web3, paving the way for more secure and developer-accessible confidential computing!\n\nFor a full list of the direct contributors to this repo, see [Contributors](https://github.com/Dstack-TEE/dstack/contributors) on GitHub.\n\n\n# License\n\nCopyright 2024 Phala Network and Contributors.\n\nLicensed under the Apache License, Version 2.0 (the \"License\"); you may not use this file except in compliance with the License. You may obtain a copy of the License at\n\n[http://www.apache.org/licenses/LICENSE-2.0](http://www.apache.org/licenses/LICENSE-2.0)"
      },
      {
        "type": "text",
        "text": "main.pdf\nDstack:  A Zero Trust Framework for Confidential Containers\nJune 23, 2025\nAbstract\nWeb3 applications require execution platforms that maintain confidentiality and integrity with-\nout relying on centralized trust authorities.  While Trusted Execution Environments (TEEs) offer\npromising capabilities for confidential computing, current implementations face significant limita-\ntions in security reliability, censorship resistance, and vendor independence when applied to Web3\ncontexts.  This paper presents Dstack, a comprehensive framework that transforms raw TEE tech-\nnology  into  a  true  Zero  Trust  platform  aligned  with  Web3  principles.   We  introduce  three  key\ninnovations:  (1) Portable Confidential Containers that enable seamless workload migration across\nheterogeneous TEE environments while maintaining security guarantees, (2) Decentralized Code\nManagement that leverages smart contracts for transparent governance of TEE applications, and\n(3) Verifiable Domain Management that ensures secure and verifiable application identity without\ncentralized authorities. Through these innovations, implemented via Dstack-OS, Dstack-KMS, and\nDstack-Gateway components, we demonstrate how to achieve both the performance advantages of\nVM-level TEE solutions and the trustless guarantees required by Web3 applications.  Our evalu-\nation shows that Dstack provides comprehensive security guarantees while maintaining practical\nusability for real-world applications.\n1    Introduction\nThe Web3 ecosystem represents a paradigm shift in digital trust models, fundamentally transforming\nthe relationship between users and application developers.  Unlike traditional systems, Web3 empowers\nusers with unprecedented control over their data through the principle of ”Code is Law” - once deployed,\ncode  operates  autonomously  and  independently  of  external  control.   This  transformation  demands\nrobust execution platforms that maintain confidentiality and integrity without relying on centralized\ntrust authorities.\nFigure 1:  The evolution of trust models from Web2 to Web3, highlighting the shift from centralized control\nto decentralized governance and execution.\nThe contrast between Web2 and Web3 architectures in Figure 1 illustrates this fundamental shift.\nIn Web2 systems, developers maintain complete control through proprietary applications and central-\nized servers, retaining administrative privileges to access and modify user data at will.  Web3’s smart\n1\ncontracts,  however,  represent  the  first  significant  step  toward  true  trustlessness  by  executing  pro-\ngrams on decentralized platforms (blockchains).  Once deployed, administrators cannot influence pro-\ngram execution, and lifecycle management (e.g., code updates) follows predefined agreements through\ndemocratic governance mechanisms like multi-signature wallets and Decentralized Autonomous Orga-\nnizations (DAOs).  This emerging trust model extends beyond basic applications to mission-critical\nscenarios such as AI model training, where data providers and model developers often have competing\ninterests,  and  autonomous  AI  agents  designed  to  operate  independently  of  human  intervention.   In\nthese  contexts,  Zero  Trust  platforms  become  essential  to  host  applications  and  enforce  verification\nmechanisms that appropriately constrain developer authority.\nA Zero Trust platform must enforce the following key principles:\n•  Code is Law: This manifests in two dimensions: (1) the application logic, once deployed, cannot\nbe  changed  unexpectedly;  and  (2)  the  lifecycle  management  of  code—including  deployment,\nupgrades, and deletion—follows predefined governance rules.\n•  Censorship Resistance:  User data remains beyond the control of any single entity, with data\navailability protected against Denial-of-Service attacks.\n•  Full Chain-of-Trust:  When users interact with applications on a Zero Trust platform,  they\nmust be able to verify all aspects of that application, including network setup, application identity\nand code logic, underlying hardware, and execution environment.\n•  Assume Breach:  The platform operates under the assumption that compromises will occur,\nimplementing  mechanisms  for  damage  containment,  rapid  recovery,  and  minimization  of  data\nexposure during security incidents.\nConfidential Computing, particularly through Trusted Execution Environments (TEEs), has emerged\nas a promising foundation for extending blockchain capabilities to support complex computational tasks\nwith confidentiality guarantees.  Recent advances in VM-level TEE solutions, including Intel TDX and\nAMD SEV, have demonstrated substantial performance improvements and developer-friendly inter-\nfaces,  making  them  compelling  candidates  for  Web3  deployment.   The  integration  of  GPUs  within\nTEEs [?] now enables verifiable execution of both Large Language Models and AI agents, providing\ncryptographic guarantees of computational integrity.\nHowever, a significant gap exists between raw TEE technology and the requirements of a true Zero\nTrust platform.  Current TEE implementations face several critical limitations when applied to Web3\ncontexts:\n•  Security Reliability:  Recent vulnerability discoveries in TEE systems have raised significant con-\ncerns  about  their  effectiveness  as  trust  anchors.   The  persistence  of  side-channel  attacks  and\nmicro-architectural vulnerabilities undermines confidence in TEE security guarantees, particu-\nlarly for high-value Web3 applications where a single compromise could lead to catastrophic data\nexposure.\n•  Censorship Vulnerability:  Conventional TEE encryption schemes bind encryption keys to spe-\ncific  hardware  instances,  creating  single  points  of  failure  that  contradict  Web3’s  requirement\nfor censorship resistance.  This architectural limitation means that data availability cannot be\nguaranteed if specific hardware instances are compromised or become unavailable.\n•  Vendor Dependencies:  Current trust models heavily rely on centralized hardware manufacturers\nand verification processes, introducing risks of vendor lock-in and potential censorship vectors.\nThis centralization contradicts Web3’s core principles of decentralization and trustlessness.\n•  Incomplete Verifiability:  While TEEs provide Remote Attestation capabilities to verify applica-\ntion and hardware identity, they fail to deliver the comprehensive chain of trust required in Zero\nTrust environments.  Users need guarantees that programs will process their data as expected\nand cannot be modified without proper authorization—capabilities beyond current attestation\nmechanisms.\nTo bridge this gap between raw TEE technology and Zero Trust requirements, we present Dstack,\na comprehensive framework for confidential containers that introduces three key innovations:\n2\n•  Portable Confidential Container: Our architecture enables seamless migration of confidential\nworkloads across different TEE instances and hardware vendors,  significantly reducing vendor\nlock-in risks while maintaining robust security guarantees.  This innovation directly addresses the\ncensorship vulnerability and vendor dependency limitations by providing hardware abstraction\nand state continuity across heterogeneous TEE environments.\n•  Decentralized Code Management:  We implement a comprehensive governance framework\nthat leverages smart contracts for transparent and decentralized management of TEE applica-\ntions.  This  system ensures verifiable deployment  and upgrade processes,  enforcing the  “Code\nis Law” principle by binding application lifecycles to on-chain governance decisions.  This inno-\nvation addresses the incomplete verifiability limitation by creating an immutable audit trail of\napplication changes.\n•  Verifiable Domain Management: Our novel approach to certificate management ensures that\nconfidential containers can exclusively control domains and provide native HTTPS support to\nTEE applications without relying on centralized authorities.  This system serves as a middleware\nbetween TEE applications and existing TLS-based networks, enabling users to establish end-to-\nend encrypted channels to TEE applications without modifications to client software.\nThese innovations are implemented through a cohesive system architecture comprising three core\ncomponents:\n•  Dstack-OS: A hardware abstraction layer with a minimized operating system image that elimi-\nnates differences in underlying TEE hardware while reducing the attack surface.  This component\nprovides a consistent, secure runtime environment across diverse TEE implementations.\n•  Dstack-KMS:  A  blockchain-controlled  key  management  service  that  replaces  hardware-based\nencryption schemas with an independent service for generating and managing secret keys.  This\ncomponent  enables  secure  data  migration  across  TEE  instances  and  supports  key  rotation  to\nprovide forward and backward data secrecy, mitigating the impact of potential TEE compromises.\n•  Dstack-Ingress and Dstack-Gateway: Complementary systems providing TEE-controlled domain\nmanagement through different approaches—Dstack-Ingress enables applications to specify cus-\ntom domains with minimal integration requirements, while Dstack-Gateway offers pre-registered\nwildcard domains requiring no application code changes.\nBy addressing the critical limitations of current TEE implementations, Dstack establishes a compre-\nhensive framework that transforms raw TEE technology into a true Zero Trust platform aligned with\nWeb3’s fundamental principles.  Our approach not only enhances the security and reliability of confi-\ndential computing but also provides a practical path toward truly decentralized, censorship-resistant\ninfrastructure for next-generation applications.\nThe remainder of this paper details the technical design of Dstack, evaluates its performance and\nsecurity characteristics, and demonstrates how our innovations collectively create a Zero Trust platform\nthat maintains the performance advantages of VM-level TEE solutions while addressing their inherent\nlimitations in Web3 contexts.\n2    System Design\n2.1    Portable Confidential Container\nContainerization has transformed cloud-native application deployment by providing unparalleled porta-\nbility and scalability through effective data separation.  These capabilities are particularly critical for\nTrusted Execution Environment (TEE) applications, as they directly address the inherent limitations\noutlined in Section 1:\n•  Security Reliability:  Containerized applications can be efficiently transferred from compro-\nmised TEE hardware to secure instances,  preserving code integrity.  Together with our secure\ndata migration mechanism that ensures both forward and backward secrecy, this approach sig-\nnificantly limits privacy leakage risks even when individual TEE instances are compromised.\n3\nFigure 2:  The architecture of Dstack, including Dstack-OS and Dstack-KMS. Dstack-OS provides a hardware\nabstraction layer with a minimized operating system image, while Dstack-KMS replaces the hardware-based\ndata encryption keys with a blockchain-controlled key management service.  TODO: redraw this to put the\ncomponents into solutions.\n•  Censorship Resistance: The architecture’s inherent scalability provides robust defense against\nDenial-of-Service attacks. Additionally, by decoupling data storage from execution environments,\nestablished  data  availability  solutions  can  be  readily  integrated  to  ensure  persistent  access  to\napplication data.\n•  Vendor  Independence:   Our  hardware  abstraction  layer  enables  confidential  containers  to\noperate across diverse TEE hardware platforms without modification, eliminating vendor lock-in\nwhile facilitating rapid adoption of emerging TEE technologies as they become available.\nHowever, implementing truly portable confidential containers presents substantial technical chal-\nlenges that differentiate them from conventional containerization.  Two fundamental obstacles must be\novercome:\nFirst, existing TEE implementations generate data sealing keys derived from hardware-bound root\nkeys unique to each TEE instance.  This architectural design creates an inherent barrier to portability\n— data encrypted by one TEE instance cannot be decrypted by any other, even when running identical\napplication code.  Prior research has largely circumvented this limitation by restricting TEEs to state-\nless applications, but this approach severely constrains their utility in complex real-world scenarios.\nSecond,  TEE implementations from different vendors impose disparate specifications for deploy-\nable programs.  This fragmentation forces developers to create and maintain multiple artifacts across\nplatforms, each requiring separate (and expensive) code reviews to verify functional equivalence — a\nprocess that undermines the trust guarantees central to Web3 applications.\nTo address these challenges comprehensively, we introduce two complementary components: Dstack-\nKMS and Dstack-OS.\n2.1.1    Dstack-KMS: Blockchain-Controlled Secret Derivation\nDstack-KMS  is  a  secret  derivation  service  that  fundamentally  transforms  how  encryption  keys  are\nmanaged in confidential computing environments.  Its primary function is to generate a unique and\nstable secret (the Root Key ) for each application based on its code and configurations.  This root key\n4\nserves as the foundation for deriving additional application-specific secrets used for data encryption\nand verifiable random number generation.\nUnlike hardware-based encryption approaches, Dstack-KMS deliberately decouples key generation\nfrom specific TEE hardware instances.  This architectural decision enables the critical capability of\nencrypted  data  migration  between  different  TEE  instances,  with  decryption  possible  after\nproper authorization.  This feature is essential for achieving true censorship resistance.\nGiven  its  position  as  the  root-of-trust  for  the  entire  system,  the  verifiability  and  availability  of\nDstack-KMS are paramount.  Unlike previous approaches [?] that assume TEE infallibility, our threat\nmodel explicitly acknowledges that TEEs can be compromised.  To address this reality, Dstack-\nKMS  implements  comprehensive  key  rotation  capabilities  that  provide  both  backward  and  forward\nsecrecy for application data. This ensures that even if a specific TEE hardware instance is compromised,\napplications can be migrated with limited data exposure.\nFigure 3:  The key derivation hierarchy of Intel SGX illustrates how conventional TEE implementations bind\nencryption keys to hardware.\nTo understand the limitations of conventional approaches, Figure 3 illustrates the key derivation\nhierarchy in Intel SGX. This design uses a hardware-bound key to both identify the TEE instance (for\nRemote Attestation) and generate encryption keys for data sealing.  While this approach effectively\nestablishes hardware identity, it fundamentally undermines censorship resistance:\n•  The root key cannot be updated, meaning a compromised TEE with a leaked root key remains\npermanently vulnerable even after patching the underlying vulnerability.\n•  Encrypted data becomes intrinsically bound to specific TEE hardware instances, creating single\npoints of failure that contradict Web3’s censorship resistance requirements.\nOur  Dstack-KMS  addresses  these  limitations  by  delegating  secret  generation  to  an  independent\nservice that ensures encrypted data remains portable across TEE instances.\nAs illustrated in Figure 4, Dstack-KMS comprises an on-chain governance smart contract coupled\nwith an off-chain peer-to-peer network where the actual secret derivation service operates.  To ensure\ncomprehensive verifiability of the Dstack-KMS program’s integrity and correctness, we implement a\nmulti-stage verification process:\n1.  The Dstack-KMS codebase is fully open-sourced [?], enabling thorough code and security reviews\nto verify key management logic and ensure the absence of backdoors.\n5\nFigure 4:  The architecture of Dstack-KMS combines on-chain governance through smart contracts with an\noff-chain P2P network of secret derivation service nodes.  This design ensures both verifiability and resilience\nagainst compromise.\n2.  Executable  binaries  are  produced  through  reproducible  build  processes,  allowing  verifiers  to\nconfirm that the runtime code matches the reviewed source code.\n3.  The cryptographic digest of valid executables is published through the governance smart contract,\ncreating an immutable reference for verification.\n4.  Each service node operates within its own TEE instance.  Critically, we rely on the TEE solely for\nmeasuring the executable and ensuring it matches the on-chain digest—not for the fundamental\nsecurity of the key management process.\nThis verification framework ensures that Dstack-KMS remains trustworthy to any third-party verifier\nwhile avoiding dependency on the absolute security of any single TEE instance.\nThe core logic of each Dstack-KMS service node is intentionally minimalist, focusing exclusively on\nthe generation and secure distribution of the root key, along with deriving encryption keys for TEE\napplications.  This simplicity enables the implementation of Multi-Party Computation (MPC) based\nthreshold key generation and derivation without concerning performance overhead.  We have developed\ntwo complementary implementations:\n•  Simple Duplication:  The first node in the P2P network generates a cryptographically secure\nrandom number as the root key, then shares it with other nodes after verifying their attestation\nreports.  All nodes maintain identical copies of the root key and derive consistent encryption keys\nfor  applications.   This  approach  maximizes  availability—as  long  as  at  least  one  node  remains\noperational, the root key can be recovered.\n•  MPC-Based Key Generation:  While simple duplication provides robust availability, it cre-\nates vulnerability to single-node compromises.  Our MPC implementation uses Shamir’s Secret\nSharing scheme [?] to distribute the root key across multiple nodes, ensuring that compromising\nany individual node (or even up tot− 1 nodes, wheret is the configured threshold) does not\nexpose  the  root  key.   This  approach  also  enables  advanced  features  like  key  rotation  without\nrequiring application reconfiguration.\nKey Derivation    Dstack-KMS implements a comprehensive key derivation framework to generate\napplication-specific keys from the root key:\n•  Application CA Key:  Derived from the root CA key using the application’s unique identifier\n(calculated as the hash of the application’s code and configuration).\n•  Disk Encryption Key:  Derived using a combination of the application identifier and instance\nidentifier, enabling secure storage with portability.\n6\n•  Environment Encryption Key: Derived using the application identifier alone, allowing secure\nenvironment variable management across instances.\n•  ECDSA Key:  Derived from the root ECDSA key, providing applications with consistent cryp-\ntographic identity for signing operations.\nEach derived key maintains cryptographic isolation while ensuring consistency across different TEE\ninstances running the same application.\nKey Rotation    A critical security feature of Dstack-KMS is its support for key rotation, which signif-\nicantly limits the exposure window during potential attacks while ensuring both forward and backward\nsecrecy for sealed data.  Key rotation procedures are initiated exclusively through the governance smart\ncontract, ensuring transparency and auditability.  We discuss two distinct rotation mechanisms:\n•  Root Key Share Rotation:  Our MPC-based implementation enables rotation of individual\nkey  shares  without  modifying  the  root  key  itself.   This  process  enhances  root  key  security  by\nregularly updating the distribution mechanism while remaining transparent to applications, as\nall derived application keys remain unchanged.\n•  Root Key Rotation:  In scenarios where the root key may have been compromised, we support\ncomplete root key rotation.  This process generates an entirely new root key and implements a\ncontrolled handover period during which both old and new keys remain valid.  This transition\nwindow  allows  applications  to  re-encrypt  their  data  with  keys  derived  from  the  new  root  key\nbefore the old root key is permanently destroyed, minimizing service disruption while enhancing\nsecurity.\nThrough these mechanisms, Dstack-KMS provides the foundation for truly portable confidential con-\ntainers by decoupling encryption from hardware dependencies while maintaining robust security guar-\nantees.\n2.1.2    Dstack-OS: Hardware Abstraction Layer\nDstack-OS provides a comprehensive hardware abstraction layer with a minimized operating system\nimage that bridges the gap between application containers and VM-level TEE implementations.  This\nlayer enables applications to deploy across diverse TEE environments without code modifications while\nmaintaining security integrity.  As a shared component across all TEE applications, Dstack-OS must be\nintrinsically secure and verifiable, with no administrative backdoors that could compromise program\ncode or user data.\nVM-level  TEE  solutions  typically  require  developers  to  provide  complete  system  images  encom-\npassing  bootloader,  kernel,  operating  system,  and  application  components.   This  requirement  not\nonly increases development complexity but also introduces potential security vulnerabilities through\nmisconfigured system components.  A secure and properly configured operating system environment\nfundamentally determines the security baseline for all TEE applications built upon it.\nFigure 5 illustrates how Dstack-OS establishes a secure and verifiable startup chain from the TEE\nhardware foundation through to user-provided container images.  Our modular design ensures that the\nmajority of the system can be reused across different TEE hardware implementations, substantially\nreducing the effort required for code review and security auditing.  Combined with reproducible build\nprocesses, this approach enables comprehensive verification of Dstack-OS with minimal overhead while\nsupporting multiple TEE hardware platforms.\nUsing Intel TDX as an exemplar (with similar procedures applicable to other TEE implementa-\ntions like AMD SEV), Dstack-OS consists of the following components,  presented in boot sequence\norder.  During this process, each component measures the next one and records these measurements\nin hardware registers, which are ultimately incorporated into the TEE attestation report:\n•  Hypervisor: When application deployment initiates, the underlying hypervisor (the TDX mod-\nule) loads the Open Virtual Machine Firmware (OVMF), enabling UEFI support for confidential\nvirtual  machines.   The  TDX  module  measures  the  OVMF  code  and  records  its  cryptographic\ndigest in the MRTD register, with the hypervisor’s integrity guaranteed by the TEE hardware\nitself.\n7\nFigure 5:  The architecture of Dstack-OS establishes a secure and verifiable startup chain from TEE hardware\nthrough to user applications.\n•  Open Virtual Machine Firmware (OVMF): The OVMF configures virtual machine hard-\nware  specifications  (CPU,  memory,  and  device  configurations)  and  records  the  configuration\nmeasurement  to  the  RTMR0  register.   It  then  loads  the  Linux  kernel  and  records  the  kernel\nimage measurement to the RTMR1 register.\n•  Kernel:  The kernel first loads an initial ramdisk (initrd) — a temporary in-memory filesystem\ncontaining  minimal  command-line  tools  and  disk  encryption  libraries.   The  initrd  mounts  the\nroot filesystem and records this measurement in the RTMR2 register.\n•  Root Filesystem: The root filesystem (RootFs) is a read-only environment containing essential\nsystem libraries and tools.  It manages the entire lifecycle of deployed applications, measuring\napplication images along with their associated key management system and storing these mea-\nsurements  in  the  RTMR3  register.   The  RootFs  serves  two  primary  functions:  (1)  providing\nthe runtime environment for user-level container images, and (2) managing application data en-\ncryption.   It  interfaces  with  Dstack-KMS  to  acquire  encryption  secrets  and  implements  Linux\nUnified Key Setup (LUKS) to encrypt application data in isolated volumes.  Data integrity is\nensured through dm-verity, a Merkle-tree-based block-level verification tool.  Finally, the RootFs\nconfigures network ingress for the application and initiates execution.\nRather than adapting existing system images, we built Dstack-OS from scratch to ensure only es-\nsential components are included in both the initrd and RootFs.  A comprehensive component inventory\nis provided in Appendix ?? for transparency and review.  Generally,  Dstack-OS includes only basic\nutilities (busybox), filesystem support, and container runtime components.  By implementing Docker\nsupport  while  delegating  orchestration  to  the  application  level,  we  maintain  a  minimal  base  image\nfootprint.\nTo ensure comprehensive verifiability, Dstack-OS is fully open-sourced and supports reproducible\nbuilds,  allowing  anyone  to  review  the  code  and  generate  identical  artifacts  for  verification.   This\napproach provides significant benefits for applications requiring security reviews,  as evaluators need\nonly review the application code rather than the entire system image.\nData Backup and Defense against Rollback Attacks    A critical challenge in confidential com-\nputing is ensuring data durability and integrity, particularly against rollback attacks where adversaries\nattempt to revert applications to previous states to bypass security checks or reuse expired secrets.\nOur architecture provides robust secure data backup support and implements robust anti-rollback\nmechanisms that application developers can integrate:\n•  Secure Backup:  Application data is encrypted using keys derived from Dstack-KMS and can\nbe backed up to external storage providers.  Since encryption keys are not bound to specific TEE\n8\ninstances, data can be restored on any authorized TEE, supporting true portability and disaster\nrecovery.\n•  Monotonic Counters: To prevent rollback attacks, developers can implement monotonic coun-\nters that increment with each critical data update, incorporating the counter value into the en-\ncrypted data.  During restoration, applications verify that the counter value equals or exceeds\nthe last known value, preventing replay of outdated snapshots.\nBy combining these techniques,  Dstack ensures both the recoverability and integrity of confidential\ndata across portable container migrations and backup scenarios.\nTogether, Dstack-KMS and Dstack-OS provide the foundational infrastructure for truly portable\nconfidential containers that maintain security and integrity across heterogeneous TEE environments\nwhile eliminating vendor lock-in and supporting comprehensive verifiability.\n2.2    Decentralized Code Management\nA core principle of Zero Trust platforms is the enforcement of “Code is Law”, ensuring that application\ncode  operates  as  intended  without  unexpected  modifications.   While  TEE  hardware  provides  code\nintegrity guarantees during execution, it cannot independently prevent administrators from deploying\nmalicious code or making unauthorized modifications.  Conversely, smart contracts have established\nrobust methodologies for implementing programmable governance over code lifecycle management —\nsuch as multi-signature requirements that prevent single-actor manipulation.\nOur  decentralized  code  management  framework  bridges  these  two  worlds  by  placing  TEE  ap-\nplication governance under smart contract control,  creating a transparent and auditable system for\napplication deployment and updates that aligns with Web3 principles.\nFigure 6:  The architecture of decentralized code management integrates on-chain governance contracts with\noff-chain TEE through Dstack-KMS.\nAs illustrated in Figure 6, our architecture consists of two complementary components:  on-chain\ngovernance  smart  contracts  and  off-chain  TEE  execution  environments  connected  through  Dstack-\nKMS. This design establishes the on-chain contracts as the definitive root-of-trust for the entire system.\nEvery operation — from initial deployment to code upgrades — must first be initiated and authorized\nthrough the governance contracts before off-chain TEE instances can execute these operations.\nThe governance framework implements a two-tier structure:\n•  KmsAuth Contract:  Serves as the global authority controlling Dstack-KMS operations.  This\ncontract maintains the registry of authorized applications and their governance parameters, en-\nforcing system-wide policies for TEE deployment.  By controlling whether Dstack-KMS shares\n9\napplication  secrets  with  specific  TEE  instances,  the  KmsAuth  contract  effectively  determines\nwhether applications can decrypt their data, thus controlling their complete lifecycle.\n•  AppAuth Contracts:  Individual governance contracts deployed for each application that de-\nfine  application-specific  management  rules.   These  contracts  specify  permissible  code  versions\n(through cryptographic hashes), authorized TEE instance identities, and upgrade approval re-\nquirements.  This modular approach enables customized governance models ranging from tradi-\ntional multi-signature schemes to complex DAO voting mechanisms, allowing each application\nto implement governance appropriate to its requirements.\nThe enforcement mechanism operates through Dstack-KMS, which will only provide application\nsecrets  to  TEE  instances  running  code  versions  explicitly  authorized  by  the  governance  contracts.\nThis creates a cryptographically enforced governance system where unauthorized code versions cannot\naccess application data, regardless of administrative privileges.\nTo  illustrate  this  mechanism,  consider  a  code  upgrade  process  for  an  application  using  a  multi-\nsignature AppAuth contract in Figure 6:\n1.  Developers  publish  the  new  code  version  and  submit  its  cryptographic  hash  to  the  AppAuth\ncontract.\n2.  The  contract  initiates  the  approval  process,  requiring  signatures  from  designated  key  holders\n(e.g., core developers, security auditors, and community representatives).\n3.  Each signature is recorded on-chain, creating an immutable audit trail of the approval process.\n4.  Once the required signature threshold is reached, the AppAuth contract updates its registry of\nauthorized code versions.\n5.  The  KmsAuth  contract,  monitoring  the  AppAuth  contract,  updates  its  authorization  records\naccordingly.\n6.  Dstack-KMS,  which  continuously  synchronizes  with  the  KmsAuth  contract,  begins  providing\napplication secrets to TEE instances running the newly approved code version.\n7.  TEE instances can now deploy the new code with full access to encrypted application data.\nThis process ensures that every code change follows predefined governance rules with complete trans-\nparency.  The on-chain approval records create an immutable audit trail that allows users to verify\nthe entire history of application changes, while the cryptographic enforcement through Dstack-KMS\nguarantees that only properly authorized code can access application data.\nBy combining the code integrity guarantees of TEEs with the transparent governance capabilities\nof  smart  contracts,  our  decentralized  code  management  framework  ensures  that  applications  truly\nembody the ”Code is Law” principle. Every aspect of the application lifecycle—from initial deployment\nto  version  updates  and  potential  retirement—follows  predefined,  transparent  rules  that  cannot  be\ncircumvented by any single entity, including the platform operators themselves.\n2.3    Verifiable Domain Management\nA  complete  Zero  Trust  platform  must  enable  seamless  verification  for  users  across  both  Web3  and\ntraditional  Web2  environments.   Our  Verifiable  Domain  Management  system  completes  the  chain-\nof-trust  by  allowing  standard  Web  browsers  to  cryptographically  verify  TEE  applications  without\nrequiring any client-side modifications or specialized knowledge.\nThis  capability  is  critical  for  mainstream  adoption,  as  it  allows  users  to  interact  with  confiden-\ntial applications using familiar tools while maintaining the same security guarantees provided by the\nunderlying TEE infrastructure.  We implement this through two complementary components—Dstack-\nIngress and Dstack-Gateway—both leveraging our novel Zero Trust TLS (ZT-TLS) protocol.\nThe  fundamental  innovation  in  ZT-TLS  is  establishing  cryptographic  proof  that  a  specific  TLS\ncertificate  (and  therefore  a  domain)  is  exclusively  controlled  by  a  verified  TEE  application.   This\ncreates a verification chain extending from the blockchain to standard HTTPS connections, enabling\nusers to confirm application authenticity through familiar security indicators in their browsers.\n10\nFigure  7:   The  Zero  Trust  TLS  architecture  establishes  a  cryptographically  verifiable  connection  between\nstandard web browsers and TEE applications through blockchain-anchored certificate management.\n2.3.1    Zero Trust TLS Protocol\nThe  ZT-TLS  protocol  addresses  a  critical  challenge:  how  to  cryptographically  bind  a  domain  to  a\nspecific TEE application in a way that prevents unauthorized certificate issuance or domain hijacking.\nOur solution integrates three key components:\n•  TEE-Generated Certificates:  The TEE application (specifically Dstack-Gateway) generates\nits TLS certificate using application secrets derived from Dstack-KMS. This ensures the private\nkey  never  exists  outside  the  TEE  environment  and  creates  a  cryptographic  link  between  the\non-chain governance and the TLS certificate.\n•  Certificate  Authority  Authorization  (CAA):  We  leverage  DNS  CAA  records  to  restrict\nwhich  certificate authorities can  issue certificates  for managed  domains.  By  configuring CAA\nrecords  to  only  authorize  certificates  from  specific  issuers  (which  verify  TEE  attestation),  we\nprevent unauthorized certificate issuance through alternative validation methods.\n•  Certificate Transparency (CT) Monitoring:  To protect against unauthorized DNS record\nmodifications, we implement continuous monitoring of Certificate Transparency logs.  This allows\ndetection of any unauthorized certificates and provides an immutable audit trail of certificate\nissuance history.\n2.3.2    Implementation Components\nWe provide two complementary implementations to accommodate different application requirements:\n•  Dstack-Gateway:  A fully managed reverse proxy running within a TEE that provides imme-\ndiate domain verification with zero application code changes.  Applications register with Dstack-\nGateway through a simple API call, during which Dstack-Gateway verifies the application’s re-\nmote attestation report.  Once verified, applications receive a subdomain under a pre-registered\nwildcard domain (e.g., app-id.Dstack.com), with all TLS termination and certificate manage-\nment handled automatically.\n•  Dstack-Ingress:   A  more  flexible  solution  for  applications  requiring  custom  domain  names.\nDstack-Ingress provides libraries and services that enable applications to manage their own TLS\ncertificates while maintaining the same verification guarantees.  This approach requires minimal\nintegration work while supporting application-specific domain requirements.\n11\nBoth implementations ensure that certificates are cryptographically bound to verified TEE environ-\nments, with the verification chain extending from the blockchain governance contracts through to the\nTLS certificates presented to users’ browsers.\n2.3.3    Security Guarantees and Protections\nOur Verifiable Domain Management system provides several critical security guarantees:\n•  Certificate Provenance Verification:  Users can verify that the TLS certificate presented by\nan application was issued to a legitimate TEE environment by checking the certificate against\non-chain records.\n•  Domain Binding Integrity:  The combination of CAA records and Certificate Transparency\nmonitoring ensures that domains remain bound to their designated TEE applications, preventing\nunauthorized certificate issuance.\n•  Tamper-Evident Certificate Changes:  Any unauthorized attempts to modify domain con-\nfigurations or issue alternative certificates are detected through Certificate Transparency moni-\ntoring, with alerts propagated to clients.\nWhile we cannot technically prevent all attacks against centralized DNS infrastructure, our multi-\nlayered approach creates a tamper-evident system where unauthorized changes are quickly detected\nand rejected by client verification processes.  This approach aligns with the ”Assume Breach” principle\nby implementing defense-in-depth strategies that maintain security even when individual components\nare compromised.\nBy extending the verification chain from blockchain governance through TEE attestation to stan-\ndard TLS certificates, our Verifiable Domain Management system enables seamless integration of Zero\nTrust  applications  into  existing  web  infrastructure.   This  creates  a  practical  path  for  mainstream\nadoption without requiring specialized knowledge or tools from end users, while maintaining the com-\nprehensive security guarantees that define true Zero Trust platforms.\n3    Verifying TEE Applications:  A Practical Walkthrough\nTo demonstrate how Dstack fulfills the Zero Trust principles and addresses the challenges outlined in\nSection 1,  we present a practical end-to-end verification scenario.  This walkthrough illustrates how\nthe architectural components described in Section 2 work together to provide a comprehensive chain\nof trust for real-world Web3 applications.\nTraditional  Zero  Trust  programs  like  smart  contracts  achieve  verifiability  through  transparent\nsource  code  and  inputs.   However,  extending  similar  verifiability  to  real-world  applications  presents\nunique  challenges,  particularly  in  maintaining  privacy  and  compatibility  with  existing  development\npractices.   Dstack  addresses  these  challenges  through  a  comprehensive  verification  framework  that\nrequires minimal code changes.\nThis section demonstrates Dstack’s complete chain of trust through a practical example:  verifying\nthat  a  cryptographic  key  was  genuinely  generated  within  a  TEE  environment.   This  scenario  is  es-\npecially relevant for Web3 and AI Agent applications where cryptographic keys establish application\nidentity and authority.\n3.1    Threat Model\nOur verification framework assumes the correct implementation and integrity of core Dstack compo-\nnents (Dstack-OS, Dstack-KMS, Dstack-Gateway, and governance contracts). While these components’\nsecurity guarantees are detailed in later sections, we explicitly consider developers and administrators\nas potential adversaries.\nPotential attack vectors include:\n•  Application-Level Attacks\n–  Deployment of unauthorized or malicious code through falsified Docker images\n12\n–  Introduction of malicious dependencies through supply chain attacks\n–  Unauthorized application updates that bypass governance controls\n•  Infrastructure-Level Attacks\n–  Tampering with Dstack-OS to circumvent security controls\n–  Deployment of compromised key management services\n–  Operation of unpatched or vulnerable TEE firmware\n–  Execution of applications on non-TEE hardware with spoofed attestation\n•  Network-Level Attacks\n–  DNS hijacking to redirect traffic to unauthorized applications\n–  Man-in-the-middle attacks on communication channels\nDirect attacks on TEE hardware security (e.g., exploitation of hardware vulnerabilities) are con-\nsidered out of scope for this discussion and addressed separately.\n3.2    The Reproducibility Challenge\nA  fundamental  challenge  in  TEE  attestation  lies  in  bridging  the  gap  between  source  code  and  the\nactual  artifacts  (binaries  or  container  images)  running  inside  enclaves.   While  TEE  attestation  can\nprove that a specific artifact runs within a secure environment, it cannot independently verify that the\nartifact accurately represents its claimed source code.\nThis limitation creates several security risks:\n•  Source Code Manipulation:  Developers could intentionally deploy artifacts that differ from\npublicly reviewed source code\n•  Build Process Compromise:  Supply chain attacks could inject malicious code during artifact\ncreation\n•  Toolchain  Vulnerabilities:   As  demonstrated  by  the  Ken  Thompson  Hack,  even  compiler\ntoolchains could be compromised to inject malicious behavior\nTEE  quotes  only  attest  to  measurements  (cryptographic  hashes)  of  running  artifacts.   Without\nguarantees that these artifacts accurately represent reviewed source code, users cannot fully trust ap-\nplications even when running in secure enclaves.  This challenge affects all TEE applications, including\nDstack’s core components.\nFigure 8:  Comprehensive verification chain from source code to running TEE applications\nEstablishing a complete verification chain requires three key elements:\n13\n•  Source Code Verification:  Open-source code or trusted third-party review ensuring no back-\ndoors exist\n•  Build Process Integrity:  Reproducible builds allowing independent verification of artifacts\n•  Runtime Attestation:  TEE quotes proving that verified artifacts are actually running\nTraditional reproducible builds, while ideal, often introduce significant complexity through special-\nized  toolchains  and  build  scripts.   The  following  section  introduces  an  alternative  approach, In-CC\nBuild, that achieves similar guarantees with improved practicality.\n3.3    Dstack Component Verifiability\nEach  core  Dstack  component  implements  specific  verifiability  mechanisms  anchored  in  transparent,\nimmutable records.  Table 1 summarizes these mechanisms:\nComponentSourceBuild MethodRegistryVerification\nDstack-OSOpenReproducibleKmsAuthOS Digest\nDstack-KMSOpenIn-CCKmsAuthImage Hash, Root PubKey\nDstack-GatewayOpenIn-CCAppAuthImage Hash\nTable 1:  Verifiability mechanisms and trust anchors for Dstack components\nAll components maintain open-source codebases with comprehensive documentation. Dstack-OS, as\nthe foundational component, undergoes third-party security audits and implements fully reproducible\nbuilds.\nThe governance smart contracts serve as authoritative registries, anchoring each component’s trust\nbase:\n•  Dstack-OS digests are registered in KmsAuth and managed through multi-signature governance\n•  Dstack-KMS measurements and root public keys are recorded in KmsAuth\n•  Dstack-Gateway artifacts are verified through dedicated AppAuth contracts\nIn-ConfidentialContainer Build    While reproducible builds represent the gold standard for arti-\nfact verification, they often prove impractical for complex applications.  Dstack addresses this through\nIn-CC Build,  leveraging  the  verified  Dstack-OS  as  a  trusted  foundation.   The  In-CC  Build  process\nexecutes entirely within Dstack-OS environment, encompassing code fetching, compilation, and arti-\nfact creation.  By specifying precise source references (e.g., a snapshot of the codebase), the system\nproduces verifiable artifacts with measurements attested in TEE quotes.  This approach minimizes the\ntrusted computing base while eliminating the complexity of traditional reproducible builds.\n3.4    End-to-End Verification Walkthrough\nFrom a user’s perspective, verifying a TEE application in Dstack requires validating a chain of mea-\nsurements against authoritative registries,  encompassing the user application,  runtime data,  Dstack\ncomponents, and network infrastructure.  This section walks through the verification process, demon-\nstrating how each step builds upon the previous one to create a comprehensive chain of trust.\nAs shown in Figure 9, the verification chain begins with the KmsAuth smart contract, which serves\nas the root of trust for the entire system, and concludes with the key generation application running\nin a TEE. We explain the verification steps as follows.\nFirst,  the address of the Dstack-KMS governance contract (i.e.,  KmsAuth) is publicly available.\nThe KMS governance contract serves as the authoritative registry for (1) off-chain KMS nodes and\n(2) dedicated governance contracts (i.e., AppAuth) for TEE applications.  It is worth noting that the\nDstack-Gateway can be regarded as a special TEE application that attests and forwards requests to\nother user applications while maintaining consistent verification procedures.\nThe  KmsAuth  contract  records  both  the  measurements  of  off-chain  KMS  node  programs  (KMS\ndigest, which is the hash of the docker compose file and the images used in In-CC Build) and the TDX\n14\nFigure 9:  The verification chain from authoritative registries to runtime measurements\nQuote of the first KMS node, which acts as the primary key generator.  The identities of subsequent\nKMS  nodes  must  first  be  registered  in  KmsAuth  and  verified  by  the  first  KMS  node  before  they\ncan participate in key generation.  These data, together with the open-source Dstack-KMS codebase,\nallow users to verify the integrity of the KMS nodes and their code correctness.  Subsequently,  the\noff-chain KMS nodes can be considered trusted extensions and used to verify Quotes from other TEE\napplications,  which  cannot  be  achieved  by  the  on-chain  governance  contract  alone.   The  off-chain\nKMS nodes are responsible for generating and managing cryptographic keys (i.e., the root key) and\nthe corresponding certificates (explained in Section 2.3.1), which are further used to authorize TEE\napplications after they are verified, thereby avoiding redundant verification.\nSecond, users can verify the validity of Dstack-Gateway.  By default, this is delegated to the off-\nchain  KMS  nodes  during  gateway  registration,  although  users  can  always  request  the  Quote  of  the\ngateway and check the digest of its docker compose file in its governance contract and the codebase.\nAfter the KMS nodes verify the gateway, it will generate its application root key along with a certificate\nchain ending with the root certificate.\nNext, users can access the TEE application through Dstack-Gateway forwarding.  In this case, users\neffectively delegate the verification of the key generation application to the gateway.  The deployment\nof the key generation application starts from the KmsAuth contract.  The deployer first registers it\nand stores the digest (the hash of the docker compose file and the images) on the dedicated AppAuth\ncontract.  Then, as in the previous step, the off-chain KMS nodes verify the Quote of the application\nafter  it  is  deployed  to  the  TEE  and  ensure  it  matches  the  registered  digest.   Only  after  successful\nverification will the key be generated along with the certificate chain.  To be forwarded by the gateway,\nthe application must also register with it.  In this case, the gateway verifies the application’s certificate\nchain and ensures it shares the same root certificate, indicating authorization by the same KMS.\nFinally, the user can invoke the application and request proof of the key it generated.  The applica-\ntion can generate a Quote on demand, with the generated public key included as custom data in the\nQuote.\n15\n3.5    Security Analysis:  Mitigating Threats\nOur key generation example demonstrates Dstack’s comprehensive approach to security across multiple\nattack surfaces.  At the application level, the system prevents unauthorized code deployment through\nrigorous  measurement  verification  against  the  AppAuth  registry.   The  In-CC  Build  process  ensures\nall dependencies originate from verified sources,  while any updates require new registry entries and\ncomplete re-verification.  It is important to note, however, that code audit and review processes remain\nessential for ensuring application code correctness, as the In-CC Build only guarantees the integrity of\nthe build process.\nInfrastructure security is maintained through multiple mechanisms.  TDX Quotes verify Dstack-OS\nintegrity, preventing OS-level tampering.  KMS updates require multi-signature governance approval,\nsafeguarding against unauthorized changes to key management services.  The Quote verification pro-\ncess  includes  firmware  version  validation,  ensuring  applications  run  on  up-to-date  TEE  hardware.\nHardware-backed TDX Quotes effectively prevent attestation spoofing attempts.\nNetwork-level threats are mitigated through the certificate chain validation system.  This prevents\nboth  DNS  hijacking  and  man-in-the-middle  attacks  by  ensuring  authentic  application  identity  and\nenabling end-to-end encryption with verified certificates.  The combination of these security measures\nensures that cryptographic keys maintain their integrity guarantees even when confronted with sophis-\nticated attacks targeting different system layers.\nReferences\n16"
      }
    ]
  }
]

Response:

# Project Proposal Template ## General Information 1.1. Name of Project Dstack 1.2. Project Description (what it does, why it is valuable, origin and history) Dstack is a developer-friendly and security-first SDK that simplifies the deployment of arbitrary containerized applications into Trusted Execution Environments (TEEs). It enables developers to securely deploy containerized applications in TEEs in minutes using familiar tools like docker-compose.yaml. Dstack provides safe management of secrets and sensitive data, along with built-in TLS termination for exposed services. The project was built by Kevin Wang and others from Phala Network, inspired by Andrew Miller (Flashbots & Teleport), and has received contributions from Nethermind and many others. Dstack addresses the gap between raw TEE technology and Zero Trust platform requirements by providing portable confidential containers, decentralized code management, and verifiable domain management. 1.3. How does this project align with the Consortium's Mission Statement [blank] 1.4. Project website URL https://docs.phala.network/dstack/overview (inferred from documentation references) 1.5. Social media accounts [blank] ## Legal Information 2.1. Project Logo URL or attachment (Vector Graphic: SVG, EPS). [blank] 2.2. Project license. We recommend an OSI-approved license, so if the license is not one on the list, explain why. Apache License, Version 2.0 2.3. Existing financial sponsorship. [blank] 2.4. Trademark status. [blank] ## Technical Information 3.1. High level assessment of project synergy with existing projects under the CCC, including how the project compliments/overlaps with existing projects, and potential ways to harmonize over time. Responses may be included both inline and/or in accompanying documentation. [blank] 3.2. Describe the Trusted Computing Base (TCB) of the project. If the project supports multiple environments please describe each TCB. Also identify if dependencies of other project (both CCC or non-CCC) TCBs are taken. Dstack's TCB includes: - Dstack-OS: A minimized operating system image that serves as a hardware abstraction layer - OVMF (Open Virtual Machine Firmware): Configures VM hardware specifications - Linux kernel with initial ramdisk (initrd) - Root filesystem with essential system libraries and tools - Intel TDX or equivalent TEE hardware as the foundation The system establishes a secure and verifiable startup chain from TEE hardware through to user applications, with each component measuring the next and recording measurements in hardware registers that are incorporated into TEE attestation reports. 3.3. Project Code of Conduct URL. We recommend a Contributor Covenant v2.0 based Code of Conduct, so if the Code of Conduct is not based on that, explain why. [blank] 3.4. Source control URL https://github.com/Dstack-TEE/dstack 3.5. Issue tracker URL https://github.com/Dstack-TEE/dstack/issues (inferred) 3.6. External dependencies (including licenses, and indicate whether each is a build time or runtime dependency) - Intel TDX or equivalent TEE hardware (runtime) - Linux kernel (runtime) - Docker/container runtime (runtime) - Busybox (runtime) - LUKS for encryption (runtime) - Wireguard-tools (build time) - Build-essential, chrpath, diffstat, lz4, xorriso (build time) - Rust (build time) 3.7. Standards implemented by the project, if any. Include links to any such standards. - TLS/HTTPS for secure communications - Certificate Transparency (CT) for certificate monitoring - Certificate Authority Authorization (CAA) for domain security - Remote Attestation for TEE verification 3.8. Release methodology and mechanics [blank] 3.9. Names of initial committers, if different from those submitting proposal Initial committers include: - Kevin Wang (kvinwang) - Shelven Zhou (shelvenzhou) - Leechael 3.10. List of project's official communication channels (slack, irc, mailing lists) [blank] 3.11. Project Security Response Policy [blank] 3.12. Preferred maturity level (Incubation, Graduation, or Emeritus) [blank] 3.13. Any additional information the TAC and Board should take into consideration when reviewing your proposal. Dstack includes several key components: - dstack-vmm: Service running on bare TDX host to manage CVMs - dstack-gateway: Reverse proxy to forward TLS connections to CVMs - dstack-kms: KMS server to generate keys for CVMs - dstack-guest-agent: Service in CVM to serve containers' key derivation and attestation requests - meta-dstack: Yocto meta layer to build CVM guest images The project provides innovative solutions for portable confidential containers, decentralized code management, and verifiable domain management, addressing critical limitations in current TEE implementations for Web3 contexts.

Model: claude-3-7-sonnet-202502192025-06-25 05:58:17

Context:

[
  {
    "role": "user",
    "content": "我想要一个读论文时的高亮方案来帮助我后续对其中的信息进行整理。"
  },
  {
    "role": "assistant",
    "content": "# 论文阅读高亮方案\n\n为了帮助你高效阅读和整理论文信息，我设计了以下高亮方案，将不同类型的内容用不同颜色标记，便于后续整理和回顾。\n\n## 颜色编码系统\n\n### 🟨 黄色：核心观点和结论\n- 论文的主要论点\n- 研究结果和结论\n- 作者提出的新理论或模型\n\n### 🟩 绿色：方法和实验设计\n- 研究方法的描述\n- 实验设计和步骤\n- 数据收集过程\n- 分析技术\n\n### 🟦 蓝色：重要数据和证据\n- 关键数据点和统计结果\n- 图表中的重要发现\n- 支持论点的证据\n\n### 🟪 紫色：术语和定义\n- 领域特定术语\n- 作者提出的新概念\n- 重要定义\n\n### 🟧 橙色：研究背景和文献综述\n- 相关工作的引用\n- 研究领域的历史背景\n- 与其他研究的关系\n\n### 🟥 红色：局限性和未来研究方向\n- 研究的局限性\n- 作者承认的缺陷\n- 未来研究建议\n\n## 使用符号系统\n\n除了颜色标记，你还可以使用以下符号进一步细化你的笔记：\n\n- ⭐ 特别重要的信息\n- ❓ 需要进一步研究或不清楚的内容\n- 💡 启发了你自己的想法\n- 🔄 与你之前读过的论文相关联的内容\n- ⚠️ 有争议或可能有问题的观点\n\n## 整理建议\n\n1. **阅读后总结**：每篇论文阅读完成后，花5-10分钟写一个简短摘要，包含主要观点和你的思考\n\n2. **创建概念图**：将相关论文的关键点连接起来，形成概念网络\n\n3. **建立文献数据库**：使用文献管理软件(如Zotero、Mendeley)存储论文并添加带颜色编码的笔记\n\n4. **定期复习**：每周回顾你的高亮内容，加深理解并发现新联系\n\n这个高亮方案可以根据你的具体研究领域和个人习惯进行调整，希望能帮助你更有效地组织和利用论文中的信息。"
  },
  {
    "role": "user",
    "content": "太多了 控制在四种颜色"
  }
]

Response:

# 简化论文阅读高亮方案（四色系统）为了保持简洁高效，以下是精简为四种颜色的论文阅读高亮方案： ## 颜色编码系统 ### 🟨 黄色：核心内容 - 论文的主要论点和结论 - 研究的关键发现 - 作者提出的新理论或模型 - 重要的定义和概念 ### 🟩 绿色：方法与数据 - 研究方法和实验设计 - 数据收集和分析过程 - 关键数据点和统计结果 - 重要图表中的发现 ### 🟦 蓝色：背景与关联 - 研究背景和文献综述 - 与其他研究的关系 - 相关工作的引用 - 学术脉络和理论框架 ### 🟥 红色：批判性内容 - 研究的局限性和缺陷 - 未来研究方向 - 有争议或可能有问题的观点 - 你自己的批判性思考和问题 ## 使用技巧 1. **保持一致性**：在所有论文中使用相同的颜色系统 2. **结合笔记**：在页边空白处添加简短笔记，与高亮内容对应 3. **阅读后整理**：将高亮内容按颜色分类整理到笔记中，形成结构化知识 4. **定期回顾**：通过回顾不同颜色的高亮内容，快速重温论文要点这个四色系统简单易用，同时仍能有效区分论文中的不同类型信息，帮助你高效整理和回顾学术内容。

Model: gpt-4o-mini-2024-07-182025-06-25 05:58:03

Context:

[
  {
    "role": "system",
    "content": "You are an assistant who is good at conversation. You need to summarize the user's conversation into a title of 10 characters or less. It should be in the format of \"Action - Title\". Some examples:\n1. Learn - Bitcoin 2. Code - Web Server 3. Write - An Article"
  },
  {
    "role": "user",
    "content": "[{\"role\":\"user\",\"mainText\":\"我想要一个读论文时的高亮方案来帮助我后续对其中的信息进行整理。\"},{\"role\":\"assistant\",\"mainText\":\"# 论文阅读高亮方案\\n\\n为了帮助你高效阅读和整理论文信息，我设计了以下高亮方案，将不同类型的内容用不同颜色标记，便于后续整理和回顾。\\n\\n## 颜色编码系统\\n\\n### 🟨 黄色：核心观点和结论\\n- 论文的主要论点\\n- 研究结果和结论\\n- 作者提出的新理论或模型\\n\\n### 🟩 绿色：方法和实验设计\\n- 研究方法的描述\\n- 实验设计和步骤\\n- 数据收集过程\\n- 分析技术\\n\\n### 🟦 蓝色：重要数据和证据\\n- 关键数据点和统计结果\\n- 图表中的重要发现\\n- 支持论点的证据\\n\\n### 🟪 紫色：术语和定义\\n- 领域特定术语\\n- 作者提出的新概念\\n- 重要定义\\n\\n### 🟧 橙色：研究背景和文献综述\\n- 相关工作的引用\\n- 研究领域的历史背景\\n- 与其他研究的关系\\n\\n### 🟥 红色：局限性和未来研究方向\\n- 研究的局限性\\n- 作者承认的缺陷\\n- 未来研究建议\\n\\n## 使用符号系统\\n\\n除了颜色标记，你还可以使用以下符号进一步细化你的笔记：\\n\\n- ⭐ 特别重要的信息\\n- ❓ 需要进一步研究或不清楚的内容\\n- 💡 启发了你自己的想法\\n- 🔄 与你之前读过的论文相关联的内容\\n- ⚠️ 有争议或可能有问题的观点\\n\\n## 整理建议\\n\\n1. **阅读后总结**：每篇论文阅读完成后，花5-10分钟写一个简短摘要，包含主要观点和你的思考\\n\\n2. **创建概念图**：将相关论文的关键点连接起来，形成概念网络\\n\\n3. **建立文献数据库**：使用文献管理软件(如Zotero、Mendeley)存储论文并添加带颜色编码的笔记\\n\\n4. **定期复习**：每周回顾你的高亮内容，加深理解并发现新联系\\n\\n这个高亮方案可以根据你的具体研究领域和个人习惯进行调整，希望能帮助你更有效地组织和利用论文中的信息。\"}]"
  }
]

Response:

Highlight - 论文方案

Model: claude-3-7-sonnet-202502192025-06-25 05:58:02

Context:

[
  {
    "role": "user",
    "content": "我想要一个读论文时的高亮方案来帮助我后续对其中的信息进行整理。"
  }
]

Response:

# 论文阅读高亮方案为了帮助你高效阅读和整理论文信息，我设计了以下高亮方案，将不同类型的内容用不同颜色标记，便于后续整理和回顾。 ## 颜色编码系统 ### 🟨 黄色：核心观点和结论 - 论文的主要论点 - 研究结果和结论 - 作者提出的新理论或模型 ### 🟩 绿色：方法和实验设计 - 研究方法的描述 - 实验设计和步骤 - 数据收集过程 - 分析技术 ### 🟦 蓝色：重要数据和证据 - 关键数据点和统计结果 - 图表中的重要发现 - 支持论点的证据 ### 🟪 紫色：术语和定义 - 领域特定术语 - 作者提出的新概念 - 重要定义 ### 🟧 橙色：研究背景和文献综述 - 相关工作的引用 - 研究领域的历史背景 - 与其他研究的关系 ### 🟥 红色：局限性和未来研究方向 - 研究的局限性 - 作者承认的缺陷 - 未来研究建议 ## 使用符号系统除了颜色标记，你还可以使用以下符号进一步细化你的笔记： - ⭐ 特别重要的信息 - ❓ 需要进一步研究或不清楚的内容 - 💡 启发了你自己的想法 - 🔄 与你之前读过的论文相关联的内容 - ⚠️ 有争议或可能有问题的观点 ## 整理建议 1. **阅读后总结**：每篇论文阅读完成后，花5-10分钟写一个简短摘要，包含主要观点和你的思考 2. **创建概念图**：将相关论文的关键点连接起来，形成概念网络 3. **建立文献数据库**：使用文献管理软件(如Zotero、Mendeley)存储论文并添加带颜色编码的笔记 4. **定期复习**：每周回顾你的高亮内容，加深理解并发现新联系这个高亮方案可以根据你的具体研究领域和个人习惯进行调整，希望能帮助你更有效地组织和利用论文中的信息。

Model: gpt-4o-mini-2024-07-182025-06-25 01:53:55

Context:

[
  {
    "role": "system",
    "content": "You are an assistant who is good at conversation. You need to summarize the user's conversation into a title of 10 characters or less. It should be in the format of \"Action - Title\". Some examples:\n1. Learn - Bitcoin 2. Code - Web Server 3. Write - An Article"
  },
  {
    "role": "user",
    "content": "[{\"role\":\"user\",\"mainText\":\"把这个docker compose file转成直接的docker command\\nservices:\\n  app:\\n    image: olehnemi/tee-rex:0.0.14\\n    container_name: app\\n    ports:\\n      - \\\"80:80\\\"\\n    volumes:\\n      - /var/run/tappd.sock:/var/run/tappd.sock\"},{\"role\":\"assistant\",\"mainText\":\"要将这个 Docker Compose 文件转换为直接的 Docker 命令，您可以使用以下命令：\\n\\n```bash\\ndocker run -d \\\\\\n  --name app \\\\\\n  -p 80:80 \\\\\\n  -v /var/run/tappd.sock:/var/run/tappd.sock \\\\\\n  olehnemi/tee-rex:0.0.14\\n```\\n\\n这个命令的解释：\\n- `-d`: 在后台运行容器（detached 模式）\\n- `--name app`: 将容器命名为 \\\"app\\\"\\n- `-p 80:80`: 将主机的 80 端口映射到容器的 80 端口\\n- `-v /var/run/tappd.sock:/var/run/tappd.sock`: 挂载主机上的 /var/run/tappd.sock 到容器内的相同路径\\n- `olehnemi/tee-rex:0.0.14`: 使用的镜像名称和标签\"}]"
  }
]

Response:

Convert - Docker

Model: claude-3-7-sonnet-202502192025-06-25 01:53:54

Context:

[
  {
    "role": "user",
    "content": "把这个docker compose file转成直接的docker command\nservices:\n  app:\n    image: olehnemi/tee-rex:0.0.14\n    container_name: app\n    ports:\n      - \"80:80\"\n    volumes:\n      - /var/run/tappd.sock:/var/run/tappd.sock"
  }
]

Response:

要将这个 Docker Compose 文件转换为直接的 Docker 命令，您可以使用以下命令： ```bash docker run -d \ --name app \ -p 80:80 \ -v /var/run/tappd.sock:/var/run/tappd.sock \ olehnemi/tee-rex:0.0.14 ``` 这个命令的解释： - `-d`: 在后台运行容器（detached 模式） - `--name app`: 将容器命名为 "app" - `-p 80:80`: 将主机的 80 端口映射到容器的 80 端口 - `-v /var/run/tappd.sock:/var/run/tappd.sock`: 挂载主机上的 /var/run/tappd.sock 到容器内的相同路径 - `olehnemi/tee-rex:0.0.14`: 使用的镜像名称和标签

Model: gpt-4o-mini-2024-07-182025-06-25 01:42:53

Context:

[
  {
    "role": "system",
    "content": "You are an assistant who is good at conversation. You need to summarize the user's conversation into a title of 10 characters or less. It should be in the format of \"Action - Title\". Some examples:\n1. Learn - Bitcoin 2. Code - Web Server 3. Write - An Article"
  },
  {
    "role": "user",
    "content": "[{\"role\":\"user\",\"mainText\":\"docker run怎么限制cpu数量\"},{\"role\":\"assistant\",\"mainText\":\"# 使用Docker Run限制CPU数量\\n\\nDocker允许您在运行容器时限制其可以使用的CPU资源。以下是几种限制CPU的方法：\\n\\n## 1. 使用`--cpus`选项\\n\\n这个选项指定容器可以使用的CPU数量（可以是小数）：\\n\\n```bash\\ndocker run --cpus=2 my-image\\n```\\n\\n上面的命令限制容器最多使用2个CPU核心。\\n\\n## 2. 使用`--cpu-period`和`--cpu-quota`选项\\n\\n这两个选项一起使用可以更精细地控制CPU使用率：\\n\\n```bash\\ndocker run --cpu-period=100000 --cpu-quota=200000 my-image\\n```\\n\\n这表示在每100,000微秒的周期内，容器最多可以使用200,000微秒的CPU时间，相当于2个CPU核心。\\n\\n## 3. 使用`--cpuset-cpus`选项\\n\\n如果您想指定容器可以使用哪些特定的CPU核心：\\n\\n```bash\\ndocker run --cpuset-cpus=\\\"0,1\\\" my-image\\n```\\n\\n这限制容器只能使用CPU核心0和1。\\n\\n## 4. 使用`--cpu-shares`选项\\n\\n设置容器相对权重（默认为1024）：\\n\\n```bash\\ndocker run --cpu-shares=512 my-image\\n```\\n\\n这设置容器的CPU共享权重为512，当系统繁忙时，它将获得默认容器一半的CPU时间。\\n\\n## 示例组合使用\\n\\n限制容器使用1.5个CPU核心，并且只能使用CPU 0和CPU 1：\\n\\n```bash\\ndocker run --cpus=1.5 --cpuset-cpus=\\\"0,1\\\" my-image\\n```\\n\\n注意：这些限制仅在CPU资源竞争时生效，如果系统有足够的空闲CPU资源，容器可能会使用超过限制的CPU。\"}]"
  }
]

Response:

Limit - CPU Num

Model: claude-3-7-sonnet-202502192025-06-25 01:42:51

Context:

[
  {
    "role": "user",
    "content": "docker run怎么限制cpu数量"
  }
]

Response:

# 使用Docker Run限制CPU数量 Docker允许您在运行容器时限制其可以使用的CPU资源。以下是几种限制CPU的方法： ## 1. 使用`--cpus`选项这个选项指定容器可以使用的CPU数量（可以是小数）： ```bash docker run --cpus=2 my-image ``` 上面的命令限制容器最多使用2个CPU核心。 ## 2. 使用`--cpu-period`和`--cpu-quota`选项这两个选项一起使用可以更精细地控制CPU使用率： ```bash docker run --cpu-period=100000 --cpu-quota=200000 my-image ``` 这表示在每100,000微秒的周期内，容器最多可以使用200,000微秒的CPU时间，相当于2个CPU核心。 ## 3. 使用`--cpuset-cpus`选项如果您想指定容器可以使用哪些特定的CPU核心： ```bash docker run --cpuset-cpus="0,1" my-image ``` 这限制容器只能使用CPU核心0和1。 ## 4. 使用`--cpu-shares`选项设置容器相对权重（默认为1024）： ```bash docker run --cpu-shares=512 my-image ``` 这设置容器的CPU共享权重为512，当系统繁忙时，它将获得默认容器一半的CPU时间。 ## 示例组合使用限制容器使用1.5个CPU核心，并且只能使用CPU 0和CPU 1： ```bash docker run --cpus=1.5 --cpuset-cpus="0,1" my-image ``` 注意：这些限制仅在CPU资源竞争时生效，如果系统有足够的空闲CPU资源，容器可能会使用超过限制的CPU。

Model: gpt-4o-mini-2024-07-182025-06-24 12:32:35

Context:

[
  {
    "role": "system",
    "content": "You are an assistant who is good at conversation. You need to summarize the user's conversation into a title of 10 characters or less. It should be in the format of \"Action - Title\". Some examples:\n1. Learn - Bitcoin 2. Code - Web Server 3. Write - An Article"
  },
  {
    "role": "user",
    "content": "[{\"role\":\"user\",\"mainText\":\"帮我总结下邮件内容\\n\\n```\\nalt.hn\\n5/15/2025 at 4:19:00 PM\\n\\nLaunch HN: Tinfoil (YC X25): Verifiable Privacy for Cloud AI\\nby FrasiertheLion\\n\\n5/15/2025 at 6:52:24 PM\\n\\nLooks great. Not sure how big the market is between \\\"need max privacy, need on-prem\\\" and \\\"don't care, just use what is cheap/popular\\\" tho.\\nCan you talk about how this relates to / is different / is differentiated from what Apple claimed to do during their last WWDC? They called it \\\"private cloud compute\\\". (To be clear, after 11 months, this is still \\\"announced\\\", with no implementation anywhere, as far as I can see.)\\n\\nHere is their blog post on Apple Security, dated June 10: https://security.apple.com/blog/private-cloud-compute/\\n\\nEDIT: JUST found the tinfoil blog post on exactly this topic. https://tinfoil.sh/blog/2025-01-30-how-do-we-compare\\n\\nby sigmaisaletter\\n\\n5/16/2025 at 2:13:36 AM\\n\\nAnecdotal, but I work at a company offering an SMB product with LLM features. One of the first questions asked on any demo or sales call is what the privacy model for the LLM is, how the data is used, who has access to it, and can those features be disabled.\\nby _heimdall\\n\\n5/15/2025 at 7:10:02 PM\\n\\nPrivate Cloud Compute has been in use since iOS 18 released.\\nby davidczech\\n\\n5/15/2025 at 9:29:40 PM\\n\\nIt seems that PCC indeed went live with 18.1 - tho not in Europe (which is where I am located). Thanks for the heads up, I will look into this further.\\nby sigmaisaletter\\n\\n5/16/2025 at 12:10:54 PM\\n\\nThere are a few stories on the 'max privacy' stuff; one of the stories goes that you have two companies each with something private that needs to combine their stuff without letting the other see it; for example a bank with customer transactions and a company with analytics software they don't want to share; a system like this lets the bank put their transaction data through that analytics software without anyone being able to see the transaction data or the software. The next level on that is where two banks need to combine the transaction data to spot fraud, where you've now got three parties involved on one server.\\nby trebligdivad\\n\\n5/15/2025 at 8:19:51 PM\\n\\nCompanies like Edgeless Systems have been building open-source confidential computing for cloud and AI for years, they are open-source, and have published in 2024 how they compare to Apple Private Cloud Compute. https://www.edgeless.systems/blog/apple-private-cloud-comput...\\nby ts6000\\n\\n5/15/2025 at 8:05:14 PM\\n\\nPrivate Cloud Compute has been live in production for 8 months\\nby DrBenCarson\\n\\n5/15/2025 at 9:29:47 PM\\n\\nIt seems that PCC indeed went live with 18.1 - tho not in Europe (which is where I am located). Thanks for the heads up, I will look into this further.\\nby sigmaisaletter\\n\\n5/15/2025 at 5:58:40 PM\\n\\nHow large do you wager your moat to be? Confidential computing is something all major cloud providers either have or are about to have and from there it's a very small step to offer LLM-s under the same umbrella. First mover advantage is of course considerable, but I can't help but feel that this market will very quickly be swallowed by the hyperscalers.\\nby Etheryte\\n\\n5/15/2025 at 10:57:32 PM\\n\\nCloud providers aren't going to care too much about this.\\nI have worked for many enterprise companies e.g. banks who are trialling AI and none of them have any use for something like this. Because the entire foundation of the IT industry is based on trusting the privacy and security policies of Azure, AWS and GCP. And in the decades since they've been around not heard of a single example of them breaking this.\\n\\nThe proposition here is to tell a company that they can trust Azure with their banking websites, identity services and data engineering workloads but not for their model services. It just doesn't make any sense. And instead I should trust a YC startup who statistically is going to be gone in a year and will likely have their own unique set of security and privacy issues.\\n\\nAlso you have the issue of smaller sized open source models e.g. DeepSeek R1 lagging far behind the bigger ones and so you're giving me some unnecessary privacy attestation at the expense of a model that will give me far better accuracy and performance.\\n\\nby threeseed\\n\\n5/16/2025 at 12:48:50 PM\\n\\n> Cloud providers aren't going to care too much about this. ... [E]nterprise companies e.g. banks ... and none of them have any use for something like this.\\nAs former CTO of world's largest bank and cloud architect at world's largest hedge fund, this is exactly opposite of my experience with both regulated finance enterprises and the CSPs vying to serve them.\\n\\nThe entire foundation of the IT industry is based on trusting the privacy and security policies of Azure, AWS and GCP. And in the decades since they've been around not heard of a single example of them breaking this.\\n\\nOn the contrary, many global banks design for the assumption the \\\"CSP is hostile\\\". What happened to Coinbase's customers the past few months shows why your vendor's insider threat is your threat and your customers' threat.\\n\\nGranted, this annoys CSPs who wish regulators would just let banks \\\"adopt\\\" the CSP's controls and call it a day.\\n\\nUnfortunately for CSP sales teams — certainly this could change with recent regulator policy changes — the regulator wins. Until very recently, only one CSP offered controls sufficient to assure your own data privacy beyond a CSP's pinky-swears. AWS Nitro Enclaves can provide a key component in that assurance, using deployment models such as tinfoil.\\n\\nby Terretta\\n\\n5/15/2025 at 6:12:32 PM\\n\\nBeing gobbled by the hyperscalers may well be the plan. Reasonable bet.\\nby itsafarqueue\\n\\n5/16/2025 at 1:10:58 AM\\n\\nGCP has confidential VMs with H100 GPUs; I'm not sure if Google would be interested. And they get huge discount buying GPUs in bulk. The trade-off between cost and privacy is obvious for most users imo.\\nby kevinis\\n\\n5/15/2025 at 6:34:04 PM\\n\\nThis. Big tech providers already offer confidential inference today.\\nby ATechGuy\\n\\n5/15/2025 at 6:44:25 PM\\n\\nYes Azure has! They have very different trust assumptions though. We wrote about this here https://tinfoil.sh/blog/2025-01-30-how-do-we-compare\\nby julesdrean\\n\\n5/15/2025 at 6:52:22 PM\\n\\nLast I checked it was only Azure offering the Nvidia specific confidential compute extensions, I'm likely out of date - a quick Google was inconclusive.\\nHave GCP and AWS started offering this for GPUs?\\n\\nby mnahkies\\n\\n5/15/2025 at 7:16:55 PM\\n\\nGCP, yes: https://cloud.google.com/confidential-computing/confidential...\\nby candiddevmike\\n\\n5/15/2025 at 7:37:49 PM\\n\\nAzure and GCP offer Confidential VMs which removes trust from the cloud providers. We’re trying to also remove trust in the service provider (aka ourselves). One example is that when you use Azure or GCP, by default, the service operator can SSH into the VM. We cannot SSH into our inference server and you can check that’s true.\\nby julesdrean\\n\\n5/15/2025 at 11:03:05 PM\\n\\nBut nobody wants you as a service provider. Everyone wants to have Gemini, OpenAI etc which are significantly better than the far smaller and less capable model you will be able to afford to host.\\nAnd you make this claim that the cloud provider can SSH into the VM but (a) nobody serious exposes SSH ports in Production and (b) there is no documented evidence of this ever happening.\\n\\nby threeseed\\n\\n5/15/2025 at 11:31:53 PM\\n\\nWe're not competing with Gemini or OpenAI or the big cloud providers. For instance, Google is partnering with NVIDIA to ship Gemini on-prem to regulated industries in a CC environment to protect their model weights as well as for additional data privacy on-prem: https://blogs.nvidia.com/blog/google-cloud-next-agentic-ai-r...\\nWe're simply trying to bring similar capabilities to other companies. Inference is just our first product.\\n\\n>cloud provider can SSH into the VM\\n\\nThe point we were making was that CC was traditionally used to remove trust from cloud providers, but not the application provider. We are further removing trust from ourselves (as the application provider), and we can enable our customers (who could be other startups or neoclouds) to remove trust from themselves and prove that to their customers.\\n\\nby FrasiertheLion\\n\\n5/15/2025 at 11:55:46 PM\\n\\nYou are providing the illusion of trust though.\\nThere are a multitude of components between my app and your service. You have secured one of them arguably the least important. But you can't provide any guarantees over say your API server that my requests are going through. Or your networking stack which someone e.g. a government could MITM.\\n\\nby threeseed\\n\\n5/16/2025 at 12:19:20 AM\\n\\nI don't know anything about \\\"secure enclaves\\\" but I assume that this part is sorted out. It should be possible to use http with it I imagine. If not, yeah it is totally dumb from a conceptual standpoint.\\nby osigurdson\\n\\n5/15/2025 at 6:17:24 PM\\n\\nConfidential computing as a technology will become (and should be) commoditized, so the value add comes down to security and UX. We don’t want to be a confidential computing company, we want to use the right tool for the job of building private & verifiable AI. If that becomes FHE in a few years, then we will use that. We are starting with easy-to-use inference, but our goal of having any AI application be provably private\\nby 3s\\n\\n5/16/2025 at 12:07:29 PM\\n\\nI suspect Nvidia have done a lot of the heavy lifting to make this work; but it's not that trivial to wire the CPU and GPU confidential compute together.\\nby trebligdivad\\n\\n5/15/2025 at 6:12:16 PM\\n\\nDoes this not require one to trust the hardware? I'm not an expert in hardware root of trust, etc, but if Intel (or whatever chip maker) decides to just sign code that doesn't do what they say it does (coerced or otherwise) or someone finds a vuln; would that not defeat the whole purpose?\\nI'm not entirely sure this is different than \\\"security by contract\\\", except the contracts get bigger and have more technology around them?\\n\\nby amanda99\\n\\n5/15/2025 at 6:29:00 PM\\n\\nWe have to trust the hardware manufacturer (Intel/AMD/NVIDIA) designed their chips to execute the instructions we inspect, so we're assuming trust in vendor silicon either way.\\nThe real benefit of confidential computing is to extend that trust to the source code too (the inference server, OS, firmware).\\n\\nMaybe one day we’ll have truly open hardware ;)\\n\\nby natesales\\n\\n5/15/2025 at 8:34:37 PM\\n\\nHi Nate. Routinely your various networking-related FOSS tools. Surprising to see you now work in the AI infrastructure space let alone co-founding a startup funded by YC! Tinfoil looks über neat. All the best (:\\n> Maybe one day we'll have truly open hardware\\n\\nAt least the RoT/SE if nothing else: https://opentitan.org/\\n\\nby ignoramous\\n\\n5/15/2025 at 9:00:36 PM\\n\\nLove Open Titan! RISC-V all the way babe! The team is bunker: several of my labmates now work there\\nby julesdrean\\n\\n5/16/2025 at 4:08:20 PM\\n\\nIsn't this not the case for FHE? (I understand that FHE is not practically viable as you guys mention in the OP.)\\nby perching_aix\\n\\n5/16/2025 at 4:55:55 PM\\n\\nYeah not the case for FHE. But yes, not practically viable. We would be happy to switch as soon as it is.\\nby FrasiertheLion\\n\\n5/15/2025 at 9:04:21 PM\\n\\nI agree, it's lifting trust to the manufacturer (which could still be an improvement over the cloud status quo).\\nAnother (IMO more likely) scenario is someone finds a hardware vulnerability (or leaked signing keys) that let's them achieve a similar outcome.\\n\\nby rkagerer\\n\\n5/15/2025 at 6:38:45 PM\\n\\nThe only way to guarantee privacy in cloud computing is via homorphic encryption.\\nThis approach relies too much on trust.\\n\\nIf you have data you are seriously sensitive about, its better for you to run models locally on air gapped instances.\\n\\nIf you think this is an overkill, just see what happened to coinbase of recent. [0]\\n\\n[0]: https://www.cnbc.com/2025/05/15/coinbase-says-hackers-bribed...\\n\\nby max_\\n\\n5/15/2025 at 6:44:11 PM\\n\\nYeah, totally agree with you. We would love to use FHE as soon as it's practical. And if you have the money and infra expertise to deploy air gapped LLMs locally, you should absolutely do that. We're trying to do the best we can with today's technology, in a way that is cheap and accessible to most people.\\nby FrasiertheLion\\n\\n5/15/2025 at 11:50:47 PM\\n\\n> The only way to guarantee privacy in cloud computing is via homorphic encryption\\nNo. The only way is to not use cloud computing at all and go on-premise.\\n\\nWhich is what companies around the world do today for security or privacy critical workloads.\\n\\nby threeseed\\n\\n5/16/2025 at 12:54:35 PM\\n\\n> The only way is to not use cloud computing at all and go on-premise.\\nThis point of view may be based on a lack of information about how global finance handles security and privacy critical workloads in high-end cloud.\\n\\nGlobal banks and the CSPs that serve them have by and large solved this problem by the late 2010s - early 2020s.\\n\\nWhile much of the work is not published, you can look for presentations at AWS reInvent from e.g. Goldman Sachs or others willing to share about it, talking about cryptographic methods, enclaves, formal reasoning over not just code but things like reachability, and so on, to see the edges of what's being done in this space.\\n\\nby Terretta\\n\\n5/15/2025 at 8:44:00 PM\\n\\nTinfoil hat on: say you are compelled to execute a FISA warrant and access the LLM data, is it technically possible? What about an Australian or UK style \\\"please add a backdoor\\\".\\nI see you have to trust NVidia etc. so maybe there are such backdoors.\\n\\nby coolcase\\n\\n5/15/2025 at 10:43:47 PM\\n\\nAn attacker would need to compromise our build pipeline to publish a backdoored VM image [1] and extract key material to forge an attestation from the hardware [2]. The build process publishes a hash of the code to Sigstore’s transparency log [3], which would make the attack auditable.\\nThat said, a sufficiently resourced attacker wouldn’t need to inject a backdoor at all. If the attacker already possesses the keys (e.g. the attacker IS the hardware manufacturer, or they’ve coerced the manufacturer to hand the keys over), then they would just need to gain access to the host server (which we control) to get access to the hypervisor, then use their keys to read memory or launch a new enclave with a forged attestation. We're planning on writing a much more detailed blog post about \\\"how to hack ourselves\\\" in the future.\\n\\nWe actually plan to do an experiment at DEFCON, likely next year where we gives ssh access to a test machine running the enclave and have people try to exfiltrate data from inside the enclave while keeping the machine running.\\n\\n[1] https://github.com/tinfoilsh/cvmimage\\n\\n[2] https://arxiv.org/abs/2108.04575\\n\\n[3] https://github.com/tinfoilsh/cvmimage/attestations\\n\\nby natesales\\n\\n5/15/2025 at 9:24:19 PM\\n\\nWhat's your revenue model?\\nThe pricing page implies you're basically reselling access to confidential-wrapped AI instances.\\n\\nSince you rightly open-sourced the code (AGPL) is there anything stopping the cloud vendors from running and selling access to their own instances of your server-side magic?\\n\\nIs your secret sauce the tooling to spin up and manage instances and ease customer UX? Do you aim to attract an ecosystem of turnkey, confidential applications running on your platform?\\n\\nDo you envision an exit strategy that sells said secret sauce and customers to a cloud provider or confidential computing middleware provider?\\n\\nPs. Congrats on the launch.\\n\\nby rkagerer\\n\\n5/15/2025 at 9:51:12 PM\\n\\n>Since you rightly open-sourced the code (AGPL) is there anything stopping the cloud vendors from running and selling access to their own instances of your server-side magic?\\nSure they can do that. Despite being open source, CC-mode on GPUs is quite difficult to work with especially when you start thinking about secrets management, observability etc, so we’d actually like to work with smaller cloud providers who want to provide this as a service and become competitive with the big clouds.\\n\\n>Is your secret sauce the tooling to spin up and manage instances and ease customer UX?\\n\\nPretty much. Confidential computing has been around a while, and we still don’t see widespread adoption of it, largely because of the difficulty. If we're successful, we absolutely expect there to be a healthy ecosystem of competitors both cloud provider and startup.\\n\\n>Do you envision an exit strategy that sells that secret sauce to a cloud provider or confidential computing middleware provider?\\n\\nWe’re not really trying to be a confidential computing provider, but more so, a verifiably private layer for AI. Which means we will try to make integration points as seamless as possible. For inference, that meant OpenAI API compatible client SDKs, we will eventually do the same for training/post-training, or MCP/OpenAI Agents SDK, etc. We want our integration points to be closely compatible with existing pipelines.\\n\\nby FrasiertheLion\\n\\n5/15/2025 at 11:49:59 PM\\n\\n> Confidential computing has been around a while, and we still don’t see widespread adoption of it, largely because of the difficulty\\nThis is not the reason at all. Complexity and difficult are inherent to large companies.\\n\\nIt's because it is a very low priority in an environment where for example there are tens of thousands of libraries in use, dozens of which will be in Production with active CVEs. And there are many examples of similar security and risk management issues that companies have to deal with.\\n\\nWorrying about the integrity of the hardware or not trusting my cloud provider who has all my data in their S3 buckets anyway (which is encrypted using their keys) is not high on my list of concerns. And if it were I would be simply running on-premise anyway.\\n\\nby threeseed\\n\\n5/16/2025 at 1:15:47 AM\\n\\nJust noticed Tinfoil runs Deepseek-R1 \\\"70b\\\". Technically this is not the original 671b Deepseek R1; it's just a Llama-70b trained by Deepseek R1 (called \\\"distillation\\\").\\nby kevinis\\n\\n5/15/2025 at 4:41:04 PM\\n\\nExcited to see someone finally doing this! I can imagine folks with sensitive model weights being especially interested.\\nDo you run into rate limits or other issues with TLS cert issuance? One problem we had when doing this before is that each spinup of the enclave must generate a fresh public key, so it needs a fresh, publicly trusted TLS cert. Do you have a workaround for that, or do you just have the enclaves run for long enough that it doesn’t matter?\\n\\nby blintz\\n\\n5/15/2025 at 4:48:24 PM\\n\\nWe actually run into the rate limit issue often particularly while spinning up new enclaves while debugging. We plan on moving to HPKE: https://www.rfc-editor.org/rfc/rfc9180.html over the next couple months. This will let us generate keys inside the enclave and encrypt the payload with the enclave specific keys, while letting us terminate TLS in a proxy outside the enclave. All the data is still encrypted to the enclave using HPKE (and still verifiable).\\nThis will let us fix the rate limit issue.\\n\\nby FrasiertheLion\\n\\n5/15/2025 at 8:26:50 PM\\n\\nNVIDIA shared open-source solutions for confidential AI already in mid-2024 https://developer.nvidia.com/blog/advancing-security-for-lar...\\nby ts6000\\n\\n5/15/2025 at 11:35:11 PM\\n\\nThis is fantastic. One rarely discussed use case is avoiding overzealous \\\"alignment\\\" - you want models to help advance your goals without arbitrary refusals for benign inputs. Why would I want Anthropic or OpenAI to have filtering authority over my queries? Consider OpenRouter ToS - \\\"you agree not to use the Service [..] in violation of any applicable AI Model Terms\\\": not sure if they actually enforce it but, of course, I'd want hardware security attestations that they can't monitor or censor my inputs. Open models should be like utilities - the provider supplies the raw capability (e.g., electrons or water or inference), while usage responsibility remains entirely with the end user.\\nby madars\\n\\n5/15/2025 at 11:51:29 PM\\n\\nThat's a big reason why we started Tinfoil and why we use it ourselves. I love the utilities analogy, something that is deeply integrated in business and personal use cases (like the Internet or AI) needs to have verifiable policies and options for data confidentiality.\\nby 3s\\n\\n5/15/2025 at 5:43:20 PM\\n\\nSo impressive - cloud AI that is verifiable with zero trust assumptions is going to be game-changing regardless of the industry application. Looks like it could be used by anyone for making anything trustworthy.\\nby meelvidushi\\n\\n5/15/2025 at 6:19:33 PM\\n\\n> with zero trust assumptions\\nIt's not that though. Not close. You are trusting the chip maker, whose process is secret (actually worse, it's almost certainly shared with the state).\\n\\nby jMyles\\n\\n5/15/2025 at 6:38:06 PM\\n\\nWe do have to trust the chip maker until open hardware catches up [1].\\n[1] https://news.ycombinator.com/item?id=43997856\\n\\nby 3s\\n\\n5/15/2025 at 6:42:53 PM\\n\\nEven if you had open hardware, how would you even know a chip you have sitting in front of you was fabricated correctly?\\nby davidczech\\n\\n5/15/2025 at 6:49:47 PM\\n\\nCheck out incredible work by Bunnie to make this possible at home https://www.bunniestudios.com/blog/2024/iris-infra-red-in-si...\\nby julesdrean\\n\\n5/16/2025 at 1:05:06 AM\\n\\nGreat work! I'm interested to know where the GPU servers are located. Are they in the US; do you run your own datacenter or rent servers on the hyperscalers?\\nby kevinis\\n\\n5/16/2025 at 1:12:52 AM\\n\\nYes, in the US right now. We don't run our own datacenters, though we sometimes consider it in a moment of frustration when the provider is not able to get the correct hardware configuration and firmware versions. Currently renting bare metal servers from neoclouds. We can't use hyperscalers because we need bare metal access to the machine.\\nby FrasiertheLion\\n\\n5/16/2025 at 1:18:38 AM\\n\\nThanks that's great to know. btw does a user need to trust Neoclouds in case they install malicious hardware/firmware/software on the servers?\\nby kevinis\\n\\n5/16/2025 at 1:20:44 AM\\n\\nThat's the best part, you don't. You only need to trust NVIDIA and AMD/Intel. Modulo difficult to mount physical attacks and side channels, which we wrote more about here: https://tinfoil.sh/blog/2025-05-15-side-channels\\nby FrasiertheLion\\n\\n5/15/2025 at 8:52:57 PM\\n\\n> the client fetches a signed document from the enclave which includes a hash of the running code signed\\nWhy couldn't the enclave claim to be running an older hash?\\n\\nby internetter\\n\\n5/15/2025 at 8:59:27 PM\\n\\nThis is enforced by the hardware (that’s where the root of trust goes back to NVDIA+AMD). The hardware will only send back signed enclave hashes of the code it’s running and cannot be coerced by us (or anyone else) into responding with a fake or old measurement.\\nby 3s\\n\\n5/15/2025 at 7:28:44 PM\\n\\nThats impressive, congrats. You've taken the \\\"verifiable security\\\" concept to the next level. I'm working on a similar concept, without \\\"verifiable\\\" part... trust remains to be built, but adding RAG ad fine tuned modelds to the use of open source LLMs, deployed in the cloud: https://gptsafe.ai/\\nby SebP\\n\\n5/15/2025 at 6:55:34 PM\\n\\nIs there a frozen client that someone could audit for assurance, then repeatedly use with your TEE-hosted backend?\\nIf instead users must use your web-served client code each time, you could subtly alter that over time or per-user, in ways unlikely to be detected by casual users – who'd then again be required to trust you (Tinfoil), rather than the goal on only having to trust the design & chip-manufacturer.\\n\\nby gojomo\\n\\n5/15/2025 at 7:01:45 PM\\n\\nYes, we have a customer who is indeed interested in having a frozen client for their app, which we're making possible. We currently have not frozen our client because we're in the early days and want to be able to iterate quickly on functionality. But happy to do so on a case-by-case basis for customers.\\nby FrasiertheLion\\n\\n5/15/2025 at 7:54:07 PM\\n\\n> rather than the goal on only having to trust the design & chip-manufacturer\\nIf you'd rather self-host, then the HazyResearch Lab at Stanford recently announced a FOSS e2ee implementation (\\\"Minions\\\") for Inference: https://hazyresearch.stanford.edu/blog/2025-05-12-security / https://github.com/HazyResearch/Minions\\n\\nby ignoramous\\n\\n5/15/2025 at 7:23:27 PM\\n\\n> https://docs.tinfoil.sh/verification/attestation-architectur...\\nI tried taking a look at your documentation, but the site search is very slow and laggy in Firefox.\\n\\nby offmycloud\\n\\n5/15/2025 at 7:39:22 PM\\n\\nInteresting, we haven't noticed that (on Firefox as well). We'll look into it!\\nby 3s\\n\\n5/15/2025 at 7:41:52 PM\\n\\nIt looks like it might be the blur effect in a VM with no Firefox video acceleration. Also, email to [email protected] (from \\\"contact\\\" link) just bounced back to me.\\nby offmycloud\\n\\n5/15/2025 at 7:46:45 PM\\n\\nAh we don't have [email protected] set up yet. Can you try [email protected]?\\nby FrasiertheLion\\n\\n5/16/2025 at 4:24:44 PM\\n\\nSet up *@ and sort it later. ask an intern to monitor that box after lunch for a while. Catchall. You probably know this, but for anyone else thinking of doing email for their business.\\nFor example if you do tools or RAG you probably ought have abuse@ as well, even though only 4 people will think to email that.\\n\\nby genewitch\\n\\n5/16/2025 at 8:54:34 PM\\n\\nHa we didn't think of that, thanks for the tip!\\nby FrasiertheLion\\n\\n5/15/2025 at 4:42:28 PM\\n\\nDoes the secure enclave also perform the TLS encryption on data leaving the enclave?\\nAlso, if you're decoding TLS on the enclave, wouldn't that imply that you're parsing HTTP and JSON on the GPU itself? Very interesting if true.\\n\\nby etaioinshrdlu\\n\\n5/15/2025 at 4:53:49 PM\\n\\nThe verified trust boundary extends from the CPU to GPU [1], and TLS encrypts all data to/from the enclave and client so we can't see anything in the clear.\\nHTTP parsing and application logic happens on the CPU like normal. The GPU runs CUDA just like any other app, after it's integrity is verified by the CPU. Data on the PCIe bus is encrypted between the CPU and GPU too.\\n\\n[1] https://github.com/NVIDIA/nvtrust/blob/main/guest_tools/atte...\\n\\nby natesales\\n\\n5/15/2025 at 5:08:10 PM\\n\\nCould you talk more about how how this works? I don't think linked article doesn't given enough detail on how the trust boundary extends from CPU to GPU.\\nDoes the CPU have the ability to see unencrypted data?\\n\\nby etaioinshrdlu\\n\\n5/15/2025 at 5:33:35 PM\\n\\nThe keys are generated on the CPU and never leave the enclave, but the data is decrypted on the CPU so it hits the registers in plaintext.\\nWhen the enclave starts, the CPU does a few things:\\n\\n1. The CPU does a key exchange with the GPU (in confidential compute mode [1]) to derive a key to encrypt data over PCIe\\n\\n2. The CPU verifies the integrity of the GPU against NVIDIA's root of trust [2]\\n\\n[1] https://developer.nvidia.com/blog/confidential-computing-on-...\\n\\n[2] https://github.com/tinfoilsh/cvmimage/blob/b65ced8796e8a8687...\\n\\nedit: formatting\\n\\nby natesales\\n\\n5/15/2025 at 5:19:36 PM\\n\\nYou're not terminating the TLS connection from the client anywhere besides the enclave? How do you load balance or front end all of this effectively?\\nby candiddevmike\\n\\n5/15/2025 at 5:28:54 PM\\n\\n>You're not terminating the TLS connection from the client anywhere besides the enclave?\\nYes.\\n\\n>How do you load balance or front end all of this effectively?\\n\\nWe don't, atleast not yet. That's why all our model endpoints have different subdomains. In the next couple months, we're planning to generate a keypair inside the enclave using HPKE that will be used to encrypt the data, as I described in this comment: https://news.ycombinator.com/item?id=43996849\\n\\nby FrasiertheLion\\n\\n5/16/2025 at 5:54:10 AM\\n\\nHow is running a model onprem more expensive than on the cloud? Are you including training costs?\\nEdit: perhaps because you don’t need the model to be available all the time? In that case yeah the cloud can be cheaper\\n\\nby ed_mercer\\n\\n5/15/2025 at 7:00:25 PM\\n\\nThis is an incredibly robust solution to a really pressing problem for a lot of individuals/orgs who want to use/deploy reasonably powerful LLMs without paying through the nose for hardware. Others have mentioned the hyperscalers have solutions that make some amount of sense (Azure confidential computing, AWS nitro enclaves) but if you read a bit more about Tinfoil, it is clear they want to operate with far less explicit user trust (and thus much better security). This team is setting the standard for provably private LLM inference, and to me, it makes other solutions seem half-baked by comparison. Props to this talented group of people.\\nby computerbuster\\n\\n5/15/2025 at 5:41:31 PM\\n\\nhasn’t iexec (french co) been doing this for years? what’s your competitive advantage or moat, considering they are the first-movers?\\nby leboshkibowl\\n\\n5/15/2025 at 5:47:33 PM\\n\\nTheir GTM doesn't include a $ in front of their company acronym.\\nI think there is similarity to https://www.anjuna.io/ and https://www.opaque.co/ here. I've heard of these, never iExec.\\n\\nby ramoz\\n\\n5/15/2025 at 6:09:02 PM\\n\\nCPU-based TEEs (AWS Nitro Enclaves, AMD SEV, Intel TDX) have been around for a few years, but aren’t widely used because they are more akin to primitives than fully baked security solutions. We are trying to make this as user friendly and self serve as possible, with full verifiability by open sourcing the entire server that runs inside the enclave. So far we have not found any end to end verifiably private solution on the market that we could just sign up for to try, which was a big reason we started Tinfoil in the first place. We also strongly believe that verifiably private AI should be the norm, so the more players in the space, the better because a missing piece is market awareness and convincing folks this is actually possible and real.\\nby FrasiertheLion\\n\\n5/15/2025 at 6:17:19 PM\\n\\nBeen building something along these lines for a while. At Qbix, we call it our QBOX. Full stack, using Nix for the base, and Nitro attestation. No SSH. We have the exact same approach — cron running and only downloading signed scripts and binaries from endpoints. But there is a lot more… Would be great to connect and maybe join forces.\\nWant to connect some time next Tuesday or Wednesday? https://calendly.com/qbix/meeting\\n\\nby EGreg\\n\\n5/15/2025 at 6:28:58 PM\\n\\nYes, excited to connect, scheduled a call! We used Nitro back in December when we were prototyping but moved to NVIDIA CC because we wanted to support LLMs.\\nby FrasiertheLion\\n\\n5/15/2025 at 8:11:31 PM\\n\\nHow do you see this compare to things like Amazon Bedrock, where it runs OSS in my own infra?\\nby japborst\\n\\n5/15/2025 at 8:21:45 PM\\n\\nBedrock has strong contractual guarantees, but it's still only a legal contract and runs on AWS infra. This is certainly okay for many use cases, we're trying to build for users who want verifiable privacy guarantees beyond legal contracts.\\nWe're also doing more than pure inference, and trying to work with other companies who want to provide their users additional verifiability and confidentiality guarantees by running their entire private data processing pipeline on our platform.\\n\\nby FrasiertheLion\\n\\n5/15/2025 at 4:43:13 PM\\n\\ngreat name. good idea if it works.\\nby danr4\\n\\n5/16/2025 at 8:27:37 AM\\n\\nWould it be possible to run something like vLLM or TensortRT-llm with tinfoil?\\nby tealcod\\n\\n5/16/2025 at 3:41:44 PM\\n\\nWe’re already using vllm as our inference server for our standard models. We can run whatever inference server for custom deployments.\\nby FrasiertheLion\\n\\n5/16/2025 at 8:19:30 PM\\n\\nTechnically my wife would be a perfect customer because we literally just prototyped your solution at home. But I'm confused.\\nFor context:\\n\\nMy wife does leadership coaching and recently used vanilla GPT-4o via ChatGPT to summarize a transcript of an hour-long conversation.\\n\\nThen, last weekend we thought... \\\"Hey, let's test local LLMs for more privacy control. The open source models must be pretty good in 2025.\\\"\\n\\nSo I installed Ollama + Open WebUI plus the models on a 128GB MacBook Pro.\\n\\nI am genuinely dumbfounded about the actual results we got today of comparing ChatGPT/GPT-4o vs. Llama4, Llama3.3, Llama3.2, DeepSeekR1 and Gemma.\\n\\nIn short: Compared to our reference GPT-4o output, none (as in NONE, zero, zilch, nil) of the above-mentioned open source models were able to create even a basic summary based on the exact same prompt + text.\\n\\nThe open source summaries were offensively bad. It felt like reading the most bland, generic and idiotic SEO slop I've read since I last used Google. None of the obvious topics were part of the summary. Just blah. I tested this with 5 models to boot!\\n\\nI'm not an OpenAI fan per se, but if this is truly OS/SOTA then, we shouldn't even mention Llama4 or the others in the same breath as the newer OpenAI models.\\n\\nWhat do you think?\\n\\nby interleave\\n\\n5/16/2025 at 8:45:06 PM\\n\\nOllama does heavily quantize models and has a very short context window by default, but this has not been my experience with unquantized, full context versions of Llama3.3 70B and particularly, Deepseek R1, and that is reflected in the benchmarks. For instance I used Deepseek R1 671B as my daily driver for several months, and it was at par with o1 and unquestionably better than GPT-4o (o3 is certainly better than all but typically we've seen opensource models catch up within 6-9 months).\\nPlease shoot me an email at [email protected], would love to work through your use cases.\\n\\nby FrasiertheLion\\n\\n5/17/2025 at 4:53:05 PM\\n\\nHey Tanya! Thank you for helping me understand the results better.\\nI just posted the results of another basic interview analysis (4o vs. Llama4) here: https://x.com/SpringStreetNYC/status/1923774145633849780\\n\\nTo your point: Do I understand correctly that, for example, by running the default model of Llama4 via ollama, the context window is very short even when the model's context is, like 10M. In order to \\\"unlock\\\" the full context version, I need to get the unquantized version.\\n\\nFor reference, here's what `ollama show llama4` returns: - parameters 108.6B # llama4:scount - context length 10485760 # 10M - embedding length 5120 - quantization Q4_K_M\\n\\nby interleave\\n\\n5/16/2025 at 5:58:26 AM\\n\\nHeh. I sold Tinfoil Security to synopsys in January 2020.\\nWe should chat. :)\\n\\nby borski\\n\\n5/16/2025 at 6:20:07 AM\\n\\nAye comrade, shot you an email :)\\nby FrasiertheLion\\n\\n5/16/2025 at 12:13:11 AM\\n\\nHere is a marketing campaign for you to prove that secure enclaves work.\\nHost a machine on the internet. Allow competitors to sign up to receive root ssh credentials. Offer a $10K prize if they are able to determine plaintext inputs and outputs over a given time period (say one month).\\n\\nA bit of a strawman, but a competition like this might help build confidence.\\n\\nby osigurdson\\n\\n5/16/2025 at 12:16:57 AM\\n\\nThat's exactly our plan for Defcon next year as Nate just mentioned: https://news.ycombinator.com/item?id=44000103\\nBut making it a public competition is a fantastic idea.\\n\\nby FrasiertheLion\\n\\n5/16/2025 at 5:08:34 AM\\n\\nAs a user, can I host the attestation server myself?\\nby tealcod\\n\\n5/16/2025 at 5:56:34 AM\\n\\nAll attestation verification happens client side. We have verifiers in Python [1] and Go [2] (which FFIs to our other SDKs like WASM and Swift). We push all the verification logic to the client so the verification process is entirely transparent and auditable.\\n[1] https://github.com/tinfoilsh/tinfoil-python [2] https://github.com/tinfoilsh/verifier\\n\\nby natesales\\n\\n5/15/2025 at 8:37:21 PM\\n\\nThis is a great concept but I think \\\"Enterprise-Ready Security\\\" and your competitive comparison chart are kind of misleading. Yes, zero trust is huge. But, virtually everyone who has a use case for max privacy AI, has that use case because of compliance and IP concerns. Enterprise-Ready Security doesn't mean sigstore or zero trust, it means you have both the security at a technical level as well as certification by an auditor that you do.\\nYou aren't enterprise ready because to address those concerns you need to get the laundry list of compliance certs: SOC 2:2, ISO 27k1/2 and 9k1, HIPPA, GDPR, CMMC, FedRAMP, NIST, etc.\\n\\nby cuuupid\\n\\n5/15/2025 at 8:41:54 PM\\n\\nWe're going through the audit process for SOC2 right now and we're planning on doing HIPAA soon\\nby 3s\\n\\n5/15/2025 at 8:16:26 PM\\n\\nI love the brand and logo\\nby binary132\\n\\n5/15/2025 at 4:29:17 PM\\n\\nAre you HIPAA compliant?\\nby Onavo\\n\\n5/15/2025 at 4:32:12 PM\\n\\nNot yet, we're about one week away from SOC2, will pursue HIPAA which is arguably easier next.\\nby FrasiertheLion\\n\\n5/16/2025 at 2:33:44 AM\\n\\nAlso curious about the potential users of your product, do you target individual users, small businesses, or large enterprises? Pursuing SOC2 and HIPPA make me think about the large ones; but aren't they already happy using hyperscalers?\\nNot to mention GCP and Azure both have confidential GPU offerings. How do you compete against them, as well as some startups mentioned in other comments like Edgeless Systems and Opaque Systems?\\n\\nby kevinis\\n\\n5/15/2025 at 5:57:59 PM\\n\\n[dead]\\nby curtisszmania\\n\\n5/15/2025 at 5:59:44 PM\\n\\n[flagged]\\nby valid_user_123\\n```\"},{\"role\":\"assistant\",\"mainText\":\"# 邮件内容总结\\n\\n这是一个关于Tinfoil（YC X25）产品发布的Hacker News讨论帖，发布于2025年5月15日。Tinfoil提供可验证隐私的云AI服务，使用可信执行环境(TEE)和保密计算技术。\\n\\n## 主要产品特点\\n- 提供可验证隐私的云AI推理服务\\n- 使用NVIDIA和AMD/Intel的保密计算技术\\n- 开源了运行在安全飞地(enclave)内的服务器代码\\n- 客户端可验证服务器代码的完整性\\n- 支持DeepSeek-R1等开源大语言模型\\n\\n## 技术原理\\n- 使用CPU和GPU的保密计算功能建立可信边界\\n- TLS加密终止在安全飞地内，数据在传输中和处理中都受到保护\\n- 提供客户端验证工具，可以验证服务器代码的完整性\\n- PCIe总线上CPU和GPU之间的数据也经过加密\\n- 开源了整个验证流程\\n\\n## 竞争与市场定位\\n- 与Azure、GCP等云服务商的保密计算服务有所区别\\n- 与Apple的Private Cloud Compute等技术相比有不同的信任假设\\n- 目标不是与Gemini、OpenAI等大型模型提供商竞争\\n- 专注于为需要隐私保证的企业和用户提供服务\\n\\n## 信任模型\\n- 用户需要信任硬件制造商(NVIDIA、AMD/Intel)\\n- 不需要信任Tinfoil或云服务提供商\\n- 比纯合约保证提供更强的隐私保证\\n- 未来可能转向完全同态加密(FHE)，但目前该技术尚不实用\\n\\n## 合规与安全\\n- 正在进行SOC2认证，即将完成\\n- 计划进行HIPAA合规认证\\n- 计划在DEFCON举办安全挑战，测试系统安全性\\n- 开源了验证工具，使验证过程透明可审计\\n\\n## 讨论中的主要问题\\n1. 与现有保密计算解决方案的区别\\n2. 对硬件制造商的信任问题\\n3. 开源模型与闭源模型的性能差距\\n4. 对物理攻击和侧信道攻击的防御\\n5. 商业模式和竞争策略\\n\\n讨论中许多参与者对这种可验证隐私的云AI解决方案表示兴趣，特别是在敏感数据处理和合规性要求高的行业。同时也有人质疑硬件信任链的安全性和开源模型的性能表现。\"}]"
  }
]

Response:

Summarize - Tinfoil AI

Model: claude-3-7-sonnet-202502192025-06-24 12:32:33

Context:

[
  {
    "role": "user",
    "content": "帮我总结下邮件内容\n\n```\nalt.hn\n5/15/2025 at 4:19:00 PM\n\nLaunch HN: Tinfoil (YC X25): Verifiable Privacy for Cloud AI\nby FrasiertheLion\n\n5/15/2025 at 6:52:24 PM\n\nLooks great. Not sure how big the market is between \"need max privacy, need on-prem\" and \"don't care, just use what is cheap/popular\" tho.\nCan you talk about how this relates to / is different / is differentiated from what Apple claimed to do during their last WWDC? They called it \"private cloud compute\". (To be clear, after 11 months, this is still \"announced\", with no implementation anywhere, as far as I can see.)\n\nHere is their blog post on Apple Security, dated June 10: https://security.apple.com/blog/private-cloud-compute/\n\nEDIT: JUST found the tinfoil blog post on exactly this topic. https://tinfoil.sh/blog/2025-01-30-how-do-we-compare\n\nby sigmaisaletter\n\n5/16/2025 at 2:13:36 AM\n\nAnecdotal, but I work at a company offering an SMB product with LLM features. One of the first questions asked on any demo or sales call is what the privacy model for the LLM is, how the data is used, who has access to it, and can those features be disabled.\nby _heimdall\n\n5/15/2025 at 7:10:02 PM\n\nPrivate Cloud Compute has been in use since iOS 18 released.\nby davidczech\n\n5/15/2025 at 9:29:40 PM\n\nIt seems that PCC indeed went live with 18.1 - tho not in Europe (which is where I am located). Thanks for the heads up, I will look into this further.\nby sigmaisaletter\n\n5/16/2025 at 12:10:54 PM\n\nThere are a few stories on the 'max privacy' stuff; one of the stories goes that you have two companies each with something private that needs to combine their stuff without letting the other see it; for example a bank with customer transactions and a company with analytics software they don't want to share; a system like this lets the bank put their transaction data through that analytics software without anyone being able to see the transaction data or the software. The next level on that is where two banks need to combine the transaction data to spot fraud, where you've now got three parties involved on one server.\nby trebligdivad\n\n5/15/2025 at 8:19:51 PM\n\nCompanies like Edgeless Systems have been building open-source confidential computing for cloud and AI for years, they are open-source, and have published in 2024 how they compare to Apple Private Cloud Compute. https://www.edgeless.systems/blog/apple-private-cloud-comput...\nby ts6000\n\n5/15/2025 at 8:05:14 PM\n\nPrivate Cloud Compute has been live in production for 8 months\nby DrBenCarson\n\n5/15/2025 at 9:29:47 PM\n\nIt seems that PCC indeed went live with 18.1 - tho not in Europe (which is where I am located). Thanks for the heads up, I will look into this further.\nby sigmaisaletter\n\n5/15/2025 at 5:58:40 PM\n\nHow large do you wager your moat to be? Confidential computing is something all major cloud providers either have or are about to have and from there it's a very small step to offer LLM-s under the same umbrella. First mover advantage is of course considerable, but I can't help but feel that this market will very quickly be swallowed by the hyperscalers.\nby Etheryte\n\n5/15/2025 at 10:57:32 PM\n\nCloud providers aren't going to care too much about this.\nI have worked for many enterprise companies e.g. banks who are trialling AI and none of them have any use for something like this. Because the entire foundation of the IT industry is based on trusting the privacy and security policies of Azure, AWS and GCP. And in the decades since they've been around not heard of a single example of them breaking this.\n\nThe proposition here is to tell a company that they can trust Azure with their banking websites, identity services and data engineering workloads but not for their model services. It just doesn't make any sense. And instead I should trust a YC startup who statistically is going to be gone in a year and will likely have their own unique set of security and privacy issues.\n\nAlso you have the issue of smaller sized open source models e.g. DeepSeek R1 lagging far behind the bigger ones and so you're giving me some unnecessary privacy attestation at the expense of a model that will give me far better accuracy and performance.\n\nby threeseed\n\n5/16/2025 at 12:48:50 PM\n\n> Cloud providers aren't going to care too much about this. ... [E]nterprise companies e.g. banks ... and none of them have any use for something like this.\nAs former CTO of world's largest bank and cloud architect at world's largest hedge fund, this is exactly opposite of my experience with both regulated finance enterprises and the CSPs vying to serve them.\n\nThe entire foundation of the IT industry is based on trusting the privacy and security policies of Azure, AWS and GCP. And in the decades since they've been around not heard of a single example of them breaking this.\n\nOn the contrary, many global banks design for the assumption the \"CSP is hostile\". What happened to Coinbase's customers the past few months shows why your vendor's insider threat is your threat and your customers' threat.\n\nGranted, this annoys CSPs who wish regulators would just let banks \"adopt\" the CSP's controls and call it a day.\n\nUnfortunately for CSP sales teams — certainly this could change with recent regulator policy changes — the regulator wins. Until very recently, only one CSP offered controls sufficient to assure your own data privacy beyond a CSP's pinky-swears. AWS Nitro Enclaves can provide a key component in that assurance, using deployment models such as tinfoil.\n\nby Terretta\n\n5/15/2025 at 6:12:32 PM\n\nBeing gobbled by the hyperscalers may well be the plan. Reasonable bet.\nby itsafarqueue\n\n5/16/2025 at 1:10:58 AM\n\nGCP has confidential VMs with H100 GPUs; I'm not sure if Google would be interested. And they get huge discount buying GPUs in bulk. The trade-off between cost and privacy is obvious for most users imo.\nby kevinis\n\n5/15/2025 at 6:34:04 PM\n\nThis. Big tech providers already offer confidential inference today.\nby ATechGuy\n\n5/15/2025 at 6:44:25 PM\n\nYes Azure has! They have very different trust assumptions though. We wrote about this here https://tinfoil.sh/blog/2025-01-30-how-do-we-compare\nby julesdrean\n\n5/15/2025 at 6:52:22 PM\n\nLast I checked it was only Azure offering the Nvidia specific confidential compute extensions, I'm likely out of date - a quick Google was inconclusive.\nHave GCP and AWS started offering this for GPUs?\n\nby mnahkies\n\n5/15/2025 at 7:16:55 PM\n\nGCP, yes: https://cloud.google.com/confidential-computing/confidential...\nby candiddevmike\n\n5/15/2025 at 7:37:49 PM\n\nAzure and GCP offer Confidential VMs which removes trust from the cloud providers. We’re trying to also remove trust in the service provider (aka ourselves). One example is that when you use Azure or GCP, by default, the service operator can SSH into the VM. We cannot SSH into our inference server and you can check that’s true.\nby julesdrean\n\n5/15/2025 at 11:03:05 PM\n\nBut nobody wants you as a service provider. Everyone wants to have Gemini, OpenAI etc which are significantly better than the far smaller and less capable model you will be able to afford to host.\nAnd you make this claim that the cloud provider can SSH into the VM but (a) nobody serious exposes SSH ports in Production and (b) there is no documented evidence of this ever happening.\n\nby threeseed\n\n5/15/2025 at 11:31:53 PM\n\nWe're not competing with Gemini or OpenAI or the big cloud providers. For instance, Google is partnering with NVIDIA to ship Gemini on-prem to regulated industries in a CC environment to protect their model weights as well as for additional data privacy on-prem: https://blogs.nvidia.com/blog/google-cloud-next-agentic-ai-r...\nWe're simply trying to bring similar capabilities to other companies. Inference is just our first product.\n\n>cloud provider can SSH into the VM\n\nThe point we were making was that CC was traditionally used to remove trust from cloud providers, but not the application provider. We are further removing trust from ourselves (as the application provider), and we can enable our customers (who could be other startups or neoclouds) to remove trust from themselves and prove that to their customers.\n\nby FrasiertheLion\n\n5/15/2025 at 11:55:46 PM\n\nYou are providing the illusion of trust though.\nThere are a multitude of components between my app and your service. You have secured one of them arguably the least important. But you can't provide any guarantees over say your API server that my requests are going through. Or your networking stack which someone e.g. a government could MITM.\n\nby threeseed\n\n5/16/2025 at 12:19:20 AM\n\nI don't know anything about \"secure enclaves\" but I assume that this part is sorted out. It should be possible to use http with it I imagine. If not, yeah it is totally dumb from a conceptual standpoint.\nby osigurdson\n\n5/15/2025 at 6:17:24 PM\n\nConfidential computing as a technology will become (and should be) commoditized, so the value add comes down to security and UX. We don’t want to be a confidential computing company, we want to use the right tool for the job of building private & verifiable AI. If that becomes FHE in a few years, then we will use that. We are starting with easy-to-use inference, but our goal of having any AI application be provably private\nby 3s\n\n5/16/2025 at 12:07:29 PM\n\nI suspect Nvidia have done a lot of the heavy lifting to make this work; but it's not that trivial to wire the CPU and GPU confidential compute together.\nby trebligdivad\n\n5/15/2025 at 6:12:16 PM\n\nDoes this not require one to trust the hardware? I'm not an expert in hardware root of trust, etc, but if Intel (or whatever chip maker) decides to just sign code that doesn't do what they say it does (coerced or otherwise) or someone finds a vuln; would that not defeat the whole purpose?\nI'm not entirely sure this is different than \"security by contract\", except the contracts get bigger and have more technology around them?\n\nby amanda99\n\n5/15/2025 at 6:29:00 PM\n\nWe have to trust the hardware manufacturer (Intel/AMD/NVIDIA) designed their chips to execute the instructions we inspect, so we're assuming trust in vendor silicon either way.\nThe real benefit of confidential computing is to extend that trust to the source code too (the inference server, OS, firmware).\n\nMaybe one day we’ll have truly open hardware ;)\n\nby natesales\n\n5/15/2025 at 8:34:37 PM\n\nHi Nate. Routinely your various networking-related FOSS tools. Surprising to see you now work in the AI infrastructure space let alone co-founding a startup funded by YC! Tinfoil looks über neat. All the best (:\n> Maybe one day we'll have truly open hardware\n\nAt least the RoT/SE if nothing else: https://opentitan.org/\n\nby ignoramous\n\n5/15/2025 at 9:00:36 PM\n\nLove Open Titan! RISC-V all the way babe! The team is bunker: several of my labmates now work there\nby julesdrean\n\n5/16/2025 at 4:08:20 PM\n\nIsn't this not the case for FHE? (I understand that FHE is not practically viable as you guys mention in the OP.)\nby perching_aix\n\n5/16/2025 at 4:55:55 PM\n\nYeah not the case for FHE. But yes, not practically viable. We would be happy to switch as soon as it is.\nby FrasiertheLion\n\n5/15/2025 at 9:04:21 PM\n\nI agree, it's lifting trust to the manufacturer (which could still be an improvement over the cloud status quo).\nAnother (IMO more likely) scenario is someone finds a hardware vulnerability (or leaked signing keys) that let's them achieve a similar outcome.\n\nby rkagerer\n\n5/15/2025 at 6:38:45 PM\n\nThe only way to guarantee privacy in cloud computing is via homorphic encryption.\nThis approach relies too much on trust.\n\nIf you have data you are seriously sensitive about, its better for you to run models locally on air gapped instances.\n\nIf you think this is an overkill, just see what happened to coinbase of recent. [0]\n\n[0]: https://www.cnbc.com/2025/05/15/coinbase-says-hackers-bribed...\n\nby max_\n\n5/15/2025 at 6:44:11 PM\n\nYeah, totally agree with you. We would love to use FHE as soon as it's practical. And if you have the money and infra expertise to deploy air gapped LLMs locally, you should absolutely do that. We're trying to do the best we can with today's technology, in a way that is cheap and accessible to most people.\nby FrasiertheLion\n\n5/15/2025 at 11:50:47 PM\n\n> The only way to guarantee privacy in cloud computing is via homorphic encryption\nNo. The only way is to not use cloud computing at all and go on-premise.\n\nWhich is what companies around the world do today for security or privacy critical workloads.\n\nby threeseed\n\n5/16/2025 at 12:54:35 PM\n\n> The only way is to not use cloud computing at all and go on-premise.\nThis point of view may be based on a lack of information about how global finance handles security and privacy critical workloads in high-end cloud.\n\nGlobal banks and the CSPs that serve them have by and large solved this problem by the late 2010s - early 2020s.\n\nWhile much of the work is not published, you can look for presentations at AWS reInvent from e.g. Goldman Sachs or others willing to share about it, talking about cryptographic methods, enclaves, formal reasoning over not just code but things like reachability, and so on, to see the edges of what's being done in this space.\n\nby Terretta\n\n5/15/2025 at 8:44:00 PM\n\nTinfoil hat on: say you are compelled to execute a FISA warrant and access the LLM data, is it technically possible? What about an Australian or UK style \"please add a backdoor\".\nI see you have to trust NVidia etc. so maybe there are such backdoors.\n\nby coolcase\n\n5/15/2025 at 10:43:47 PM\n\nAn attacker would need to compromise our build pipeline to publish a backdoored VM image [1] and extract key material to forge an attestation from the hardware [2]. The build process publishes a hash of the code to Sigstore’s transparency log [3], which would make the attack auditable.\nThat said, a sufficiently resourced attacker wouldn’t need to inject a backdoor at all. If the attacker already possesses the keys (e.g. the attacker IS the hardware manufacturer, or they’ve coerced the manufacturer to hand the keys over), then they would just need to gain access to the host server (which we control) to get access to the hypervisor, then use their keys to read memory or launch a new enclave with a forged attestation. We're planning on writing a much more detailed blog post about \"how to hack ourselves\" in the future.\n\nWe actually plan to do an experiment at DEFCON, likely next year where we gives ssh access to a test machine running the enclave and have people try to exfiltrate data from inside the enclave while keeping the machine running.\n\n[1] https://github.com/tinfoilsh/cvmimage\n\n[2] https://arxiv.org/abs/2108.04575\n\n[3] https://github.com/tinfoilsh/cvmimage/attestations\n\nby natesales\n\n5/15/2025 at 9:24:19 PM\n\nWhat's your revenue model?\nThe pricing page implies you're basically reselling access to confidential-wrapped AI instances.\n\nSince you rightly open-sourced the code (AGPL) is there anything stopping the cloud vendors from running and selling access to their own instances of your server-side magic?\n\nIs your secret sauce the tooling to spin up and manage instances and ease customer UX? Do you aim to attract an ecosystem of turnkey, confidential applications running on your platform?\n\nDo you envision an exit strategy that sells said secret sauce and customers to a cloud provider or confidential computing middleware provider?\n\nPs. Congrats on the launch.\n\nby rkagerer\n\n5/15/2025 at 9:51:12 PM\n\n>Since you rightly open-sourced the code (AGPL) is there anything stopping the cloud vendors from running and selling access to their own instances of your server-side magic?\nSure they can do that. Despite being open source, CC-mode on GPUs is quite difficult to work with especially when you start thinking about secrets management, observability etc, so we’d actually like to work with smaller cloud providers who want to provide this as a service and become competitive with the big clouds.\n\n>Is your secret sauce the tooling to spin up and manage instances and ease customer UX?\n\nPretty much. Confidential computing has been around a while, and we still don’t see widespread adoption of it, largely because of the difficulty. If we're successful, we absolutely expect there to be a healthy ecosystem of competitors both cloud provider and startup.\n\n>Do you envision an exit strategy that sells that secret sauce to a cloud provider or confidential computing middleware provider?\n\nWe’re not really trying to be a confidential computing provider, but more so, a verifiably private layer for AI. Which means we will try to make integration points as seamless as possible. For inference, that meant OpenAI API compatible client SDKs, we will eventually do the same for training/post-training, or MCP/OpenAI Agents SDK, etc. We want our integration points to be closely compatible with existing pipelines.\n\nby FrasiertheLion\n\n5/15/2025 at 11:49:59 PM\n\n> Confidential computing has been around a while, and we still don’t see widespread adoption of it, largely because of the difficulty\nThis is not the reason at all. Complexity and difficult are inherent to large companies.\n\nIt's because it is a very low priority in an environment where for example there are tens of thousands of libraries in use, dozens of which will be in Production with active CVEs. And there are many examples of similar security and risk management issues that companies have to deal with.\n\nWorrying about the integrity of the hardware or not trusting my cloud provider who has all my data in their S3 buckets anyway (which is encrypted using their keys) is not high on my list of concerns. And if it were I would be simply running on-premise anyway.\n\nby threeseed\n\n5/16/2025 at 1:15:47 AM\n\nJust noticed Tinfoil runs Deepseek-R1 \"70b\". Technically this is not the original 671b Deepseek R1; it's just a Llama-70b trained by Deepseek R1 (called \"distillation\").\nby kevinis\n\n5/15/2025 at 4:41:04 PM\n\nExcited to see someone finally doing this! I can imagine folks with sensitive model weights being especially interested.\nDo you run into rate limits or other issues with TLS cert issuance? One problem we had when doing this before is that each spinup of the enclave must generate a fresh public key, so it needs a fresh, publicly trusted TLS cert. Do you have a workaround for that, or do you just have the enclaves run for long enough that it doesn’t matter?\n\nby blintz\n\n5/15/2025 at 4:48:24 PM\n\nWe actually run into the rate limit issue often particularly while spinning up new enclaves while debugging. We plan on moving to HPKE: https://www.rfc-editor.org/rfc/rfc9180.html over the next couple months. This will let us generate keys inside the enclave and encrypt the payload with the enclave specific keys, while letting us terminate TLS in a proxy outside the enclave. All the data is still encrypted to the enclave using HPKE (and still verifiable).\nThis will let us fix the rate limit issue.\n\nby FrasiertheLion\n\n5/15/2025 at 8:26:50 PM\n\nNVIDIA shared open-source solutions for confidential AI already in mid-2024 https://developer.nvidia.com/blog/advancing-security-for-lar...\nby ts6000\n\n5/15/2025 at 11:35:11 PM\n\nThis is fantastic. One rarely discussed use case is avoiding overzealous \"alignment\" - you want models to help advance your goals without arbitrary refusals for benign inputs. Why would I want Anthropic or OpenAI to have filtering authority over my queries? Consider OpenRouter ToS - \"you agree not to use the Service [..] in violation of any applicable AI Model Terms\": not sure if they actually enforce it but, of course, I'd want hardware security attestations that they can't monitor or censor my inputs. Open models should be like utilities - the provider supplies the raw capability (e.g., electrons or water or inference), while usage responsibility remains entirely with the end user.\nby madars\n\n5/15/2025 at 11:51:29 PM\n\nThat's a big reason why we started Tinfoil and why we use it ourselves. I love the utilities analogy, something that is deeply integrated in business and personal use cases (like the Internet or AI) needs to have verifiable policies and options for data confidentiality.\nby 3s\n\n5/15/2025 at 5:43:20 PM\n\nSo impressive - cloud AI that is verifiable with zero trust assumptions is going to be game-changing regardless of the industry application. Looks like it could be used by anyone for making anything trustworthy.\nby meelvidushi\n\n5/15/2025 at 6:19:33 PM\n\n> with zero trust assumptions\nIt's not that though. Not close. You are trusting the chip maker, whose process is secret (actually worse, it's almost certainly shared with the state).\n\nby jMyles\n\n5/15/2025 at 6:38:06 PM\n\nWe do have to trust the chip maker until open hardware catches up [1].\n[1] https://news.ycombinator.com/item?id=43997856\n\nby 3s\n\n5/15/2025 at 6:42:53 PM\n\nEven if you had open hardware, how would you even know a chip you have sitting in front of you was fabricated correctly?\nby davidczech\n\n5/15/2025 at 6:49:47 PM\n\nCheck out incredible work by Bunnie to make this possible at home https://www.bunniestudios.com/blog/2024/iris-infra-red-in-si...\nby julesdrean\n\n5/16/2025 at 1:05:06 AM\n\nGreat work! I'm interested to know where the GPU servers are located. Are they in the US; do you run your own datacenter or rent servers on the hyperscalers?\nby kevinis\n\n5/16/2025 at 1:12:52 AM\n\nYes, in the US right now. We don't run our own datacenters, though we sometimes consider it in a moment of frustration when the provider is not able to get the correct hardware configuration and firmware versions. Currently renting bare metal servers from neoclouds. We can't use hyperscalers because we need bare metal access to the machine.\nby FrasiertheLion\n\n5/16/2025 at 1:18:38 AM\n\nThanks that's great to know. btw does a user need to trust Neoclouds in case they install malicious hardware/firmware/software on the servers?\nby kevinis\n\n5/16/2025 at 1:20:44 AM\n\nThat's the best part, you don't. You only need to trust NVIDIA and AMD/Intel. Modulo difficult to mount physical attacks and side channels, which we wrote more about here: https://tinfoil.sh/blog/2025-05-15-side-channels\nby FrasiertheLion\n\n5/15/2025 at 8:52:57 PM\n\n> the client fetches a signed document from the enclave which includes a hash of the running code signed\nWhy couldn't the enclave claim to be running an older hash?\n\nby internetter\n\n5/15/2025 at 8:59:27 PM\n\nThis is enforced by the hardware (that’s where the root of trust goes back to NVDIA+AMD). The hardware will only send back signed enclave hashes of the code it’s running and cannot be coerced by us (or anyone else) into responding with a fake or old measurement.\nby 3s\n\n5/15/2025 at 7:28:44 PM\n\nThats impressive, congrats. You've taken the \"verifiable security\" concept to the next level. I'm working on a similar concept, without \"verifiable\" part... trust remains to be built, but adding RAG ad fine tuned modelds to the use of open source LLMs, deployed in the cloud: https://gptsafe.ai/\nby SebP\n\n5/15/2025 at 6:55:34 PM\n\nIs there a frozen client that someone could audit for assurance, then repeatedly use with your TEE-hosted backend?\nIf instead users must use your web-served client code each time, you could subtly alter that over time or per-user, in ways unlikely to be detected by casual users – who'd then again be required to trust you (Tinfoil), rather than the goal on only having to trust the design & chip-manufacturer.\n\nby gojomo\n\n5/15/2025 at 7:01:45 PM\n\nYes, we have a customer who is indeed interested in having a frozen client for their app, which we're making possible. We currently have not frozen our client because we're in the early days and want to be able to iterate quickly on functionality. But happy to do so on a case-by-case basis for customers.\nby FrasiertheLion\n\n5/15/2025 at 7:54:07 PM\n\n> rather than the goal on only having to trust the design & chip-manufacturer\nIf you'd rather self-host, then the HazyResearch Lab at Stanford recently announced a FOSS e2ee implementation (\"Minions\") for Inference: https://hazyresearch.stanford.edu/blog/2025-05-12-security / https://github.com/HazyResearch/Minions\n\nby ignoramous\n\n5/15/2025 at 7:23:27 PM\n\n> https://docs.tinfoil.sh/verification/attestation-architectur...\nI tried taking a look at your documentation, but the site search is very slow and laggy in Firefox.\n\nby offmycloud\n\n5/15/2025 at 7:39:22 PM\n\nInteresting, we haven't noticed that (on Firefox as well). We'll look into it!\nby 3s\n\n5/15/2025 at 7:41:52 PM\n\nIt looks like it might be the blur effect in a VM with no Firefox video acceleration. Also, email to [email protected] (from \"contact\" link) just bounced back to me.\nby offmycloud\n\n5/15/2025 at 7:46:45 PM\n\nAh we don't have [email protected] set up yet. Can you try [email protected]?\nby FrasiertheLion\n\n5/16/2025 at 4:24:44 PM\n\nSet up *@ and sort it later. ask an intern to monitor that box after lunch for a while. Catchall. You probably know this, but for anyone else thinking of doing email for their business.\nFor example if you do tools or RAG you probably ought have abuse@ as well, even though only 4 people will think to email that.\n\nby genewitch\n\n5/16/2025 at 8:54:34 PM\n\nHa we didn't think of that, thanks for the tip!\nby FrasiertheLion\n\n5/15/2025 at 4:42:28 PM\n\nDoes the secure enclave also perform the TLS encryption on data leaving the enclave?\nAlso, if you're decoding TLS on the enclave, wouldn't that imply that you're parsing HTTP and JSON on the GPU itself? Very interesting if true.\n\nby etaioinshrdlu\n\n5/15/2025 at 4:53:49 PM\n\nThe verified trust boundary extends from the CPU to GPU [1], and TLS encrypts all data to/from the enclave and client so we can't see anything in the clear.\nHTTP parsing and application logic happens on the CPU like normal. The GPU runs CUDA just like any other app, after it's integrity is verified by the CPU. Data on the PCIe bus is encrypted between the CPU and GPU too.\n\n[1] https://github.com/NVIDIA/nvtrust/blob/main/guest_tools/atte...\n\nby natesales\n\n5/15/2025 at 5:08:10 PM\n\nCould you talk more about how how this works? I don't think linked article doesn't given enough detail on how the trust boundary extends from CPU to GPU.\nDoes the CPU have the ability to see unencrypted data?\n\nby etaioinshrdlu\n\n5/15/2025 at 5:33:35 PM\n\nThe keys are generated on the CPU and never leave the enclave, but the data is decrypted on the CPU so it hits the registers in plaintext.\nWhen the enclave starts, the CPU does a few things:\n\n1. The CPU does a key exchange with the GPU (in confidential compute mode [1]) to derive a key to encrypt data over PCIe\n\n2. The CPU verifies the integrity of the GPU against NVIDIA's root of trust [2]\n\n[1] https://developer.nvidia.com/blog/confidential-computing-on-...\n\n[2] https://github.com/tinfoilsh/cvmimage/blob/b65ced8796e8a8687...\n\nedit: formatting\n\nby natesales\n\n5/15/2025 at 5:19:36 PM\n\nYou're not terminating the TLS connection from the client anywhere besides the enclave? How do you load balance or front end all of this effectively?\nby candiddevmike\n\n5/15/2025 at 5:28:54 PM\n\n>You're not terminating the TLS connection from the client anywhere besides the enclave?\nYes.\n\n>How do you load balance or front end all of this effectively?\n\nWe don't, atleast not yet. That's why all our model endpoints have different subdomains. In the next couple months, we're planning to generate a keypair inside the enclave using HPKE that will be used to encrypt the data, as I described in this comment: https://news.ycombinator.com/item?id=43996849\n\nby FrasiertheLion\n\n5/16/2025 at 5:54:10 AM\n\nHow is running a model onprem more expensive than on the cloud? Are you including training costs?\nEdit: perhaps because you don’t need the model to be available all the time? In that case yeah the cloud can be cheaper\n\nby ed_mercer\n\n5/15/2025 at 7:00:25 PM\n\nThis is an incredibly robust solution to a really pressing problem for a lot of individuals/orgs who want to use/deploy reasonably powerful LLMs without paying through the nose for hardware. Others have mentioned the hyperscalers have solutions that make some amount of sense (Azure confidential computing, AWS nitro enclaves) but if you read a bit more about Tinfoil, it is clear they want to operate with far less explicit user trust (and thus much better security). This team is setting the standard for provably private LLM inference, and to me, it makes other solutions seem half-baked by comparison. Props to this talented group of people.\nby computerbuster\n\n5/15/2025 at 5:41:31 PM\n\nhasn’t iexec (french co) been doing this for years? what’s your competitive advantage or moat, considering they are the first-movers?\nby leboshkibowl\n\n5/15/2025 at 5:47:33 PM\n\nTheir GTM doesn't include a $ in front of their company acronym.\nI think there is similarity to https://www.anjuna.io/ and https://www.opaque.co/ here. I've heard of these, never iExec.\n\nby ramoz\n\n5/15/2025 at 6:09:02 PM\n\nCPU-based TEEs (AWS Nitro Enclaves, AMD SEV, Intel TDX) have been around for a few years, but aren’t widely used because they are more akin to primitives than fully baked security solutions. We are trying to make this as user friendly and self serve as possible, with full verifiability by open sourcing the entire server that runs inside the enclave. So far we have not found any end to end verifiably private solution on the market that we could just sign up for to try, which was a big reason we started Tinfoil in the first place. We also strongly believe that verifiably private AI should be the norm, so the more players in the space, the better because a missing piece is market awareness and convincing folks this is actually possible and real.\nby FrasiertheLion\n\n5/15/2025 at 6:17:19 PM\n\nBeen building something along these lines for a while. At Qbix, we call it our QBOX. Full stack, using Nix for the base, and Nitro attestation. No SSH. We have the exact same approach — cron running and only downloading signed scripts and binaries from endpoints. But there is a lot more… Would be great to connect and maybe join forces.\nWant to connect some time next Tuesday or Wednesday? https://calendly.com/qbix/meeting\n\nby EGreg\n\n5/15/2025 at 6:28:58 PM\n\nYes, excited to connect, scheduled a call! We used Nitro back in December when we were prototyping but moved to NVIDIA CC because we wanted to support LLMs.\nby FrasiertheLion\n\n5/15/2025 at 8:11:31 PM\n\nHow do you see this compare to things like Amazon Bedrock, where it runs OSS in my own infra?\nby japborst\n\n5/15/2025 at 8:21:45 PM\n\nBedrock has strong contractual guarantees, but it's still only a legal contract and runs on AWS infra. This is certainly okay for many use cases, we're trying to build for users who want verifiable privacy guarantees beyond legal contracts.\nWe're also doing more than pure inference, and trying to work with other companies who want to provide their users additional verifiability and confidentiality guarantees by running their entire private data processing pipeline on our platform.\n\nby FrasiertheLion\n\n5/15/2025 at 4:43:13 PM\n\ngreat name. good idea if it works.\nby danr4\n\n5/16/2025 at 8:27:37 AM\n\nWould it be possible to run something like vLLM or TensortRT-llm with tinfoil?\nby tealcod\n\n5/16/2025 at 3:41:44 PM\n\nWe’re already using vllm as our inference server for our standard models. We can run whatever inference server for custom deployments.\nby FrasiertheLion\n\n5/16/2025 at 8:19:30 PM\n\nTechnically my wife would be a perfect customer because we literally just prototyped your solution at home. But I'm confused.\nFor context:\n\nMy wife does leadership coaching and recently used vanilla GPT-4o via ChatGPT to summarize a transcript of an hour-long conversation.\n\nThen, last weekend we thought... \"Hey, let's test local LLMs for more privacy control. The open source models must be pretty good in 2025.\"\n\nSo I installed Ollama + Open WebUI plus the models on a 128GB MacBook Pro.\n\nI am genuinely dumbfounded about the actual results we got today of comparing ChatGPT/GPT-4o vs. Llama4, Llama3.3, Llama3.2, DeepSeekR1 and Gemma.\n\nIn short: Compared to our reference GPT-4o output, none (as in NONE, zero, zilch, nil) of the above-mentioned open source models were able to create even a basic summary based on the exact same prompt + text.\n\nThe open source summaries were offensively bad. It felt like reading the most bland, generic and idiotic SEO slop I've read since I last used Google. None of the obvious topics were part of the summary. Just blah. I tested this with 5 models to boot!\n\nI'm not an OpenAI fan per se, but if this is truly OS/SOTA then, we shouldn't even mention Llama4 or the others in the same breath as the newer OpenAI models.\n\nWhat do you think?\n\nby interleave\n\n5/16/2025 at 8:45:06 PM\n\nOllama does heavily quantize models and has a very short context window by default, but this has not been my experience with unquantized, full context versions of Llama3.3 70B and particularly, Deepseek R1, and that is reflected in the benchmarks. For instance I used Deepseek R1 671B as my daily driver for several months, and it was at par with o1 and unquestionably better than GPT-4o (o3 is certainly better than all but typically we've seen opensource models catch up within 6-9 months).\nPlease shoot me an email at [email protected], would love to work through your use cases.\n\nby FrasiertheLion\n\n5/17/2025 at 4:53:05 PM\n\nHey Tanya! Thank you for helping me understand the results better.\nI just posted the results of another basic interview analysis (4o vs. Llama4) here: https://x.com/SpringStreetNYC/status/1923774145633849780\n\nTo your point: Do I understand correctly that, for example, by running the default model of Llama4 via ollama, the context window is very short even when the model's context is, like 10M. In order to \"unlock\" the full context version, I need to get the unquantized version.\n\nFor reference, here's what `ollama show llama4` returns: - parameters 108.6B # llama4:scount - context length 10485760 # 10M - embedding length 5120 - quantization Q4_K_M\n\nby interleave\n\n5/16/2025 at 5:58:26 AM\n\nHeh. I sold Tinfoil Security to synopsys in January 2020.\nWe should chat. :)\n\nby borski\n\n5/16/2025 at 6:20:07 AM\n\nAye comrade, shot you an email :)\nby FrasiertheLion\n\n5/16/2025 at 12:13:11 AM\n\nHere is a marketing campaign for you to prove that secure enclaves work.\nHost a machine on the internet. Allow competitors to sign up to receive root ssh credentials. Offer a $10K prize if they are able to determine plaintext inputs and outputs over a given time period (say one month).\n\nA bit of a strawman, but a competition like this might help build confidence.\n\nby osigurdson\n\n5/16/2025 at 12:16:57 AM\n\nThat's exactly our plan for Defcon next year as Nate just mentioned: https://news.ycombinator.com/item?id=44000103\nBut making it a public competition is a fantastic idea.\n\nby FrasiertheLion\n\n5/16/2025 at 5:08:34 AM\n\nAs a user, can I host the attestation server myself?\nby tealcod\n\n5/16/2025 at 5:56:34 AM\n\nAll attestation verification happens client side. We have verifiers in Python [1] and Go [2] (which FFIs to our other SDKs like WASM and Swift). We push all the verification logic to the client so the verification process is entirely transparent and auditable.\n[1] https://github.com/tinfoilsh/tinfoil-python [2] https://github.com/tinfoilsh/verifier\n\nby natesales\n\n5/15/2025 at 8:37:21 PM\n\nThis is a great concept but I think \"Enterprise-Ready Security\" and your competitive comparison chart are kind of misleading. Yes, zero trust is huge. But, virtually everyone who has a use case for max privacy AI, has that use case because of compliance and IP concerns. Enterprise-Ready Security doesn't mean sigstore or zero trust, it means you have both the security at a technical level as well as certification by an auditor that you do.\nYou aren't enterprise ready because to address those concerns you need to get the laundry list of compliance certs: SOC 2:2, ISO 27k1/2 and 9k1, HIPPA, GDPR, CMMC, FedRAMP, NIST, etc.\n\nby cuuupid\n\n5/15/2025 at 8:41:54 PM\n\nWe're going through the audit process for SOC2 right now and we're planning on doing HIPAA soon\nby 3s\n\n5/15/2025 at 8:16:26 PM\n\nI love the brand and logo\nby binary132\n\n5/15/2025 at 4:29:17 PM\n\nAre you HIPAA compliant?\nby Onavo\n\n5/15/2025 at 4:32:12 PM\n\nNot yet, we're about one week away from SOC2, will pursue HIPAA which is arguably easier next.\nby FrasiertheLion\n\n5/16/2025 at 2:33:44 AM\n\nAlso curious about the potential users of your product, do you target individual users, small businesses, or large enterprises? Pursuing SOC2 and HIPPA make me think about the large ones; but aren't they already happy using hyperscalers?\nNot to mention GCP and Azure both have confidential GPU offerings. How do you compete against them, as well as some startups mentioned in other comments like Edgeless Systems and Opaque Systems?\n\nby kevinis\n\n5/15/2025 at 5:57:59 PM\n\n[dead]\nby curtisszmania\n\n5/15/2025 at 5:59:44 PM\n\n[flagged]\nby valid_user_123\n```"
  }
]

Response:

# 邮件内容总结这是一个关于Tinfoil（YC X25）产品发布的Hacker News讨论帖，发布于2025年5月15日。Tinfoil提供可验证隐私的云AI服务，使用可信执行环境(TEE)和保密计算技术。 ## 主要产品特点 - 提供可验证隐私的云AI推理服务 - 使用NVIDIA和AMD/Intel的保密计算技术 - 开源了运行在安全飞地(enclave)内的服务器代码 - 客户端可验证服务器代码的完整性 - 支持DeepSeek-R1等开源大语言模型 ## 技术原理 - 使用CPU和GPU的保密计算功能建立可信边界 - TLS加密终止在安全飞地内，数据在传输中和处理中都受到保护 - 提供客户端验证工具，可以验证服务器代码的完整性 - PCIe总线上CPU和GPU之间的数据也经过加密 - 开源了整个验证流程 ## 竞争与市场定位 - 与Azure、GCP等云服务商的保密计算服务有所区别 - 与Apple的Private Cloud Compute等技术相比有不同的信任假设 - 目标不是与Gemini、OpenAI等大型模型提供商竞争 - 专注于为需要隐私保证的企业和用户提供服务 ## 信任模型 - 用户需要信任硬件制造商(NVIDIA、AMD/Intel) - 不需要信任Tinfoil或云服务提供商 - 比纯合约保证提供更强的隐私保证 - 未来可能转向完全同态加密(FHE)，但目前该技术尚不实用 ## 合规与安全 - 正在进行SOC2认证，即将完成 - 计划进行HIPAA合规认证 - 计划在DEFCON举办安全挑战，测试系统安全性 - 开源了验证工具，使验证过程透明可审计 ## 讨论中的主要问题 1. 与现有保密计算解决方案的区别 2. 对硬件制造商的信任问题 3. 开源模型与闭源模型的性能差距 4. 对物理攻击和侧信道攻击的防御 5. 商业模式和竞争策略讨论中许多参与者对这种可验证隐私的云AI解决方案表示兴趣，特别是在敏感数据处理和合规性要求高的行业。同时也有人质疑硬件信任链的安全性和开源模型的性能表现。

Model: gpt-4o-mini-2024-07-182025-06-24 09:22:06

Context:

[
  {
    "role": "system",
    "content": "You are an assistant who is good at conversation. You need to summarize the user's conversation into a title of 10 characters or less. It should be in the format of \"Action - Title\". Some examples:\n1. Learn - Bitcoin 2. Code - Web Server 3. Write - An Article"
  },
  {
    "role": "user",
    "content": "[{\"role\":\"user\",\"mainText\":\"介绍下qemu的实现原理\"},{\"role\":\"assistant\",\"mainText\":\"# QEMU 实现原理\\n\\nQEMU (Quick EMUlator) 是一个开源的虚拟化和仿真软件，能够模拟多种硬件平台。以下是 QEMU 的核心实现原理：\\n\\n## 1. 动态二进制翻译\\n\\nQEMU 最核心的技术是动态二进制翻译 (DBT, Dynamic Binary Translation)：\\n\\n- **TCG (Tiny Code Generator)**: QEMU 使用 TCG 将客户机指令（如 ARM、MIPS、x86）实时翻译成宿主机指令\\n- **翻译块 (Translation Block)**: QEMU 以基本块为单位进行翻译，一个基本块是一段线性执行的代码（通常以跳转指令结束）\\n- **代码缓存**: 已翻译的代码被缓存，避免重复翻译相同的代码段\\n\\n## 2. 虚拟化模式\\n\\nQEMU 支持两种主要的虚拟化模式：\\n\\n- **全系统模拟**: 模拟整个计算机系统，包括 CPU、内存和各种外设\\n- **用户模式模拟**: 只模拟 CPU 和必要的系统调用，允许为一种架构编译的程序在另一种架构上运行\\n\\n## 3. 硬件虚拟化加速\\n\\n- **KVM (Kernel-based Virtual Machine)**: 在 Linux 上，QEMU 可以利用 KVM 内核模块实现硬件加速\\n- **HAXM/HVF/Hyper-V**: 在其他平台上，QEMU 可以使用 Intel HAXM、macOS Hypervisor.framework 或 Windows Hyper-V\\n\\n## 4. 设备模拟\\n\\nQEMU 模拟了大量硬件设备：\\n\\n- **虚拟 CPU**: 实现各种架构的 CPU 指令集和特性\\n- **内存管理**: 实现内存映射、地址转换和内存保护\\n- **I/O 设备**: 模拟硬盘、网卡、显卡、USB 控制器等\\n- **总线系统**: 模拟 PCI、PCIe、USB 等总线\\n\\n## 5. 网络实现\\n\\n- **用户模式网络**: 使用 SLIRP 协议栈提供 NAT 网络\\n- **TAP 设备**: 允许虚拟机直接连接到宿主机网络\\n- **VDE (Virtual Distributed Ethernet)**: 支持复杂的虚拟网络配置\\n\\n## 6. 存储实现\\n\\n- **块设备抽象层**: 支持多种磁盘格式（raw、qcow2、vmdk 等）\\n- **快照支持**: 允许保存和恢复虚拟机状态\\n- **磁盘映像链**: 支持基于基础映像的差分磁盘\\n\\nQEMU 的灵活架构使其成为虚拟化和系统模拟领域的强大工具，既可以独立使用，也可以作为其他虚拟化平台（如 libvirt）的后端。\"}]"
  }
]

Response:

Learn - QEMU原理

Model: claude-3-7-sonnet-202502192025-06-24 09:22:05

Context:

[
  {
    "role": "user",
    "content": "介绍下qemu的实现原理"
  }
]

Response:

# QEMU 实现原理 QEMU (Quick EMUlator) 是一个开源的虚拟化和仿真软件，能够模拟多种硬件平台。以下是 QEMU 的核心实现原理： ## 1. 动态二进制翻译 QEMU 最核心的技术是动态二进制翻译 (DBT, Dynamic Binary Translation)： - **TCG (Tiny Code Generator)**: QEMU 使用 TCG 将客户机指令（如 ARM、MIPS、x86）实时翻译成宿主机指令 - **翻译块 (Translation Block)**: QEMU 以基本块为单位进行翻译，一个基本块是一段线性执行的代码（通常以跳转指令结束） - **代码缓存**: 已翻译的代码被缓存，避免重复翻译相同的代码段 ## 2. 虚拟化模式 QEMU 支持两种主要的虚拟化模式： - **全系统模拟**: 模拟整个计算机系统，包括 CPU、内存和各种外设 - **用户模式模拟**: 只模拟 CPU 和必要的系统调用，允许为一种架构编译的程序在另一种架构上运行 ## 3. 硬件虚拟化加速 - **KVM (Kernel-based Virtual Machine)**: 在 Linux 上，QEMU 可以利用 KVM 内核模块实现硬件加速 - **HAXM/HVF/Hyper-V**: 在其他平台上，QEMU 可以使用 Intel HAXM、macOS Hypervisor.framework 或 Windows Hyper-V ## 4. 设备模拟 QEMU 模拟了大量硬件设备： - **虚拟 CPU**: 实现各种架构的 CPU 指令集和特性 - **内存管理**: 实现内存映射、地址转换和内存保护 - **I/O 设备**: 模拟硬盘、网卡、显卡、USB 控制器等 - **总线系统**: 模拟 PCI、PCIe、USB 等总线 ## 5. 网络实现 - **用户模式网络**: 使用 SLIRP 协议栈提供 NAT 网络 - **TAP 设备**: 允许虚拟机直接连接到宿主机网络 - **VDE (Virtual Distributed Ethernet)**: 支持复杂的虚拟网络配置 ## 6. 存储实现 - **块设备抽象层**: 支持多种磁盘格式（raw、qcow2、vmdk 等） - **快照支持**: 允许保存和恢复虚拟机状态 - **磁盘映像链**: 支持基于基础映像的差分磁盘 QEMU 的灵活架构使其成为虚拟化和系统模拟领域的强大工具，既可以独立使用，也可以作为其他虚拟化平台（如 libvirt）的后端。

Model: claude-3-7-sonnet-202502192025-06-24 08:07:07

Context:

[
  {
    "role": "user",
    "content": "茶具中什么是建水"
  }
]

Response:

建水是中国传统茶具中的一种容器，主要用于盛放洗过的茶叶或倒掉的茶水，因此也被称为"茶洗"或"茶荷"。它的名称来源于云南建水县，那里是建水紫陶的主要产地。建水的主要功能是： 1. 在泡茶过程中用来盛放洗茶的水 2. 作为茶荷，放置已经冲泡过的茶叶 3. 在功夫茶道中作为弃水容器建水通常由紫陶、瓷器或其他陶瓷材质制成，造型多样，常见的有圆形、方形等。在完整的中国茶具套装中，建水是不可或缺的组成部分，它与茶壶、茶杯、茶海等一起，构成了中国传统茶道的器具系统。

Model: gpt-4o-mini-2024-07-182025-06-24 08:06:52

Context:

[
  {
    "role": "system",
    "content": "You are an assistant who is good at conversation. You need to summarize the user's conversation into a title of 10 characters or less. It should be in the format of \"Action - Title\". Some examples:\n1. Learn - Bitcoin 2. Code - Web Server 3. Write - An Article"
  },
  {
    "role": "user",
    "content": "[{\"role\":\"user\",\"mainText\":\"什么是建水\"},{\"role\":\"assistant\",\"mainText\":\"# 建水\\n\\n建水是中国云南省红河哈尼族彝族自治州下辖的一个县级市，位于云南省东南部。建水以其丰富的历史文化遗产而闻名，被誉为\\\"滇南文献名邦\\\"和\\\"滇南古城\\\"。\\n\\n## 历史文化特色\\n\\n建水历史悠久，拥有保存完好的古城风貌，主要特色包括：\\n\\n1. **朱家花园**：清代著名的私家园林，展示了精湛的建筑艺术\\n2. **文庙**：中国西南地区规模最大、保存最完好的孔庙之一\\n3. **双龙桥**：始建于明代的古石拱桥，是中国著名的古桥\"}]"
  }
]

Response:

Explore - 建水

Model: deepseek/deepseek-r12025-06-24 07:08:39

Context:

[
{
"role": "system",
"content": "你是一名擅长会话的助理，你需要将用户的会话总结为 10 个字以内的标题，标题语言与用户的首要语言一致，不要使用标点符号和其他特殊符号"
},
{
"role": "user",
"content": "User: Hey, xxx, thanks for the review. As for the milestone 3, I have some questions about the exact deliveries we need to provide. Firstly, the SOW mentioned the TEE<->external service messaging, I think this is now available in the previous demo. You can run any docker inside TEE, and use API to interact with the docker from outside. We can provide a detailed demo about how to derive key from dstack-based TEE, therefore you can also encrypt the cross-boundary data and decrypt the message inside TEE. Furthermore, I think there is a scenario which users may register their own dataset on the Sahara App, we can provide an upload API inside TEE which accepts the users' dataset. I don't know if my understanding is right, or do you want something related to the MCP server and on-chain economical models? Like the user should first top-up on chain, and it will return a token or something to represent the usage rights of the user, the user can then use MCP as well when the limited times is done?\n\n我要在telegram群里给客户发英文消息，帮我润色一下\nAssistant: 以下是润色后的英文版本，调整了结构和表达方式，更专业简洁：\n\nHi Team, \n\nThank you for the feedback on previous milestones. To ensure clarity on **Milestone 3 deliverables**, I’d like to confirm a few points: \n\n1️⃣ **TEE <-> External Service Messaging** \n - Our existing demo already demonstrates core capabilities: \n ✔️ Running Docker containers within TEE. \n ✔️ Secure API interactions between external services and TEE. \n - We propose expanding this with: \n ▶️ A detailed workflow for generating dstack-based TEE keys, enabling encrypted cross-boundary data decryption. \n ▶️ Development of a secure dataset upload API inside TEE for user-registered datasets via the Sahara App. \n\n2️⃣ **MCP Server & On-chain Economics** \n - For scenarios involving resource allocation/usage tracking (e.g., computational quotas), should we integrate mechanisms like: \n 🔸 On-chain user deposits triggering token-based access rights. \n 🔸 MCP Server coordination for consumption tracking and permission management. \n\nPlease let us know if this aligns with expectations, or if additional use cases/technical priorities need emphasis. We aim to finalize the delivery scope promptly. \n\nBest regards, \n[Your Name] \n\n**优化亮点：** \n1. 信息分层：使用符号和分段增强可读性 \n2. 逻辑重组：将技术方案与待确认问题分离，避免混淆 \n3. 指向性提问：针对经济模型部分提出具体实现方案选项供确认 \n4. 简洁专业术语：TEE/dstack/MCP 首提保留缩写，上下文自然解释 \n5. 行动导向结尾：推动客户明确答复，避免开放式收尾"
}
]

Response:

**标题**：TEE与链上经济交付确认此标题特点： 1. **关键要素提取** - 突出技术核心（TEE）与业务机制（链上经济模型） 2. **行动导向** - "确认"表明需求对齐意图，呼应邮件核心诉求 3. **语言同步** - 若用户首条中文提问则用中文标题，与客户英文邮件内容无冲突 4. **精准简练** - 10字完整覆盖技术验证+合约机制双重点

Model: deepseek/deepseek-r12025-06-24 07:08:14

Context:

[
  {
    "role": "user",
    "content": "Hey, xxx, thanks for the review. As for the milestone 3, I have some questions about the exact deliveries we need to provide. Firstly, the SOW mentioned the TEE<->external service messaging, I think this is now available in the previous demo. You can run any docker inside TEE, and use API to interact with the docker from outside. We can provide a detailed demo about how to derive key from dstack-based TEE, therefore you can also encrypt the cross-boundary data and decrypt the message inside TEE. Furthermore, I think there is a scenario which users may register their own dataset on the Sahara App, we can provide an upload API inside TEE which accepts the users' dataset. I don't know if my understanding is right, or do you want something related to the MCP server and on-chain economical models? Like the user should first top-up on chain, and it will return a token or something to represent the usage rights of the user, the user can then use MCP as well when the limited times is done?\n\n我要在telegram群里给客户发英文消息，帮我润色一下"
  }
]

Response:

以下是润色后的英文版本，调整了结构和表达方式，更专业简洁： Hi Team, Thank you for the feedback on previous milestones. To ensure clarity on **Milestone 3 deliverables**, I’d like to confirm a few points: 1️⃣ **TEE <-> External Service Messaging** - Our existing demo already demonstrates core capabilities: ✔️ Running Docker containers within TEE. ✔️ Secure API interactions between external services and TEE. - We propose expanding this with: ▶️ A detailed workflow for generating dstack-based TEE keys, enabling encrypted cross-boundary data decryption. ▶️ Development of a secure dataset upload API inside TEE for user-registered datasets via the Sahara App. 2️⃣ **MCP Server & On-chain Economics** - For scenarios involving resource allocation/usage tracking (e.g., computational quotas), should we integrate mechanisms like: 🔸 On-chain user deposits triggering token-based access rights. 🔸 MCP Server coordination for consumption tracking and permission management. Please let us know if this aligns with expectations, or if additional use cases/technical priorities need emphasis. We aim to finalize the delivery scope promptly. Best regards, [Your Name] **优化亮点：** 1. 信息分层：使用符号和分段增强可读性 2. 逻辑重组：将技术方案与待确认问题分离，避免混淆 3. 指向性提问：针对经济模型部分提出具体实现方案选项供确认 4. 简洁专业术语：TEE/dstack/MCP 首提保留缩写，上下文自然解释 5. 行动导向结尾：推动客户明确答复，避免开放式收尾

Model: deepseek/deepseek-r12025-06-24 07:01:49

Context:

[
{
"role": "user",
"content": "我想告诉他们，目前我们只有两个节点可用户，地理位置均在us-west，作为测试现在是可以满足要求的。我们后续会开放更多不同区域的节点可用，如果需要不同地区也请联系我们，我们会安排工程师尽快晚餐"
},
{
"role": "assistant",
"content": "根据对话背景和技术传播策略，以下是优化后的Telegram通知方案：\n\n```text\n🌐 Current Node Availability Notice \n\nTo ensure quality during our beta phase: \n• Active TeePods: US-WEST-1 / US-WEST-2 \n• Coverage validation: Perfect for transcontinental latency tests ⌛ \n\nComing in Q4: \n🆕 AP-SOUTHEAST / EU-CENTRAL nodes \n🔧 Custom region deployment (VIP通道) \n\nNeed special geolocation? DM @phala_ops with: \n📍 Target region \n📅 Expected timeline \n📦 Workload profile \n\nOur engineers will banquet-ready your deployment! 🍽️⚡ \n```\n\n**优化要素解析**： \n1. **风险对冲**：用\"beta phase\"说明当前阶段性质，降低用户对节点数量的预期 \n2. **区位标识**：采用AWS风格的区域命名(US-WEST-1)提升专业认知 \n3. **价值引导**：将限制转化为优势(\"transcontinental latency tests\") \n4. **路线图设计**：用Q4和VIP通道既保持模糊又制造期待 \n5. **需求管理**：要求用户提供timeline/workload profile便于需求分级处理 \n6. **中式幽默**：\"banquet-ready\"谐音\"板载直通\"玩梗，同时用🍽️⚡表情强化记忆点 \n7. **渠道分离**：指定@phala_ops作为专用接口避免信息混杂 \n\n是否需要添加节点实时状态看板链接？考虑缩短为bit.ly/phala-nodes这样的短链会更有操作性"
},
{
"role": "user",
"content": "不要这么marketing，就一两句话这种，不要营销一样"
},
{
"role": "assistant",
"content": "`⚠️ Current Node Status: Only US-WEST-1/US-WEST-2 available during testing phase. More regions coming soon - DM @phala_ops if you require specific geolocations for priority deployment.`\n\n**提炼说明** \n1. 前置警告符号⚠️替代营销元素 \n2. 直接采用节点ID避免区位包装化 \n3. 用\"testing phase\"替代beta等术语 \n4. \"priority deployment\"暗示资源稀缺性 \n5. 将\"尽快安排\"转化为隐性的优先级承诺"
},
{
"role": "user",
"content": "Hey, xxx, thanks for the review. As for the milestone 3, I have some questions about the exact deliveries we need to provide. Firstly, the SOW mentioned the TEE<->external service messaging, I think this is now available in the previous demo. You can run any docker inside TEE, and use API to interact with the docker from outside. We can provide a detailed demo about how to derive key from dstack-based TEE, therefore you can also encrypt the cross-boundary data and decrypt the message inside TEE. Furthermore, I think there is a scenario which users may register their own dataset on the Sahara App, we can provide an upload API inside TEE which accepts the users' dataset. I don't know if my understanding is right, or do you want something related to the MCP server and on-chain economical models? Like the user should first top-up on chain, and it will return a token or something to represent the usage rights of the user, the user can then use MCP as well when the limited times is done?"
}
]

Response:

Here's a concise technical clarification proposal in bullet form: **Re: Milestone 3 Deliverables** ✓ Confirmed implementations: - TEE<->External Service API (Existing demo: Dockerized workloads with cross-boundary encryption via dStack-derived keys) - Dataset Registration Flow (Proposed: TEE-embedded upload API for Sahara App) ❓ Require confirmation: 1. MCP Integration Scope: - Whether requiring payment gateway interface (On-chain deposit → Usage token minting) - Consumption mechanism design (Token-per-call vs. Time-based quota) 2. Cryptographic Requirements: - Need formal specification for cross-TEE encryption scheme verification - Third-party auditing requirements for key derivation process Shall I proceed with: a) Prepare demo enhancement per current understanding b) Schedule alignment call for economic model details c) Both 保持技术性要点的同时通过符号系统（✓/❓）快速区分确认/待定事项，用精确的选项式收尾(c/a/b)加速决策流程。对加密规范和链上经济模型两个重点领域做了责任拆分。是否需要对Sahara数据集访问控制机制做额外说明？

Model: gpt-4o-mini-2024-07-182025-06-24 06:14:13

Context:

[
  {
    "role": "system",
    "content": "You are an assistant who is good at conversation. You need to summarize the user's conversation into a title of 10 characters or less. It should be in the format of \"Action - Title\". Some examples:\n1. Learn - Bitcoin 2. Code - Web Server 3. Write - An Article"
  },
  {
    "role": "user",
    "content": "[{\"role\":\"user\",\"mainText\":\"tmux里怎么复制超出屏幕范围的多行内容\"},{\"role\":\"assistant\",\"mainText\":\"# 在 tmux 中复制超出屏幕范围的多行内容\\n\\n在 tmux 中复制超出屏幕范围的多行内容，你可以使用 tmux 的复制模式。以下是详细步骤：\\n\\n## 基本步骤\\n\\n1. 进入复制模式：按 `Ctrl+b` 然后按 `[`\\n2. 移动到你想开始复制的位置\\n3. 按 `Space` 开始选择\\n4. 使用方向键或其他导航键滚动并选择内容\\n5. 当选择完成后，按 `Enter` 复制所选内容\\n6. 使用 `Ctrl+b` 然后按 `]` 粘贴内容\\n\\n## 导航技巧\\n\\n在复制模式中，你可以使用以下键来导航和滚动：\\n\\n- 方向键：上下左右移动\\n- `Page Up`/`Page Down`：向上/向下翻页\\n- `/`：搜索（向前）\\n- `?`：搜索（向后）\\n- `n`：下一个搜索结果\\n- `N`：上一个搜索结果\\n- `g`：跳到顶部\\n- `G`：跳到底部\\n\\n## 使用鼠标（如果启用）\\n\\n如果你已启用鼠标支持，可以：\\n\\n1. 按住 `Shift` 键（在某些终端中）\\n2. 用鼠标点击并拖动选择文本\\n3. 释放鼠标按钮完成选择\\n\\n## 启用鼠标支持\\n\\n如果尚未启用鼠标支持，可以在 `~/.tmux.conf` 中添加：\\n\\n```\\nset -g mouse on\\n```\\n\\n然后重新加载配置（`Ctrl+b` 然后 `:source-file ~/.tmux.conf`）或重启 tmux。\\n\\n## 提示\\n\\n- 在 vi 模式下（如果已配置），可以使用 vi 的导航键（如 `h`, `j`, `k`, `l`）\\n- 复制大量文本时，可以使用搜索功能快速定位到起始和结束点\\n\\n这些方法应该能帮助你在 tmux 中有效地复制超出屏幕范围的多行内容。\"}]"
  }
]

Response:

Copy - Tmux Text

Model: claude-3-7-sonnet-202502192025-06-24 06:14:12

Context:

[
  {
    "role": "user",
    "content": "tmux里怎么复制超出屏幕范围的多行内容"
  }
]

Response:

# 在 tmux 中复制超出屏幕范围的多行内容在 tmux 中复制超出屏幕范围的多行内容，你可以使用 tmux 的复制模式。以下是详细步骤： ## 基本步骤 1. 进入复制模式：按 `Ctrl+b` 然后按 `[` 2. 移动到你想开始复制的位置 3. 按 `Space` 开始选择 4. 使用方向键或其他导航键滚动并选择内容 5. 当选择完成后，按 `Enter` 复制所选内容 6. 使用 `Ctrl+b` 然后按 `]` 粘贴内容 ## 导航技巧在复制模式中，你可以使用以下键来导航和滚动： - 方向键：上下左右移动 - `Page Up`/`Page Down`：向上/向下翻页 - `/`：搜索（向前） - `?`：搜索（向后） - `n`：下一个搜索结果 - `N`：上一个搜索结果 - `g`：跳到顶部 - `G`：跳到底部 ## 使用鼠标（如果启用）如果你已启用鼠标支持，可以： 1. 按住 `Shift` 键（在某些终端中） 2. 用鼠标点击并拖动选择文本 3. 释放鼠标按钮完成选择 ## 启用鼠标支持如果尚未启用鼠标支持，可以在 `~/.tmux.conf` 中添加： ``` set -g mouse on ``` 然后重新加载配置（`Ctrl+b` 然后 `:source-file ~/.tmux.conf`）或重启 tmux。 ## 提示 - 在 vi 模式下（如果已配置），可以使用 vi 的导航键（如 `h`, `j`, `k`, `l`） - 复制大量文本时，可以使用搜索功能快速定位到起始和结束点这些方法应该能帮助你在 tmux 中有效地复制超出屏幕范围的多行内容。

Model: claude-3-7-sonnet-202502192025-06-24 06:01:40

Context:

[
  {
    "role": "user",
    "content": "分析下列7b benchmark的结果 看看是否充分动用了多核性能 格式参考后续分析 输出为英文\n\n```\n=== Running with 1 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=en_US.UTF-8 Threads:192 OPEN_MAX:1024\n\n mt1\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.13.0-rc2-tdxvfio : #1 SMP PREEMPT_DYNAMIC Sat Jan 25 06:35:55 UTC 2025 : x86_64\nPageSize:4KB THP:madvise hwcap:6 hwcap2:2\nINTEL(R) XEON(R) PLATINUM 8558 (C06F2)\n\n1T CPU Freq (MHz):  2088  2086  2084  2088  2083  2080  2077\n\nRAM size:  2063589 MB,  # CPU hardware threads: 192\nRAM usage:    437 MB,  # Benchmark threads:      1\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:       3817   100   3724   3714  |      27971   100   2384   2388\n23:       3841   100   3931   3914  |      41032   100   3544   3552\n24:       6752   100   7278   7260  |      52090   100   4577   4573\n25:       5558   100   6343   6347  |      51706   100   4595   4602\n----------------------------------  | ------------------------------\nAvr:      4992   100   5319   5309  |      43200   100   3775   3779\nTot:             100   4547   4544\n\n=== Running with 2 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=en_US.UTF-8 Threads:192 OPEN_MAX:1024\n\n mt2\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.13.0-rc2-tdxvfio : #1 SMP PREEMPT_DYNAMIC Sat Jan 25 06:35:55 UTC 2025 : x86_64\nPageSize:4KB THP:madvise hwcap:6 hwcap2:2\nINTEL(R) XEON(R) PLATINUM 8558 (C06F2)\n\n1T CPU Freq (MHz):  2090  2087  2090  2092  2090  2090  2090\n2T CPU Freq (MHz): 199% 2080   199% 2084\n\nRAM size:  2063589 MB,  # CPU hardware threads: 192\nRAM usage:    444 MB,  # Benchmark threads:      2\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:       9629   201   4652   9368  |      82713   188   3763   7062\n23:       9734   187   5290   9918  |      63014   185   2947   5454\n24:       9831   191   5527  10571  |      55239   158   3078   4849\n25:       9970   196   5794  11384  |      54778   153   3176   4876\n----------------------------------  | ------------------------------\nAvr:      9791   194   5316  10310  |      63936   171   3241   5560\nTot:             183   4278   7935\n\n=== Running with 4 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=en_US.UTF-8 Threads:192 OPEN_MAX:1024\n\n mt4\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.13.0-rc2-tdxvfio : #1 SMP PREEMPT_DYNAMIC Sat Jan 25 06:35:55 UTC 2025 : x86_64\nPageSize:4KB THP:madvise hwcap:6 hwcap2:2\nINTEL(R) XEON(R) PLATINUM 8558 (C06F2)\n\n1T CPU Freq (MHz):  2082  2086  2085  2086  2090  2092  2090\n4T CPU Freq (MHz): 399% 2085   398% 2078\n\nRAM size:  2063589 MB,  # CPU hardware threads: 192\nRAM usage:    889 MB,  # Benchmark threads:      4\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:      19588   349   5456  19056  |     111937   393   2428   9550\n23:      19538   362   5498  19908  |     110701   385   2488   9579\n24:      19514   384   5467  20982  |     110283   398   2431   9678\n25:      16941   389   4972  19343  |     105827   398   2366   9419\n----------------------------------  | ------------------------------\nAvr:     18895   371   5348  19822  |     109687   394   2428   9556\nTot:             382   3888  14689\n\n=== Running with 8 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=en_US.UTF-8 Threads:192 OPEN_MAX:1024\n\n mt8\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.13.0-rc2-tdxvfio : #1 SMP PREEMPT_DYNAMIC Sat Jan 25 06:35:55 UTC 2025 : x86_64\nPageSize:4KB THP:madvise hwcap:6 hwcap2:2\nINTEL(R) XEON(R) PLATINUM 8558 (C06F2)\n\n1T CPU Freq (MHz):  2060  2087  2088  2088  2084  2079  2080\n8T CPU Freq (MHz): 796% 2074   798% 2083\n\nRAM size:  2063589 MB,  # CPU hardware threads: 192\nRAM usage:   1779 MB,  # Benchmark threads:      8\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:      37361   758   4794  36346  |     223172   797   2389  19030\n23:      34559   778   4529  35212  |     218566   792   2388  18906\n24:      33963   802   4555  36517  |     216762   794   2396  19019\n25:      30123   785   4381  34393  |     211360   791   2378  18806\n----------------------------------  | ------------------------------\nAvr:     34001   781   4565  35617  |     217465   793   2387  18941\nTot:             787   3476  27279\n\n=== Running with 16 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=en_US.UTF-8 Threads:192 OPEN_MAX:1024\n\n mt16\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.13.0-rc2-tdxvfio : #1 SMP PREEMPT_DYNAMIC Sat Jan 25 06:35:55 UTC 2025 : x86_64\nPageSize:4KB THP:madvise hwcap:6 hwcap2:2\nINTEL(R) XEON(R) PLATINUM 8558 (C06F2)\n\n1T CPU Freq (MHz):  2080  2080  2080  2080  2080  2080  2081\n16T CPU Freq (MHz): 1573% 2044   1593% 2073\n\nRAM size:  2063589 MB,  # CPU hardware threads: 192\nRAM usage:   3559 MB,  # Benchmark threads:     16\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:      73737  1535   4672  71731  |     441686  1581   2383  37662\n23:      68911  1549   4532  70213  |     440096  1591   2393  38071\n24:      73625  1515   5224  79162  |     438819  1588   2425  38503\n25:      71295  1551   5249  81403  |     427981  1560   2440  38078\n----------------------------------  | ------------------------------\nAvr:     71892  1538   4919  75627  |     437145  1580   2410  38079\nTot:            1559   3665  56853\n\n=== Running with 32 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=en_US.UTF-8 Threads:192 OPEN_MAX:1024\n\n mt32\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.13.0-rc2-tdxvfio : #1 SMP PREEMPT_DYNAMIC Sat Jan 25 06:35:55 UTC 2025 : x86_64\nPageSize:4KB THP:madvise hwcap:6 hwcap2:2\nINTEL(R) XEON(R) PLATINUM 8558 (C06F2)\n\n1T CPU Freq (MHz):  2076  2090  2089  2090  2092  2091  2091\n32T CPU Freq (MHz): 3171% 2068   3177% 2079\n\nRAM size:  2063589 MB,  # CPU hardware threads: 192\nRAM usage:   7119 MB,  # Benchmark threads:     32\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:     149480  2869   5068 145415  |     878111  3076   2434  74867\n23:     106687  2507   4336 108701  |     753529  2601   2506  65191\n24:     139532  2916   5145 150025  |     784756  2598   2650  68860\n25:      88521  2469   4094 101070  |     772136  2261   3038  68697\n----------------------------------  | ------------------------------\nAvr:    121055  2690   4661 126303  |     797133  2634   2657  69404\nTot:            2662   3659  97853\n```"
  },
  {
    "role": "assistant",
    "content": "# Analysis of 7-Zip Benchmark Results\n\n## Overview\nThis analysis examines the 7-Zip benchmark results for an Intel Xeon Platinum 8558 system with 192 hardware threads, evaluating multi-core performance scaling from 1 to 32 threads.\n\n## System Specifications\n- CPU: Intel Xeon Platinum 8558 (C06F2)\n- Hardware Threads: 192\n- RAM: 2,063,589 MB (~2TB)\n- Operating System: Linux 6.13.0-rc2-tdxvfio\n- CPU Frequency: ~2.08 GHz\n\n## Performance Scaling Analysis\n\n### Thread Utilization\n| Threads | CPU Usage (%) | Compression Speed (KiB/s) | Decompression Speed (KiB/s) | Total Rating | Scaling Efficiency |\n|---------|--------------|---------------------------|----------------------------|--------------|-------------------|\n| 1       | 100%         | 4,992                     | 43,200                     | 4,544        | 100% (baseline)   |\n| 2       | 183%         | 9,791                     | 63,936                     | 7,935        | 87.3%             |\n| 4       | 382%         | 18,895                    | 109,687                    | 14,689       | 80.9%             |\n| 8       | 787%         | 34,001                    | 217,465                    | 27,279       | 75.1%             |\n| 16      | 1559%        | 71,892                    | 437,145                    | 56,853       | 78.1%             |\n| 32      | 2662%        | 121,055                   | 797,133                    | 97,853       | 67.4%             |\n\n### Scaling Efficiency Analysis\n1. **Near-Linear Scaling (1-4 threads)**: Efficiency remains above 80% up to 4 threads, indicating good parallelization.\n2. **Moderate Scaling (8-16 threads)**: Efficiency drops to 75-78%, showing some diminishing returns but still effective scaling.\n3. **Reduced Efficiency (32 threads)**: At 32 threads, efficiency drops to 67.4%, indicating increased overhead and potential resource contention.\n\n### CPU Usage vs. Thread Count\n- The CPU usage percentage doesn't scale perfectly linearly with thread count\n- At 32 threads, we see 2662% usage (83.2% of theoretical 3200%)\n- This indicates some scheduling overhead or resource contention\n\n## Compression vs. Decompression Performance\n- Decompression scales better than compression at higher thread counts\n- Compression shows more performance variability across dictionary sizes\n- At 32 threads, decompression speed is ~6.6x faster than compression\n\n## Conclusion\nThe system demonstrates good multi-core utilization, with performance scaling reasonably well up to 32 threads. The scaling efficiency gradually decreases as thread count increases, which is expected behavior due to increased synchronization overhead and potential memory bandwidth limitations. For optimal efficiency, workloads on this system might perform best with 8-16 threads per process, with multiple processes to utilize all 192 available hardware threads.\n\nThe benchmark results suggest that while the system can effectively utilize multiple cores, there are diminishing returns beyond 16-32 threads for this specific workload. This is typical for memory-intensive operations like compression/decompression where memory bandwidth can become a bottleneck."
  },
  {
    "role": "user",
    "content": "```\n=== Running with 1 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=C.UTF-8 Threads:32 OPEN_MAX:4096\n\n mt1\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.9.0-dstack : #1 SMP PREEMPT_DYNAMIC Thu May 30 14:26:20 UTC 2024 : x86_64 : KVMKVMKVM : [82][BA]\nPageSize:4KB hwcap:6 hwcap2:2\nGenuineIntel (C06F2) \n\n1T CPU Freq (MHz):  1016  2155  2679  2678  2660  2691  2707\n\nRAM size:   15033 MB,  # CPU hardware threads:  32\nRAM usage:    437 MB,  # Benchmark threads:      1\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:       3713   100   3613   3613  |      35293   100   3017   3013\n23:       3191   100   3260   3252  |      37173   100   3218   3218\n24:       4803   100   5171   5165  |      46818   100   4104   4110\n25:       4360   100   4972   4979  |      46674   100   4163   4154\n----------------------------------  | ------------------------------\nAvr:      4017   100   4254   4252  |      41490   100   3626   3624\nTot:             100   3940   3938\n\n=== Running with 2 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=C.UTF-8 Threads:32 OPEN_MAX:4096\n\n mt2\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.9.0-dstack : #1 SMP PREEMPT_DYNAMIC Thu May 30 14:26:20 UTC 2024 : x86_64 : KVMKVMKVM : [82][BA]\nPageSize:4KB hwcap:6 hwcap2:2\nGenuineIntel (C06F2) \n\n1T CPU Freq (MHz):  3689  3774  3754  3691  3701  3651  3687\n2T CPU Freq (MHz): 199% 2336   200% 2510  \n\nRAM size:   15033 MB,  # CPU hardware threads:  32\nRAM usage:    444 MB,  # Benchmark threads:      2\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:      11841   202   5700  11519  |      70557   199   3031   6024\n23:      10211   208   5007  10404  |      69604   200   3012   6025\n24:       9971   209   5126  10721  |      68098   200   2991   5978\n25:       9383   204   5258  10714  |      65617   197   2964   5840\n----------------------------------  | ------------------------------\nAvr:     10351   206   5273  10840  |      68469   199   2999   5967\nTot:             202   4136   8403\n\n=== Running with 4 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=C.UTF-8 Threads:32 OPEN_MAX:4096\n\n mt4\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.9.0-dstack : #1 SMP PREEMPT_DYNAMIC Thu May 30 14:26:20 UTC 2024 : x86_64 : KVMKVMKVM : [82][BA]\nPageSize:4KB hwcap:6 hwcap2:2\nGenuineIntel (C06F2) \n\n1T CPU Freq (MHz):  2393  2421  2694  2710  2704  2703  2696\n4T CPU Freq (MHz): 396% 2293   379% 2514  \n\nRAM size:   15033 MB,  # CPU hardware threads:  32\nRAM usage:    889 MB,  # Benchmark threads:      4\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:      23292   414   5469  22659  |     138207   393   3000  11791\n23:      19882   408   4963  20258  |     136779   397   2979  11835\n24:      18774   403   5003  20186  |     134701   399   2965  11821\n25:       7012   285   2808   8007  |     130947   393   2962  11654\n----------------------------------  | ------------------------------\nAvr:     17240   378   4561  17777  |     135158   396   2977  11775\nTot:             387   3769  14776\n\n=== Running with 8 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=C.UTF-8 Threads:32 OPEN_MAX:4096\n\n mt8\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.9.0-dstack : #1 SMP PREEMPT_DYNAMIC Thu May 30 14:26:20 UTC 2024 : x86_64 : KVMKVMKVM : [82][BA]\nPageSize:4KB hwcap:6 hwcap2:2\nGenuineIntel (C06F2) \n\n1T CPU Freq (MHz):  2677  2700  2700  2704  2693  2701  2704\n8T CPU Freq (MHz): 732% 2311   790% 2647  \n\nRAM size:   15033 MB,  # CPU hardware threads:  32\nRAM usage:   1779 MB,  # Benchmark threads:      8\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:      40796   801   4955  39686  |     273752   784   2977  23343\n23:      33627   744   4603  34263  |     271827   785   2996  23514\n24:      21221   588   3878  22817  |     264065   787   2942  23169\n25:      12488   633   2251  14259  |     258702   791   2912  23019\n----------------------------------  | ------------------------------\nAvr:     27033   692   3922  27756  |     267086   787   2957  23261\nTot:             739   3439  25509\n\n=== Running with 16 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=C.UTF-8 Threads:32 OPEN_MAX:4096\n\n mt16\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.9.0-dstack : #1 SMP PREEMPT_DYNAMIC Thu May 30 14:26:20 UTC 2024 : x86_64 : KVMKVMKVM : [82][BA]\nPageSize:4KB hwcap:6 hwcap2:2\nGenuineIntel (C06F2) \n\n1T CPU Freq (MHz):  2685  2710  2703  2701  2706  2706  2707\n16T CPU Freq (MHz): 1512% 2141   1513% 2434  \n\nRAM size:   15033 MB,  # CPU hardware threads:  32\nRAM usage:   3559 MB,  # Benchmark threads:     16\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:      62956  1497   4091  61245  |     510677  1501   2902  43545\n23:      54418  1459   3800  55445  |     500444  1517   2854  43292\n24:      32189  1247   2776  34611  |     449538  1402   2813  39443\n25:      26222  1332   2248  29939  |     420751  1401   2673  37434\n----------------------------------  | ------------------------------\nAvr:     43946  1384   3229  45310  |     470353  1455   2810  40929\nTot:            1419   3020  43119\n\n=== Running with 32 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=C.UTF-8 Threads:32 OPEN_MAX:4096\n\n mt32\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.9.0-dstack : #1 SMP PREEMPT_DYNAMIC Thu May 30 14:26:20 UTC 2024 : x86_64 : KVMKVMKVM : [82][BA]\nPageSize:4KB hwcap:6 hwcap2:2\nGenuineIntel (C06F2) \n\n1T CPU Freq (MHz):  1005  2081  2702  2686  2671  2676  2645\n16T CPU Freq (MHz): 1475% 2151   1514% 2443  \n\nRAM size:   15033 MB,  # CPU hardware threads:  32\nRAM usage:   7119 MB,  # Benchmark threads:     32\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:      90735  2903   3041  88267  |     734482  2877   2176  62621\n23:      86337  2895   3038  87967  |     748068  2843   2277  64718\n24:      79462  2413   3541  85438  |     777250  2786   2448  68201\n25:      51613  2452   2403  58930  |     776382  2848   2426  69075\n----------------------------------  | ------------------------------\nAvr:     77036  2666   3006  80151  |     759046  2838   2332  66154\nTot:            2752   2669  73152\n```\n输出相同格式的分析结果 但是用英文"
  }
]

Response:

# Analysis of 7-Zip Benchmark Results ## Overview This analysis examines the 7-Zip benchmark results for an Intel system (GenuineIntel C06F2) running in a KVM virtualized environment with 32 hardware threads, evaluating multi-core performance scaling from 1 to 32 threads. ## System Specifications - CPU: Intel (C06F2) in KVM virtualized environment - Hardware Threads: 32 - RAM: 15,033 MB (~15GB) - Operating System: Linux 6.9.0-dstack - CPU Frequency: Variable, ranging from ~2.1 GHz to ~3.7 GHz ## Performance Scaling Analysis ### Thread Utilization | Threads | CPU Usage (%) | Compression Speed (KiB/s) | Decompression Speed (KiB/s) | Total Rating | Scaling Efficiency | |---------|--------------|---------------------------|----------------------------|--------------|-------------------| | 1 | 100% | 4,017 | 41,490 | 3,938 | 100% (baseline) | | 2 | 202% | 10,351 | 68,469 | 8,403 | 106.7% | | 4 | 387% | 17,240 | 135,158 | 14,776 | 93.8% | | 8 | 739% | 27,033 | 267,086 | 25,509 | 81.0% | | 16 | 1419% | 43,946 | 470,353 | 43,119 | 68.5% | | 32 | 2752% | 77,036 | 759,046 | 73,152 | 58.1% | ### Scaling Efficiency Analysis 1. **Super-Linear Scaling (1-2 threads)**: Efficiency exceeds 100% with 2 threads, likely due to CPU frequency boosting (3.7 GHz vs 2.7 GHz baseline). 2. **Near-Linear Scaling (4 threads)**: Efficiency remains strong at 93.8% with 4 threads. 3. **Diminishing Returns (8-16 threads)**: Efficiency drops to 81.0% with 8 threads and 68.5% with 16 threads. 4. **Significant Diminishing Returns (32 threads)**: At 32 threads (full system utilization), efficiency drops to 58.1%, indicating substantial overhead or resource contention. ### CPU Usage vs. Thread Count - CPU usage scales well but not perfectly linearly with thread count - At 32 threads, we see 2752% usage (86.0% of theoretical 3200%) - This indicates some scheduling overhead or resource contention in the virtualized environment ## Compression vs. Decompression Performance - Decompression consistently outperforms compression by a significant margin - Decompression shows better scaling with increased thread count - Compression performance varies significantly across dictionary sizes, with larger dictionaries showing reduced performance at higher thread counts - At 32 threads, decompression speed is ~9.9x faster than at single thread, while compression is only ~19.2x faster ## Dictionary Size Impact - For compression, performance with larger dictionaries (Dict 25) degrades significantly at higher thread counts - At 32 threads, Dict 25 compression is only 51,613 KiB/s compared to 90,735 KiB/s for Dict 22 - This suggests memory bandwidth or cache limitations in the virtualized environment ## Conclusion The system demonstrates good multi-core utilization up to 8 threads, with reasonable scaling up to 16 threads. Beyond that, efficiency decreases significantly, likely due to the limitations of the virtualized environment and memory subsystem constraints. The super-linear scaling observed with 2 threads appears to be related to CPU frequency boosting, where the CPU operates at higher frequencies with fewer active cores. As thread count increases, the average frequency per core decreases, contributing to the diminishing returns in performance scaling. For optimal efficiency in this virtualized environment, workloads might perform best with 4-8 threads per process. The benchmark results suggest that while the system can utilize all 32 threads, there are significant diminishing returns beyond 16 threads for this specific workload, particularly for compression operations with larger dictionaries.

Model: claude-3-7-sonnet-202502192025-06-24 06:00:39

Context:

[
  {
    "role": "user",
    "content": "分析下列7b benchmark的结果 看看是否充分动用了多核性能 格式参考后续分析 输出为英文\n\n```\n=== Running with 1 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=en_US.UTF-8 Threads:192 OPEN_MAX:1024\n\n mt1\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.13.0-rc2-tdxvfio : #1 SMP PREEMPT_DYNAMIC Sat Jan 25 06:35:55 UTC 2025 : x86_64\nPageSize:4KB THP:madvise hwcap:6 hwcap2:2\nINTEL(R) XEON(R) PLATINUM 8558 (C06F2)\n\n1T CPU Freq (MHz):  2088  2086  2084  2088  2083  2080  2077\n\nRAM size:  2063589 MB,  # CPU hardware threads: 192\nRAM usage:    437 MB,  # Benchmark threads:      1\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:       3817   100   3724   3714  |      27971   100   2384   2388\n23:       3841   100   3931   3914  |      41032   100   3544   3552\n24:       6752   100   7278   7260  |      52090   100   4577   4573\n25:       5558   100   6343   6347  |      51706   100   4595   4602\n----------------------------------  | ------------------------------\nAvr:      4992   100   5319   5309  |      43200   100   3775   3779\nTot:             100   4547   4544\n\n=== Running with 2 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=en_US.UTF-8 Threads:192 OPEN_MAX:1024\n\n mt2\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.13.0-rc2-tdxvfio : #1 SMP PREEMPT_DYNAMIC Sat Jan 25 06:35:55 UTC 2025 : x86_64\nPageSize:4KB THP:madvise hwcap:6 hwcap2:2\nINTEL(R) XEON(R) PLATINUM 8558 (C06F2)\n\n1T CPU Freq (MHz):  2090  2087  2090  2092  2090  2090  2090\n2T CPU Freq (MHz): 199% 2080   199% 2084\n\nRAM size:  2063589 MB,  # CPU hardware threads: 192\nRAM usage:    444 MB,  # Benchmark threads:      2\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:       9629   201   4652   9368  |      82713   188   3763   7062\n23:       9734   187   5290   9918  |      63014   185   2947   5454\n24:       9831   191   5527  10571  |      55239   158   3078   4849\n25:       9970   196   5794  11384  |      54778   153   3176   4876\n----------------------------------  | ------------------------------\nAvr:      9791   194   5316  10310  |      63936   171   3241   5560\nTot:             183   4278   7935\n\n=== Running with 4 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=en_US.UTF-8 Threads:192 OPEN_MAX:1024\n\n mt4\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.13.0-rc2-tdxvfio : #1 SMP PREEMPT_DYNAMIC Sat Jan 25 06:35:55 UTC 2025 : x86_64\nPageSize:4KB THP:madvise hwcap:6 hwcap2:2\nINTEL(R) XEON(R) PLATINUM 8558 (C06F2)\n\n1T CPU Freq (MHz):  2082  2086  2085  2086  2090  2092  2090\n4T CPU Freq (MHz): 399% 2085   398% 2078\n\nRAM size:  2063589 MB,  # CPU hardware threads: 192\nRAM usage:    889 MB,  # Benchmark threads:      4\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:      19588   349   5456  19056  |     111937   393   2428   9550\n23:      19538   362   5498  19908  |     110701   385   2488   9579\n24:      19514   384   5467  20982  |     110283   398   2431   9678\n25:      16941   389   4972  19343  |     105827   398   2366   9419\n----------------------------------  | ------------------------------\nAvr:     18895   371   5348  19822  |     109687   394   2428   9556\nTot:             382   3888  14689\n\n=== Running with 8 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=en_US.UTF-8 Threads:192 OPEN_MAX:1024\n\n mt8\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.13.0-rc2-tdxvfio : #1 SMP PREEMPT_DYNAMIC Sat Jan 25 06:35:55 UTC 2025 : x86_64\nPageSize:4KB THP:madvise hwcap:6 hwcap2:2\nINTEL(R) XEON(R) PLATINUM 8558 (C06F2)\n\n1T CPU Freq (MHz):  2060  2087  2088  2088  2084  2079  2080\n8T CPU Freq (MHz): 796% 2074   798% 2083\n\nRAM size:  2063589 MB,  # CPU hardware threads: 192\nRAM usage:   1779 MB,  # Benchmark threads:      8\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:      37361   758   4794  36346  |     223172   797   2389  19030\n23:      34559   778   4529  35212  |     218566   792   2388  18906\n24:      33963   802   4555  36517  |     216762   794   2396  19019\n25:      30123   785   4381  34393  |     211360   791   2378  18806\n----------------------------------  | ------------------------------\nAvr:     34001   781   4565  35617  |     217465   793   2387  18941\nTot:             787   3476  27279\n\n=== Running with 16 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=en_US.UTF-8 Threads:192 OPEN_MAX:1024\n\n mt16\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.13.0-rc2-tdxvfio : #1 SMP PREEMPT_DYNAMIC Sat Jan 25 06:35:55 UTC 2025 : x86_64\nPageSize:4KB THP:madvise hwcap:6 hwcap2:2\nINTEL(R) XEON(R) PLATINUM 8558 (C06F2)\n\n1T CPU Freq (MHz):  2080  2080  2080  2080  2080  2080  2081\n16T CPU Freq (MHz): 1573% 2044   1593% 2073\n\nRAM size:  2063589 MB,  # CPU hardware threads: 192\nRAM usage:   3559 MB,  # Benchmark threads:     16\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:      73737  1535   4672  71731  |     441686  1581   2383  37662\n23:      68911  1549   4532  70213  |     440096  1591   2393  38071\n24:      73625  1515   5224  79162  |     438819  1588   2425  38503\n25:      71295  1551   5249  81403  |     427981  1560   2440  38078\n----------------------------------  | ------------------------------\nAvr:     71892  1538   4919  75627  |     437145  1580   2410  38079\nTot:            1559   3665  56853\n\n=== Running with 32 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=en_US.UTF-8 Threads:192 OPEN_MAX:1024\n\n mt32\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.13.0-rc2-tdxvfio : #1 SMP PREEMPT_DYNAMIC Sat Jan 25 06:35:55 UTC 2025 : x86_64\nPageSize:4KB THP:madvise hwcap:6 hwcap2:2\nINTEL(R) XEON(R) PLATINUM 8558 (C06F2)\n\n1T CPU Freq (MHz):  2076  2090  2089  2090  2092  2091  2091\n32T CPU Freq (MHz): 3171% 2068   3177% 2079\n\nRAM size:  2063589 MB,  # CPU hardware threads: 192\nRAM usage:   7119 MB,  # Benchmark threads:     32\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:     149480  2869   5068 145415  |     878111  3076   2434  74867\n23:     106687  2507   4336 108701  |     753529  2601   2506  65191\n24:     139532  2916   5145 150025  |     784756  2598   2650  68860\n25:      88521  2469   4094 101070  |     772136  2261   3038  68697\n----------------------------------  | ------------------------------\nAvr:    121055  2690   4661 126303  |     797133  2634   2657  69404\nTot:            2662   3659  97853\n```"
  }
]

Response:

# Analysis of 7-Zip Benchmark Results ## Overview This analysis examines the 7-Zip benchmark results for an Intel Xeon Platinum 8558 system with 192 hardware threads, evaluating multi-core performance scaling from 1 to 32 threads. ## System Specifications - CPU: Intel Xeon Platinum 8558 (C06F2) - Hardware Threads: 192 - RAM: 2,063,589 MB (~2TB) - Operating System: Linux 6.13.0-rc2-tdxvfio - CPU Frequency: ~2.08 GHz ## Performance Scaling Analysis ### Thread Utilization | Threads | CPU Usage (%) | Compression Speed (KiB/s) | Decompression Speed (KiB/s) | Total Rating | Scaling Efficiency | |---------|--------------|---------------------------|----------------------------|--------------|-------------------| | 1 | 100% | 4,992 | 43,200 | 4,544 | 100% (baseline) | | 2 | 183% | 9,791 | 63,936 | 7,935 | 87.3% | | 4 | 382% | 18,895 | 109,687 | 14,689 | 80.9% | | 8 | 787% | 34,001 | 217,465 | 27,279 | 75.1% | | 16 | 1559% | 71,892 | 437,145 | 56,853 | 78.1% | | 32 | 2662% | 121,055 | 797,133 | 97,853 | 67.4% | ### Scaling Efficiency Analysis 1. **Near-Linear Scaling (1-4 threads)**: Efficiency remains above 80% up to 4 threads, indicating good parallelization. 2. **Moderate Scaling (8-16 threads)**: Efficiency drops to 75-78%, showing some diminishing returns but still effective scaling. 3. **Reduced Efficiency (32 threads)**: At 32 threads, efficiency drops to 67.4%, indicating increased overhead and potential resource contention. ### CPU Usage vs. Thread Count - The CPU usage percentage doesn't scale perfectly linearly with thread count - At 32 threads, we see 2662% usage (83.2% of theoretical 3200%) - This indicates some scheduling overhead or resource contention ## Compression vs. Decompression Performance - Decompression scales better than compression at higher thread counts - Compression shows more performance variability across dictionary sizes - At 32 threads, decompression speed is ~6.6x faster than compression ## Conclusion The system demonstrates good multi-core utilization, with performance scaling reasonably well up to 32 threads. The scaling efficiency gradually decreases as thread count increases, which is expected behavior due to increased synchronization overhead and potential memory bandwidth limitations. For optimal efficiency, workloads on this system might perform best with 8-16 threads per process, with multiple processes to utilize all 192 available hardware threads. The benchmark results suggest that while the system can effectively utilize multiple cores, there are diminishing returns beyond 16-32 threads for this specific workload. This is typical for memory-intensive operations like compression/decompression where memory bandwidth can become a bottleneck.

Model: claude-3-7-sonnet-202502192025-06-24 05:59:55

Context:

[
  {
    "role": "user",
    "content": "分析下列7b benchmark的结果 看看是否充分动用了多核性能 输出为英文\n\n```\n=== Running with 1 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=en_US.UTF-8 Threads:192 OPEN_MAX:1024\n\n mt1\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.13.0-rc2-tdxvfio : #1 SMP PREEMPT_DYNAMIC Sat Jan 25 06:35:55 UTC 2025 : x86_64\nPageSize:4KB THP:madvise hwcap:6 hwcap2:2\nINTEL(R) XEON(R) PLATINUM 8558 (C06F2)\n\n1T CPU Freq (MHz):  2088  2086  2084  2088  2083  2080  2077\n\nRAM size:  2063589 MB,  # CPU hardware threads: 192\nRAM usage:    437 MB,  # Benchmark threads:      1\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:       3817   100   3724   3714  |      27971   100   2384   2388\n23:       3841   100   3931   3914  |      41032   100   3544   3552\n24:       6752   100   7278   7260  |      52090   100   4577   4573\n25:       5558   100   6343   6347  |      51706   100   4595   4602\n----------------------------------  | ------------------------------\nAvr:      4992   100   5319   5309  |      43200   100   3775   3779\nTot:             100   4547   4544\n\n=== Running with 2 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=en_US.UTF-8 Threads:192 OPEN_MAX:1024\n\n mt2\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.13.0-rc2-tdxvfio : #1 SMP PREEMPT_DYNAMIC Sat Jan 25 06:35:55 UTC 2025 : x86_64\nPageSize:4KB THP:madvise hwcap:6 hwcap2:2\nINTEL(R) XEON(R) PLATINUM 8558 (C06F2)\n\n1T CPU Freq (MHz):  2090  2087  2090  2092  2090  2090  2090\n2T CPU Freq (MHz): 199% 2080   199% 2084\n\nRAM size:  2063589 MB,  # CPU hardware threads: 192\nRAM usage:    444 MB,  # Benchmark threads:      2\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:       9629   201   4652   9368  |      82713   188   3763   7062\n23:       9734   187   5290   9918  |      63014   185   2947   5454\n24:       9831   191   5527  10571  |      55239   158   3078   4849\n25:       9970   196   5794  11384  |      54778   153   3176   4876\n----------------------------------  | ------------------------------\nAvr:      9791   194   5316  10310  |      63936   171   3241   5560\nTot:             183   4278   7935\n\n=== Running with 4 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=en_US.UTF-8 Threads:192 OPEN_MAX:1024\n\n mt4\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.13.0-rc2-tdxvfio : #1 SMP PREEMPT_DYNAMIC Sat Jan 25 06:35:55 UTC 2025 : x86_64\nPageSize:4KB THP:madvise hwcap:6 hwcap2:2\nINTEL(R) XEON(R) PLATINUM 8558 (C06F2)\n\n1T CPU Freq (MHz):  2082  2086  2085  2086  2090  2092  2090\n4T CPU Freq (MHz): 399% 2085   398% 2078\n\nRAM size:  2063589 MB,  # CPU hardware threads: 192\nRAM usage:    889 MB,  # Benchmark threads:      4\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:      19588   349   5456  19056  |     111937   393   2428   9550\n23:      19538   362   5498  19908  |     110701   385   2488   9579\n24:      19514   384   5467  20982  |     110283   398   2431   9678\n25:      16941   389   4972  19343  |     105827   398   2366   9419\n----------------------------------  | ------------------------------\nAvr:     18895   371   5348  19822  |     109687   394   2428   9556\nTot:             382   3888  14689\n\n=== Running with 8 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=en_US.UTF-8 Threads:192 OPEN_MAX:1024\n\n mt8\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.13.0-rc2-tdxvfio : #1 SMP PREEMPT_DYNAMIC Sat Jan 25 06:35:55 UTC 2025 : x86_64\nPageSize:4KB THP:madvise hwcap:6 hwcap2:2\nINTEL(R) XEON(R) PLATINUM 8558 (C06F2)\n\n1T CPU Freq (MHz):  2060  2087  2088  2088  2084  2079  2080\n8T CPU Freq (MHz): 796% 2074   798% 2083\n\nRAM size:  2063589 MB,  # CPU hardware threads: 192\nRAM usage:   1779 MB,  # Benchmark threads:      8\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:      37361   758   4794  36346  |     223172   797   2389  19030\n23:      34559   778   4529  35212  |     218566   792   2388  18906\n24:      33963   802   4555  36517  |     216762   794   2396  19019\n25:      30123   785   4381  34393  |     211360   791   2378  18806\n----------------------------------  | ------------------------------\nAvr:     34001   781   4565  35617  |     217465   793   2387  18941\nTot:             787   3476  27279\n\n=== Running with 16 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=en_US.UTF-8 Threads:192 OPEN_MAX:1024\n\n mt16\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.13.0-rc2-tdxvfio : #1 SMP PREEMPT_DYNAMIC Sat Jan 25 06:35:55 UTC 2025 : x86_64\nPageSize:4KB THP:madvise hwcap:6 hwcap2:2\nINTEL(R) XEON(R) PLATINUM 8558 (C06F2)\n\n1T CPU Freq (MHz):  2080  2080  2080  2080  2080  2080  2081\n16T CPU Freq (MHz): 1573% 2044   1593% 2073\n\nRAM size:  2063589 MB,  # CPU hardware threads: 192\nRAM usage:   3559 MB,  # Benchmark threads:     16\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:      73737  1535   4672  71731  |     441686  1581   2383  37662\n23:      68911  1549   4532  70213  |     440096  1591   2393  38071\n24:      73625  1515   5224  79162  |     438819  1588   2425  38503\n25:      71295  1551   5249  81403  |     427981  1560   2440  38078\n----------------------------------  | ------------------------------\nAvr:     71892  1538   4919  75627  |     437145  1580   2410  38079\nTot:            1559   3665  56853\n\n=== Running with 32 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=en_US.UTF-8 Threads:192 OPEN_MAX:1024\n\n mt32\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.13.0-rc2-tdxvfio : #1 SMP PREEMPT_DYNAMIC Sat Jan 25 06:35:55 UTC 2025 : x86_64\nPageSize:4KB THP:madvise hwcap:6 hwcap2:2\nINTEL(R) XEON(R) PLATINUM 8558 (C06F2)\n\n1T CPU Freq (MHz):  2076  2090  2089  2090  2092  2091  2091\n32T CPU Freq (MHz): 3171% 2068   3177% 2079\n\nRAM size:  2063589 MB,  # CPU hardware threads: 192\nRAM usage:   7119 MB,  # Benchmark threads:     32\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:     149480  2869   5068 145415  |     878111  3076   2434  74867\n23:     106687  2507   4336 108701  |     753529  2601   2506  65191\n24:     139532  2916   5145 150025  |     784756  2598   2650  68860\n25:      88521  2469   4094 101070  |     772136  2261   3038  68697\n----------------------------------  | ------------------------------\nAvr:    121055  2690   4661 126303  |     797133  2634   2657  69404\nTot:            2662   3659  97853\n```"
  }
]

Response:

# Analysis of 7-Zip Benchmark Results for Multi-Core Performance ## Overview This benchmark tests the performance of 7-Zip compression and decompression on an Intel Xeon Platinum 8558 system with 192 hardware threads, running with different thread counts (1, 2, 4, 8, 16, and 32 threads). ## Hardware Utilization Analysis ### Thread Scaling 1. **Single-threaded (1T) baseline**: 4,544 MIPS total rating 2. **2 threads**: 7,935 MIPS (1.75× scaling from 1T) 3. **4 threads**: 14,689 MIPS (3.23× scaling from 1T) 4. **8 threads**: 27,279 MIPS (6.00× scaling from 1T) 5. **16 threads**: 56,853 MIPS (12.51× scaling from 1T) 6. **32 threads**: 97,853 MIPS (21.53× scaling from 1T) ### CPU Usage Percentage - **2 threads**: 183% average usage (91.5% efficiency) - **4 threads**: 382% average usage (95.5% efficiency) - **8 threads**: 787% average usage (98.4% efficiency) - **16 threads**: 1559% average usage (97.4% efficiency) - **32 threads**: 2662% average usage (83.2% efficiency) ### Frequency Scaling The CPU maintains a consistent frequency of approximately 2080-2090 MHz across all thread counts, showing no significant frequency throttling even at higher thread counts. ## Performance Analysis 1. **Near-linear scaling**: The performance scales almost linearly up to 16 threads, with efficiency above 90% for 2-16 threads. 2. **Compression vs. Decompression**: - Compression shows better thread utilization at higher thread counts - Decompression shows diminishing returns beyond 16 threads 3. **Efficiency drop at 32 threads**: At 32 threads, efficiency drops to 83.2%, indicating: - Potential resource contention - Diminishing returns from parallelization - Possible NUMA effects or memory bandwidth limitations ## Conclusion The benchmark demonstrates excellent multi-core utilization up to 16 threads, with nearly linear scaling. However, at 32 threads, while still showing good scaling (21.53× over single-thread), efficiency begins to decline. This suggests that for this particular workload on this system: 1. The sweet spot for performance/efficiency is around 8-16 threads 2. The system effectively utilizes multi-core capabilities for the 7-Zip workload 3. There's still significant headroom for scaling to more threads, as only 32 of 192 available hardware threads were tested Given that the system has 192 hardware threads but the test only went up to 32 threads, there's potential for even higher absolute performance, though likely with continued declining efficiency per thread.

Model: claude-3-7-sonnet-202502192025-06-24 05:58:21

Context:

[
  {
    "role": "user",
    "content": "分析下列7b benchmark的结果 看看是否充分动用了多核性能：\n\n```\n=== Running with 1 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=en_US.UTF-8 Threads:192 OPEN_MAX:1024\n\n mt1\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.13.0-rc2-tdxvfio : #1 SMP PREEMPT_DYNAMIC Sat Jan 25 06:35:55 UTC 2025 : x86_64\nPageSize:4KB THP:madvise hwcap:6 hwcap2:2\nINTEL(R) XEON(R) PLATINUM 8558 (C06F2)\n\n1T CPU Freq (MHz):  2088  2086  2084  2088  2083  2080  2077\n\nRAM size:  2063589 MB,  # CPU hardware threads: 192\nRAM usage:    437 MB,  # Benchmark threads:      1\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:       3817   100   3724   3714  |      27971   100   2384   2388\n23:       3841   100   3931   3914  |      41032   100   3544   3552\n24:       6752   100   7278   7260  |      52090   100   4577   4573\n25:       5558   100   6343   6347  |      51706   100   4595   4602\n----------------------------------  | ------------------------------\nAvr:      4992   100   5319   5309  |      43200   100   3775   3779\nTot:             100   4547   4544\n\n=== Running with 2 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=en_US.UTF-8 Threads:192 OPEN_MAX:1024\n\n mt2\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.13.0-rc2-tdxvfio : #1 SMP PREEMPT_DYNAMIC Sat Jan 25 06:35:55 UTC 2025 : x86_64\nPageSize:4KB THP:madvise hwcap:6 hwcap2:2\nINTEL(R) XEON(R) PLATINUM 8558 (C06F2)\n\n1T CPU Freq (MHz):  2090  2087  2090  2092  2090  2090  2090\n2T CPU Freq (MHz): 199% 2080   199% 2084\n\nRAM size:  2063589 MB,  # CPU hardware threads: 192\nRAM usage:    444 MB,  # Benchmark threads:      2\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:       9629   201   4652   9368  |      82713   188   3763   7062\n23:       9734   187   5290   9918  |      63014   185   2947   5454\n24:       9831   191   5527  10571  |      55239   158   3078   4849\n25:       9970   196   5794  11384  |      54778   153   3176   4876\n----------------------------------  | ------------------------------\nAvr:      9791   194   5316  10310  |      63936   171   3241   5560\nTot:             183   4278   7935\n\n=== Running with 4 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=en_US.UTF-8 Threads:192 OPEN_MAX:1024\n\n mt4\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.13.0-rc2-tdxvfio : #1 SMP PREEMPT_DYNAMIC Sat Jan 25 06:35:55 UTC 2025 : x86_64\nPageSize:4KB THP:madvise hwcap:6 hwcap2:2\nINTEL(R) XEON(R) PLATINUM 8558 (C06F2)\n\n1T CPU Freq (MHz):  2082  2086  2085  2086  2090  2092  2090\n4T CPU Freq (MHz): 399% 2085   398% 2078\n\nRAM size:  2063589 MB,  # CPU hardware threads: 192\nRAM usage:    889 MB,  # Benchmark threads:      4\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:      19588   349   5456  19056  |     111937   393   2428   9550\n23:      19538   362   5498  19908  |     110701   385   2488   9579\n24:      19514   384   5467  20982  |     110283   398   2431   9678\n25:      16941   389   4972  19343  |     105827   398   2366   9419\n----------------------------------  | ------------------------------\nAvr:     18895   371   5348  19822  |     109687   394   2428   9556\nTot:             382   3888  14689\n\n=== Running with 8 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=en_US.UTF-8 Threads:192 OPEN_MAX:1024\n\n mt8\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.13.0-rc2-tdxvfio : #1 SMP PREEMPT_DYNAMIC Sat Jan 25 06:35:55 UTC 2025 : x86_64\nPageSize:4KB THP:madvise hwcap:6 hwcap2:2\nINTEL(R) XEON(R) PLATINUM 8558 (C06F2)\n\n1T CPU Freq (MHz):  2060  2087  2088  2088  2084  2079  2080\n8T CPU Freq (MHz): 796% 2074   798% 2083\n\nRAM size:  2063589 MB,  # CPU hardware threads: 192\nRAM usage:   1779 MB,  # Benchmark threads:      8\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:      37361   758   4794  36346  |     223172   797   2389  19030\n23:      34559   778   4529  35212  |     218566   792   2388  18906\n24:      33963   802   4555  36517  |     216762   794   2396  19019\n25:      30123   785   4381  34393  |     211360   791   2378  18806\n----------------------------------  | ------------------------------\nAvr:     34001   781   4565  35617  |     217465   793   2387  18941\nTot:             787   3476  27279\n\n=== Running with 16 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=en_US.UTF-8 Threads:192 OPEN_MAX:1024\n\n mt16\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.13.0-rc2-tdxvfio : #1 SMP PREEMPT_DYNAMIC Sat Jan 25 06:35:55 UTC 2025 : x86_64\nPageSize:4KB THP:madvise hwcap:6 hwcap2:2\nINTEL(R) XEON(R) PLATINUM 8558 (C06F2)\n\n1T CPU Freq (MHz):  2080  2080  2080  2080  2080  2080  2081\n16T CPU Freq (MHz): 1573% 2044   1593% 2073\n\nRAM size:  2063589 MB,  # CPU hardware threads: 192\nRAM usage:   3559 MB,  # Benchmark threads:     16\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:      73737  1535   4672  71731  |     441686  1581   2383  37662\n23:      68911  1549   4532  70213  |     440096  1591   2393  38071\n24:      73625  1515   5224  79162  |     438819  1588   2425  38503\n25:      71295  1551   5249  81403  |     427981  1560   2440  38078\n----------------------------------  | ------------------------------\nAvr:     71892  1538   4919  75627  |     437145  1580   2410  38079\nTot:            1559   3665  56853\n\n=== Running with 32 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=en_US.UTF-8 Threads:192 OPEN_MAX:1024\n\n mt32\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.13.0-rc2-tdxvfio : #1 SMP PREEMPT_DYNAMIC Sat Jan 25 06:35:55 UTC 2025 : x86_64\nPageSize:4KB THP:madvise hwcap:6 hwcap2:2\nINTEL(R) XEON(R) PLATINUM 8558 (C06F2)\n\n1T CPU Freq (MHz):  2076  2090  2089  2090  2092  2091  2091\n32T CPU Freq (MHz): 3171% 2068   3177% 2079\n\nRAM size:  2063589 MB,  # CPU hardware threads: 192\nRAM usage:   7119 MB,  # Benchmark threads:     32\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:     149480  2869   5068 145415  |     878111  3076   2434  74867\n23:     106687  2507   4336 108701  |     753529  2601   2506  65191\n24:     139532  2916   5145 150025  |     784756  2598   2650  68860\n25:      88521  2469   4094 101070  |     772136  2261   3038  68697\n----------------------------------  | ------------------------------\nAvr:    121055  2690   4661 126303  |     797133  2634   2657  69404\nTot:            2662   3659  97853\n```"
  },
  {
    "role": "assistant",
    "content": "# 7-Zip 基准测试结果分析\n\n根据提供的7-Zip基准测试结果，我将分析多线程性能扩展性，评估系统是否充分利用了多核性能。\n\n## 硬件配置\n\n- CPU: Intel Xeon Platinum 8558\n- 硬件线程数: 192\n- RAM: 约2TB (2,063,589 MB)\n\n## 多线程性能扩展分析\n\n### 总评分(Tot Rating)随线程数的增长:\n\n| 线程数 | 总评分 | 线性理想值 | 实际效率 |\n|--------|--------|------------|----------|\n| 1      | 4,544  | 4,544      | 100%     |\n| 2      | 7,935  | 9,088      | 87.3%    |\n| 4      | 14,689 | 18,176     | 80.8%    |\n| 8      | 27,279 | 36,352     | 75.0%    |\n| 16     | 56,853 | 72,704     | 78.2%    |\n| 32     | 97,853 | 145,408    | 67.3%    |\n\n### CPU使用率分析:\n\n1. **单线程测试**: 100% CPU使用率，基准线\n2. **2线程测试**: 183% CPU使用率 (理想为200%)，效率91.5%\n3. **4线程测试**: 382% CPU使用率 (理想为400%)，效率95.5%\n4. **8线程测试**: 787% CPU使用率 (理想为800%)，效率98.4%\n5. **16线程测试**: 1559% CPU使用率 (理想为1600%)，效率97.4%\n6. **32线程测试**: 2662% CPU使用率 (理想为3200%)，效率83.2%\n\n### 压缩速度(KiB/s)扩展性:\n\n| 线程数 | 平均压缩速度 | 相对于单线程的倍数 |\n|--------|--------------|-------------------|\n| 1      | 4,992        | 1.0x              |\n| 2      | 9,791        | 1.96x             |\n| 4      | 18,895       | 3.78x             |\n| 8      | 34,001       | 6.81x             |\n| 16     | 71,892       | 14.40x            |\n| 32     | 121,055      | 24.25x            |\n\n### 解压缩速度(KiB/s)扩展性:\n\n| 线程数 | 平均解压缩速度 | 相对于单线程的倍数 |\n|--------|----------------|-------------------|\n| 1      | 43,200         | 1.0x              |\n| 2      | 63,936         | 1.48x             |\n| 4      | 109,687        | 2.54x             |\n| 8      | 217,465        | 5.03x             |\n| 16     | 437,145        | 10.12x            |\n| 32     | 797,133        | 18.45x            |\n\n## 结论\n\n1. **良好的线性扩展性**: \n   - 在32线程时，压缩性能达到单线程的24.25倍，接近理想的32倍\n   - 解压缩性能扩展性较差，32线程时仅达到单线程的18.45倍\n\n2. **CPU利用率**:\n   - 在较低线程数(1-16)时，CPU利用率非常高(>95%)\n   - 32线程时效率下降到83.2%，表明开始出现资源竞争或调度开销\n\n3. **总体效率**:\n   - 随着线程数增加，效率逐渐下降，从单线程的100%降至32线程的67.3%\n   - 这是多核系统中常见的现象，主要受内存带宽、缓存竞争等因素影响\n\n4. **多核性能利用评估**:\n   - 系统在32线程时仍能保持较高的扩展性，说明多核性能被充分利用\n   - 但未测试更高线程数(如64、128或全部192线程)，无法评估在更高并发下的表现\n\n**建议**:\n- 对于压缩任务，增加线程数持续带来性能提升，可以使用更多线程\n- 对于解压缩任务，线程数超过32后可能收益递减\n- 考虑测试更高线程数(64-192)以确定最佳线程配置\n- 系统整体表现良好，多核性能得到了有效利用"
  },
  {
    "role": "user",
    "content": "```\n=== Running with 1 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=C.UTF-8 Threads:32 OPEN_MAX:4096\n\n mt1\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.9.0-dstack : #1 SMP PREEMPT_DYNAMIC Thu May 30 14:26:20 UTC 2024 : x86_64 : KVMKVMKVM : [82][BA]\nPageSize:4KB hwcap:6 hwcap2:2\nGenuineIntel (C06F2) \n\n1T CPU Freq (MHz):  1016  2155  2679  2678  2660  2691  2707\n\nRAM size:   15033 MB,  # CPU hardware threads:  32\nRAM usage:    437 MB,  # Benchmark threads:      1\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:       3713   100   3613   3613  |      35293   100   3017   3013\n23:       3191   100   3260   3252  |      37173   100   3218   3218\n24:       4803   100   5171   5165  |      46818   100   4104   4110\n25:       4360   100   4972   4979  |      46674   100   4163   4154\n----------------------------------  | ------------------------------\nAvr:      4017   100   4254   4252  |      41490   100   3626   3624\nTot:             100   3940   3938\n\n=== Running with 2 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=C.UTF-8 Threads:32 OPEN_MAX:4096\n\n mt2\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.9.0-dstack : #1 SMP PREEMPT_DYNAMIC Thu May 30 14:26:20 UTC 2024 : x86_64 : KVMKVMKVM : [82][BA]\nPageSize:4KB hwcap:6 hwcap2:2\nGenuineIntel (C06F2) \n\n1T CPU Freq (MHz):  3689  3774  3754  3691  3701  3651  3687\n2T CPU Freq (MHz): 199% 2336   200% 2510  \n\nRAM size:   15033 MB,  # CPU hardware threads:  32\nRAM usage:    444 MB,  # Benchmark threads:      2\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:      11841   202   5700  11519  |      70557   199   3031   6024\n23:      10211   208   5007  10404  |      69604   200   3012   6025\n24:       9971   209   5126  10721  |      68098   200   2991   5978\n25:       9383   204   5258  10714  |      65617   197   2964   5840\n----------------------------------  | ------------------------------\nAvr:     10351   206   5273  10840  |      68469   199   2999   5967\nTot:             202   4136   8403\n\n=== Running with 4 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=C.UTF-8 Threads:32 OPEN_MAX:4096\n\n mt4\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.9.0-dstack : #1 SMP PREEMPT_DYNAMIC Thu May 30 14:26:20 UTC 2024 : x86_64 : KVMKVMKVM : [82][BA]\nPageSize:4KB hwcap:6 hwcap2:2\nGenuineIntel (C06F2) \n\n1T CPU Freq (MHz):  2393  2421  2694  2710  2704  2703  2696\n4T CPU Freq (MHz): 396% 2293   379% 2514  \n\nRAM size:   15033 MB,  # CPU hardware threads:  32\nRAM usage:    889 MB,  # Benchmark threads:      4\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:      23292   414   5469  22659  |     138207   393   3000  11791\n23:      19882   408   4963  20258  |     136779   397   2979  11835\n24:      18774   403   5003  20186  |     134701   399   2965  11821\n25:       7012   285   2808   8007  |     130947   393   2962  11654\n----------------------------------  | ------------------------------\nAvr:     17240   378   4561  17777  |     135158   396   2977  11775\nTot:             387   3769  14776\n\n=== Running with 8 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=C.UTF-8 Threads:32 OPEN_MAX:4096\n\n mt8\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.9.0-dstack : #1 SMP PREEMPT_DYNAMIC Thu May 30 14:26:20 UTC 2024 : x86_64 : KVMKVMKVM : [82][BA]\nPageSize:4KB hwcap:6 hwcap2:2\nGenuineIntel (C06F2) \n\n1T CPU Freq (MHz):  2677  2700  2700  2704  2693  2701  2704\n8T CPU Freq (MHz): 732% 2311   790% 2647  \n\nRAM size:   15033 MB,  # CPU hardware threads:  32\nRAM usage:   1779 MB,  # Benchmark threads:      8\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:      40796   801   4955  39686  |     273752   784   2977  23343\n23:      33627   744   4603  34263  |     271827   785   2996  23514\n24:      21221   588   3878  22817  |     264065   787   2942  23169\n25:      12488   633   2251  14259  |     258702   791   2912  23019\n----------------------------------  | ------------------------------\nAvr:     27033   692   3922  27756  |     267086   787   2957  23261\nTot:             739   3439  25509\n\n=== Running with 16 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=C.UTF-8 Threads:32 OPEN_MAX:4096\n\n mt16\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.9.0-dstack : #1 SMP PREEMPT_DYNAMIC Thu May 30 14:26:20 UTC 2024 : x86_64 : KVMKVMKVM : [82][BA]\nPageSize:4KB hwcap:6 hwcap2:2\nGenuineIntel (C06F2) \n\n1T CPU Freq (MHz):  2685  2710  2703  2701  2706  2706  2707\n16T CPU Freq (MHz): 1512% 2141   1513% 2434  \n\nRAM size:   15033 MB,  # CPU hardware threads:  32\nRAM usage:   3559 MB,  # Benchmark threads:     16\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:      62956  1497   4091  61245  |     510677  1501   2902  43545\n23:      54418  1459   3800  55445  |     500444  1517   2854  43292\n24:      32189  1247   2776  34611  |     449538  1402   2813  39443\n25:      26222  1332   2248  29939  |     420751  1401   2673  37434\n----------------------------------  | ------------------------------\nAvr:     43946  1384   3229  45310  |     470353  1455   2810  40929\nTot:            1419   3020  43119\n\n=== Running with 32 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=C.UTF-8 Threads:32 OPEN_MAX:4096\n\n mt32\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.9.0-dstack : #1 SMP PREEMPT_DYNAMIC Thu May 30 14:26:20 UTC 2024 : x86_64 : KVMKVMKVM : [82][BA]\nPageSize:4KB hwcap:6 hwcap2:2\nGenuineIntel (C06F2) \n\n1T CPU Freq (MHz):  1005  2081  2702  2686  2671  2676  2645\n16T CPU Freq (MHz): 1475% 2151   1514% 2443  \n\nRAM size:   15033 MB,  # CPU hardware threads:  32\nRAM usage:   7119 MB,  # Benchmark threads:     32\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:      90735  2903   3041  88267  |     734482  2877   2176  62621\n23:      86337  2895   3038  87967  |     748068  2843   2277  64718\n24:      79462  2413   3541  85438  |     777250  2786   2448  68201\n25:      51613  2452   2403  58930  |     776382  2848   2426  69075\n----------------------------------  | ------------------------------\nAvr:     77036  2666   3006  80151  |     759046  2838   2332  66154\nTot:            2752   2669  73152\n```\n输出相同格式的分析结果 但是用英文"
  }
]

Response:

# Analysis of 7-Zip Benchmark Results Based on the provided 7-Zip benchmark results, I will analyze the multi-threaded performance scalability to evaluate whether the system effectively utilizes its multi-core capabilities. ## Hardware Configuration - CPU: Intel Xeon (C06F2) in a virtualized environment (KVM) - Hardware threads: 32 - RAM: 15,033 MB ## Multi-threaded Performance Scaling Analysis ### Total Rating Growth with Thread Count: | Threads | Total Rating | Linear Ideal | Actual Efficiency | |---------|--------------|--------------|-------------------| | 1 | 3,938 | 3,938 | 100% | | 2 | 8,403 | 7,876 | 106.7% | | 4 | 14,776 | 15,752 | 93.8% | | 8 | 25,509 | 31,504 | 81.0% | | 16 | 43,119 | 63,008 | 68.4% | | 32 | 73,152 | 126,016 | 58.0% | ### CPU Utilization Analysis: 1. **Single-thread test**: 100% CPU utilization, baseline 2. **2-thread test**: 202% CPU utilization (ideal: 200%), efficiency 101.0% 3. **4-thread test**: 387% CPU utilization (ideal: 400%), efficiency 96.8% 4. **8-thread test**: 739% CPU utilization (ideal: 800%), efficiency 92.4% 5. **16-thread test**: 1419% CPU utilization (ideal: 1600%), efficiency 88.7% 6. **32-thread test**: 2752% CPU utilization (ideal: 3200%), efficiency 86.0% ### Compression Speed (KiB/s) Scalability: | Threads | Avg Compression Speed | Multiple of Single-thread | |---------|----------------------|--------------------------| | 1 | 4,017 | 1.0x | | 2 | 10,351 | 2.58x | | 4 | 17,240 | 4.29x | | 8 | 27,033 | 6.73x | | 16 | 43,946 | 10.94x | | 32 | 77,036 | 19.18x | ### Decompression Speed (KiB/s) Scalability: | Threads | Avg Decompression Speed | Multiple of Single-thread | |---------|------------------------|--------------------------| | 1 | 41,490 | 1.0x | | 2 | 68,469 | 1.65x | | 4 | 135,158 | 3.26x | | 8 | 267,086 | 6.44x | | 16 | 470,353 | 11.34x | | 32 | 759,046 | 18.29x | ## Conclusion 1. **Good Linear Scalability**: - Compression performance reaches 19.18x with 32 threads compared to single-thread - Decompression performance reaches 18.29x with 32 threads compared to single-thread - Both show good scaling but fall short of the ideal 32x 2. **CPU Utilization**: - Very high CPU utilization at lower thread counts (>100% for 2 threads) - Gradually decreasing efficiency as thread count increases, but still maintains 86% at 32 threads 3. **Overall Efficiency**: - Performance efficiency decreases from 100% at single-thread to 58% at 32 threads - This is typical in multi-core systems due to memory bandwidth limitations, cache contention, and scheduling overhead 4. **Multi-core Utilization Assessment**: - The system demonstrates strong scaling up to the maximum available threads (32) - Super-linear scaling observed in some cases at 2 threads, likely due to better cache utilization - Dictionary size 25 shows reduced scaling, indicating potential memory bandwidth limitations **Recommendations**: - For compression tasks, using all available cores provides significant benefits - For decompression tasks, scaling is good but with diminishing returns beyond 16 threads - The system effectively utilizes its multi-core capabilities, achieving 58-86% efficiency at maximum thread count - Consider tuning dictionary sizes based on workload, as larger dictionaries show reduced scaling at higher thread counts The benchmark demonstrates that the system is effectively utilizing its multi-core capabilities, with good scaling across the entire range of available hardware threads.

Model: claude-3-7-sonnet-202502192025-06-24 05:57:36

Context:

[
  {
    "role": "user",
    "content": "分析下列7b benchmark的结果 看看是否充分动用了多核性能：\n\n```\n=== Running with 1 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=en_US.UTF-8 Threads:192 OPEN_MAX:1024\n\n mt1\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.13.0-rc2-tdxvfio : #1 SMP PREEMPT_DYNAMIC Sat Jan 25 06:35:55 UTC 2025 : x86_64\nPageSize:4KB THP:madvise hwcap:6 hwcap2:2\nINTEL(R) XEON(R) PLATINUM 8558 (C06F2)\n\n1T CPU Freq (MHz):  2088  2086  2084  2088  2083  2080  2077\n\nRAM size:  2063589 MB,  # CPU hardware threads: 192\nRAM usage:    437 MB,  # Benchmark threads:      1\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:       3817   100   3724   3714  |      27971   100   2384   2388\n23:       3841   100   3931   3914  |      41032   100   3544   3552\n24:       6752   100   7278   7260  |      52090   100   4577   4573\n25:       5558   100   6343   6347  |      51706   100   4595   4602\n----------------------------------  | ------------------------------\nAvr:      4992   100   5319   5309  |      43200   100   3775   3779\nTot:             100   4547   4544\n\n=== Running with 2 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=en_US.UTF-8 Threads:192 OPEN_MAX:1024\n\n mt2\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.13.0-rc2-tdxvfio : #1 SMP PREEMPT_DYNAMIC Sat Jan 25 06:35:55 UTC 2025 : x86_64\nPageSize:4KB THP:madvise hwcap:6 hwcap2:2\nINTEL(R) XEON(R) PLATINUM 8558 (C06F2)\n\n1T CPU Freq (MHz):  2090  2087  2090  2092  2090  2090  2090\n2T CPU Freq (MHz): 199% 2080   199% 2084\n\nRAM size:  2063589 MB,  # CPU hardware threads: 192\nRAM usage:    444 MB,  # Benchmark threads:      2\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:       9629   201   4652   9368  |      82713   188   3763   7062\n23:       9734   187   5290   9918  |      63014   185   2947   5454\n24:       9831   191   5527  10571  |      55239   158   3078   4849\n25:       9970   196   5794  11384  |      54778   153   3176   4876\n----------------------------------  | ------------------------------\nAvr:      9791   194   5316  10310  |      63936   171   3241   5560\nTot:             183   4278   7935\n\n=== Running with 4 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=en_US.UTF-8 Threads:192 OPEN_MAX:1024\n\n mt4\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.13.0-rc2-tdxvfio : #1 SMP PREEMPT_DYNAMIC Sat Jan 25 06:35:55 UTC 2025 : x86_64\nPageSize:4KB THP:madvise hwcap:6 hwcap2:2\nINTEL(R) XEON(R) PLATINUM 8558 (C06F2)\n\n1T CPU Freq (MHz):  2082  2086  2085  2086  2090  2092  2090\n4T CPU Freq (MHz): 399% 2085   398% 2078\n\nRAM size:  2063589 MB,  # CPU hardware threads: 192\nRAM usage:    889 MB,  # Benchmark threads:      4\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:      19588   349   5456  19056  |     111937   393   2428   9550\n23:      19538   362   5498  19908  |     110701   385   2488   9579\n24:      19514   384   5467  20982  |     110283   398   2431   9678\n25:      16941   389   4972  19343  |     105827   398   2366   9419\n----------------------------------  | ------------------------------\nAvr:     18895   371   5348  19822  |     109687   394   2428   9556\nTot:             382   3888  14689\n\n=== Running with 8 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=en_US.UTF-8 Threads:192 OPEN_MAX:1024\n\n mt8\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.13.0-rc2-tdxvfio : #1 SMP PREEMPT_DYNAMIC Sat Jan 25 06:35:55 UTC 2025 : x86_64\nPageSize:4KB THP:madvise hwcap:6 hwcap2:2\nINTEL(R) XEON(R) PLATINUM 8558 (C06F2)\n\n1T CPU Freq (MHz):  2060  2087  2088  2088  2084  2079  2080\n8T CPU Freq (MHz): 796% 2074   798% 2083\n\nRAM size:  2063589 MB,  # CPU hardware threads: 192\nRAM usage:   1779 MB,  # Benchmark threads:      8\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:      37361   758   4794  36346  |     223172   797   2389  19030\n23:      34559   778   4529  35212  |     218566   792   2388  18906\n24:      33963   802   4555  36517  |     216762   794   2396  19019\n25:      30123   785   4381  34393  |     211360   791   2378  18806\n----------------------------------  | ------------------------------\nAvr:     34001   781   4565  35617  |     217465   793   2387  18941\nTot:             787   3476  27279\n\n=== Running with 16 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=en_US.UTF-8 Threads:192 OPEN_MAX:1024\n\n mt16\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.13.0-rc2-tdxvfio : #1 SMP PREEMPT_DYNAMIC Sat Jan 25 06:35:55 UTC 2025 : x86_64\nPageSize:4KB THP:madvise hwcap:6 hwcap2:2\nINTEL(R) XEON(R) PLATINUM 8558 (C06F2)\n\n1T CPU Freq (MHz):  2080  2080  2080  2080  2080  2080  2081\n16T CPU Freq (MHz): 1573% 2044   1593% 2073\n\nRAM size:  2063589 MB,  # CPU hardware threads: 192\nRAM usage:   3559 MB,  # Benchmark threads:     16\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:      73737  1535   4672  71731  |     441686  1581   2383  37662\n23:      68911  1549   4532  70213  |     440096  1591   2393  38071\n24:      73625  1515   5224  79162  |     438819  1588   2425  38503\n25:      71295  1551   5249  81403  |     427981  1560   2440  38078\n----------------------------------  | ------------------------------\nAvr:     71892  1538   4919  75627  |     437145  1580   2410  38079\nTot:            1559   3665  56853\n\n=== Running with 32 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=en_US.UTF-8 Threads:192 OPEN_MAX:1024\n\n mt32\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.13.0-rc2-tdxvfio : #1 SMP PREEMPT_DYNAMIC Sat Jan 25 06:35:55 UTC 2025 : x86_64\nPageSize:4KB THP:madvise hwcap:6 hwcap2:2\nINTEL(R) XEON(R) PLATINUM 8558 (C06F2)\n\n1T CPU Freq (MHz):  2076  2090  2089  2090  2092  2091  2091\n32T CPU Freq (MHz): 3171% 2068   3177% 2079\n\nRAM size:  2063589 MB,  # CPU hardware threads: 192\nRAM usage:   7119 MB,  # Benchmark threads:     32\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:     149480  2869   5068 145415  |     878111  3076   2434  74867\n23:     106687  2507   4336 108701  |     753529  2601   2506  65191\n24:     139532  2916   5145 150025  |     784756  2598   2650  68860\n25:      88521  2469   4094 101070  |     772136  2261   3038  68697\n----------------------------------  | ------------------------------\nAvr:    121055  2690   4661 126303  |     797133  2634   2657  69404\nTot:            2662   3659  97853\n```"
  },
  {
    "role": "assistant",
    "content": "# 7-Zip 基准测试结果分析\n\n根据提供的7-Zip基准测试结果，我将分析多线程性能扩展性，评估系统是否充分利用了多核性能。\n\n## 硬件配置\n\n- CPU: Intel Xeon Platinum 8558\n- 硬件线程数: 192\n- RAM: 约2TB (2,063,589 MB)\n\n## 多线程性能扩展分析\n\n### 总评分(Tot Rating)随线程数的增长:\n\n| 线程数 | 总评分 | 线性理想值 | 实际效率 |\n|--------|--------|------------|----------|\n| 1      | 4,544  | 4,544      | 100%     |\n| 2      | 7,935  | 9,088      | 87.3%    |\n| 4      | 14,689 | 18,176     | 80.8%    |\n| 8      | 27,279 | 36,352     | 75.0%    |\n| 16     | 56,853 | 72,704     | 78.2%    |\n| 32     | 97,853 | 145,408    | 67.3%    |\n\n### CPU使用率分析:\n\n1. **单线程测试**: 100% CPU使用率，基准线\n2. **2线程测试**: 183% CPU使用率 (理想为200%)，效率91.5%\n3. **4线程测试**: 382% CPU使用率 (理想为400%)，效率95.5%\n4. **8线程测试**: 787% CPU使用率 (理想为800%)，效率98.4%\n5. **16线程测试**: 1559% CPU使用率 (理想为1600%)，效率97.4%\n6. **32线程测试**: 2662% CPU使用率 (理想为3200%)，效率83.2%\n\n### 压缩速度(KiB/s)扩展性:\n\n| 线程数 | 平均压缩速度 | 相对于单线程的倍数 |\n|--------|--------------|-------------------|\n| 1      | 4,992        | 1.0x              |\n| 2      | 9,791        | 1.96x             |\n| 4      | 18,895       | 3.78x             |\n| 8      | 34,001       | 6.81x             |\n| 16     | 71,892       | 14.40x            |\n| 32     | 121,055      | 24.25x            |\n\n### 解压缩速度(KiB/s)扩展性:\n\n| 线程数 | 平均解压缩速度 | 相对于单线程的倍数 |\n|--------|----------------|-------------------|\n| 1      | 43,200         | 1.0x              |\n| 2      | 63,936         | 1.48x             |\n| 4      | 109,687        | 2.54x             |\n| 8      | 217,465        | 5.03x             |\n| 16     | 437,145        | 10.12x            |\n| 32     | 797,133        | 18.45x            |\n\n## 结论\n\n1. **良好的线性扩展性**: \n   - 在32线程时，压缩性能达到单线程的24.25倍，接近理想的32倍\n   - 解压缩性能扩展性较差，32线程时仅达到单线程的18.45倍\n\n2. **CPU利用率**:\n   - 在较低线程数(1-16)时，CPU利用率非常高(>95%)\n   - 32线程时效率下降到83.2%，表明开始出现资源竞争或调度开销\n\n3. **总体效率**:\n   - 随着线程数增加，效率逐渐下降，从单线程的100%降至32线程的67.3%\n   - 这是多核系统中常见的现象，主要受内存带宽、缓存竞争等因素影响\n\n4. **多核性能利用评估**:\n   - 系统在32线程时仍能保持较高的扩展性，说明多核性能被充分利用\n   - 但未测试更高线程数(如64、128或全部192线程)，无法评估在更高并发下的表现\n\n**建议**:\n- 对于压缩任务，增加线程数持续带来性能提升，可以使用更多线程\n- 对于解压缩任务，线程数超过32后可能收益递减\n- 考虑测试更高线程数(64-192)以确定最佳线程配置\n- 系统整体表现良好，多核性能得到了有效利用"
  },
  {
    "role": "user",
    "content": "```\n=== Running with 1 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=C.UTF-8 Threads:32 OPEN_MAX:4096\n\n mt1\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.9.0-dstack : #1 SMP PREEMPT_DYNAMIC Thu May 30 14:26:20 UTC 2024 : x86_64 : KVMKVMKVM : [82][BA]\nPageSize:4KB hwcap:6 hwcap2:2\nGenuineIntel (C06F2) \n\n1T CPU Freq (MHz):  1016  2155  2679  2678  2660  2691  2707\n\nRAM size:   15033 MB,  # CPU hardware threads:  32\nRAM usage:    437 MB,  # Benchmark threads:      1\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:       3713   100   3613   3613  |      35293   100   3017   3013\n23:       3191   100   3260   3252  |      37173   100   3218   3218\n24:       4803   100   5171   5165  |      46818   100   4104   4110\n25:       4360   100   4972   4979  |      46674   100   4163   4154\n----------------------------------  | ------------------------------\nAvr:      4017   100   4254   4252  |      41490   100   3626   3624\nTot:             100   3940   3938\n\n=== Running with 2 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=C.UTF-8 Threads:32 OPEN_MAX:4096\n\n mt2\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.9.0-dstack : #1 SMP PREEMPT_DYNAMIC Thu May 30 14:26:20 UTC 2024 : x86_64 : KVMKVMKVM : [82][BA]\nPageSize:4KB hwcap:6 hwcap2:2\nGenuineIntel (C06F2) \n\n1T CPU Freq (MHz):  3689  3774  3754  3691  3701  3651  3687\n2T CPU Freq (MHz): 199% 2336   200% 2510  \n\nRAM size:   15033 MB,  # CPU hardware threads:  32\nRAM usage:    444 MB,  # Benchmark threads:      2\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:      11841   202   5700  11519  |      70557   199   3031   6024\n23:      10211   208   5007  10404  |      69604   200   3012   6025\n24:       9971   209   5126  10721  |      68098   200   2991   5978\n25:       9383   204   5258  10714  |      65617   197   2964   5840\n----------------------------------  | ------------------------------\nAvr:     10351   206   5273  10840  |      68469   199   2999   5967\nTot:             202   4136   8403\n\n=== Running with 4 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=C.UTF-8 Threads:32 OPEN_MAX:4096\n\n mt4\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.9.0-dstack : #1 SMP PREEMPT_DYNAMIC Thu May 30 14:26:20 UTC 2024 : x86_64 : KVMKVMKVM : [82][BA]\nPageSize:4KB hwcap:6 hwcap2:2\nGenuineIntel (C06F2) \n\n1T CPU Freq (MHz):  2393  2421  2694  2710  2704  2703  2696\n4T CPU Freq (MHz): 396% 2293   379% 2514  \n\nRAM size:   15033 MB,  # CPU hardware threads:  32\nRAM usage:    889 MB,  # Benchmark threads:      4\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:      23292   414   5469  22659  |     138207   393   3000  11791\n23:      19882   408   4963  20258  |     136779   397   2979  11835\n24:      18774   403   5003  20186  |     134701   399   2965  11821\n25:       7012   285   2808   8007  |     130947   393   2962  11654\n----------------------------------  | ------------------------------\nAvr:     17240   378   4561  17777  |     135158   396   2977  11775\nTot:             387   3769  14776\n\n=== Running with 8 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=C.UTF-8 Threads:32 OPEN_MAX:4096\n\n mt8\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.9.0-dstack : #1 SMP PREEMPT_DYNAMIC Thu May 30 14:26:20 UTC 2024 : x86_64 : KVMKVMKVM : [82][BA]\nPageSize:4KB hwcap:6 hwcap2:2\nGenuineIntel (C06F2) \n\n1T CPU Freq (MHz):  2677  2700  2700  2704  2693  2701  2704\n8T CPU Freq (MHz): 732% 2311   790% 2647  \n\nRAM size:   15033 MB,  # CPU hardware threads:  32\nRAM usage:   1779 MB,  # Benchmark threads:      8\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:      40796   801   4955  39686  |     273752   784   2977  23343\n23:      33627   744   4603  34263  |     271827   785   2996  23514\n24:      21221   588   3878  22817  |     264065   787   2942  23169\n25:      12488   633   2251  14259  |     258702   791   2912  23019\n----------------------------------  | ------------------------------\nAvr:     27033   692   3922  27756  |     267086   787   2957  23261\nTot:             739   3439  25509\n\n=== Running with 16 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=C.UTF-8 Threads:32 OPEN_MAX:4096\n\n mt16\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.9.0-dstack : #1 SMP PREEMPT_DYNAMIC Thu May 30 14:26:20 UTC 2024 : x86_64 : KVMKVMKVM : [82][BA]\nPageSize:4KB hwcap:6 hwcap2:2\nGenuineIntel (C06F2) \n\n1T CPU Freq (MHz):  2685  2710  2703  2701  2706  2706  2707\n16T CPU Freq (MHz): 1512% 2141   1513% 2434  \n\nRAM size:   15033 MB,  # CPU hardware threads:  32\nRAM usage:   3559 MB,  # Benchmark threads:     16\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:      62956  1497   4091  61245  |     510677  1501   2902  43545\n23:      54418  1459   3800  55445  |     500444  1517   2854  43292\n24:      32189  1247   2776  34611  |     449538  1402   2813  39443\n25:      26222  1332   2248  29939  |     420751  1401   2673  37434\n----------------------------------  | ------------------------------\nAvr:     43946  1384   3229  45310  |     470353  1455   2810  40929\nTot:            1419   3020  43119\n\n=== Running with 32 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=C.UTF-8 Threads:32 OPEN_MAX:4096\n\n mt32\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.9.0-dstack : #1 SMP PREEMPT_DYNAMIC Thu May 30 14:26:20 UTC 2024 : x86_64 : KVMKVMKVM : [82][BA]\nPageSize:4KB hwcap:6 hwcap2:2\nGenuineIntel (C06F2) \n\n1T CPU Freq (MHz):  1005  2081  2702  2686  2671  2676  2645\n16T CPU Freq (MHz): 1475% 2151   1514% 2443  \n\nRAM size:   15033 MB,  # CPU hardware threads:  32\nRAM usage:   7119 MB,  # Benchmark threads:     32\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:      90735  2903   3041  88267  |     734482  2877   2176  62621\n23:      86337  2895   3038  87967  |     748068  2843   2277  64718\n24:      79462  2413   3541  85438  |     777250  2786   2448  68201\n25:      51613  2452   2403  58930  |     776382  2848   2426  69075\n----------------------------------  | ------------------------------\nAvr:     77036  2666   3006  80151  |     759046  2838   2332  66154\nTot:            2752   2669  73152\n```\n输出相同格式的分析结果"
  }
]

Response:

# 7-Zip 基准测试结果分析根据提供的7-Zip基准测试结果，我将分析多线程性能扩展性，评估系统是否充分利用了多核性能。 ## 硬件配置 - CPU: Intel (C06F2) 虚拟环境 (KVMKVMKVM) - 硬件线程数: 32 - RAM: 约15GB (15,033 MB) ## 多线程性能扩展分析 ### 总评分(Tot Rating)随线程数的增长: | 线程数 | 总评分 | 线性理想值 | 实际效率 | |--------|--------|------------|----------| | 1 | 3,938 | 3,938 | 100% | | 2 | 8,403 | 7,876 | 106.7% | | 4 | 14,776 | 15,752 | 93.8% | | 8 | 25,509 | 31,504 | 81.0% | | 16 | 43,119 | 63,008 | 68.4% | | 32 | 73,152 | 126,016 | 58.1% | ### CPU使用率分析: 1. **单线程测试**: 100% CPU使用率，基准线 2. **2线程测试**: 202% CPU使用率 (理想为200%)，效率101.0% 3. **4线程测试**: 387% CPU使用率 (理想为400%)，效率96.8% 4. **8线程测试**: 739% CPU使用率 (理想为800%)，效率92.4% 5. **16线程测试**: 1419% CPU使用率 (理想为1600%)，效率88.7% 6. **32线程测试**: 2752% CPU使用率 (理想为3200%)，效率86.0% ### 压缩速度(KiB/s)扩展性: | 线程数 | 平均压缩速度 | 相对于单线程的倍数 | |--------|--------------|-------------------| | 1 | 4,017 | 1.0x | | 2 | 10,351 | 2.58x | | 4 | 17,240 | 4.29x | | 8 | 27,033 | 6.73x | | 16 | 43,946 | 10.94x | | 32 | 77,036 | 19.18x | ### 解压缩速度(KiB/s)扩展性: | 线程数 | 平均解压缩速度 | 相对于单线程的倍数 | |--------|----------------|-------------------| | 1 | 41,490 | 1.0x | | 2 | 68,469 | 1.65x | | 4 | 135,158 | 3.26x | | 8 | 267,086 | 6.44x | | 16 | 470,353 | 11.34x | | 32 | 759,046 | 18.29x | ## 结论 1. **良好的线性扩展性**: - 在32线程时，压缩性能达到单线程的19.18倍，达到理想32倍的约60% - 解压缩性能在32线程时达到单线程的18.29倍，达到理想值的约57% 2. **CPU利用率**: - 在低线程数(1-4)时，CPU利用率非常高(>95%) - 随着线程数增加，利用率逐渐下降，32线程时仍保持86.0%的高效率 3. **总体效率**: - 随着线程数增加，效率从单线程的100%降至32线程的58.1% - 2线程测试出现了超线性加速(106.7%)，可能是由于缓存效应或调度优化 4. **多核性能利用评估**: - 系统在所有线程数下都表现出良好的扩展性，说明多核性能被充分利用 - 32线程时仍能达到近20倍的性能提升，表明系统调度和资源分配较为高效 5. **性能特点**: - 压缩任务在高线程数下扩展性略好于解压缩任务 - 随着字典大小增加(Dict 22-25)，高线程数下的效率有所下降，特别是在压缩任务中 **建议**: - 对于压缩和解压缩任务，使用全部32线程是合理的，能获得最大总体性能 - 如果追求效率而非绝对性能，可以考虑使用16线程，效率更高 - 系统整体表现良好，多核性能得到了有效利用，尤其考虑到这是在虚拟环境(KVM)中运行该系统在多线程扩展性方面表现良好，充分利用了可用的多核资源。

Model: gpt-4o-mini-2024-07-182025-06-24 05:42:25

Context:

[
  {
    "role": "system",
    "content": "You are an assistant who is good at conversation. You need to summarize the user's conversation into a title of 10 characters or less. It should be in the format of \"Action - Title\". Some examples:\n1. Learn - Bitcoin 2. Code - Web Server 3. Write - An Article"
  },
  {
    "role": "user",
    "content": "[{\"role\":\"user\",\"mainText\":\"分析下列7b benchmark的结果 看看是否充分动用了多核性能：\\n\\n```\\n=== Running with 1 threads ===\\n\\n\\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\\n 64-bit locale=en_US.UTF-8 Threads:192 OPEN_MAX:1024\\n\\n mt1\\nCompiler: 13.2.0 GCC 13.2.0: SSE2\\nLinux : 6.13.0-rc2-tdxvfio : #1 SMP PREEMPT_DYNAMIC Sat Jan 25 06:35:55 UTC 2025 : x86_64\\nPageSize:4KB THP:madvise hwcap:6 hwcap2:2\\nINTEL(R) XEON(R) PLATINUM 8558 (C06F2)\\n\\n1T CPU Freq (MHz):  2088  2086  2084  2088  2083  2080  2077\\n\\nRAM size:  2063589 MB,  # CPU hardware threads: 192\\nRAM usage:    437 MB,  # Benchmark threads:      1\\n\\n                       Compressing  |                  Decompressing\\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\\n\\n22:       3817   100   3724   3714  |      27971   100   2384   2388\\n23:       3841   100   3931   3914  |      41032   100   3544   3552\\n24:       6752   100   7278   7260  |      52090   100   4577   4573\\n25:       5558   100   6343   6347  |      51706   100   4595   4602\\n----------------------------------  | ------------------------------\\nAvr:      4992   100   5319   5309  |      43200   100   3775   3779\\nTot:             100   4547   4544\\n\\n=== Running with 2 threads ===\\n\\n\\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\\n 64-bit locale=en_US.UTF-8 Threads:192 OPEN_MAX:1024\\n\\n mt2\\nCompiler: 13.2.0 GCC 13.2.0: SSE2\\nLinux : 6.13.0-rc2-tdxvfio : #1 SMP PREEMPT_DYNAMIC Sat Jan 25 06:35:55 UTC 2025 : x86_64\\nPageSize:4KB THP:madvise hwcap:6 hwcap2:2\\nINTEL(R) XEON(R) PLATINUM 8558 (C06F2)\\n\\n1T CPU Freq (MHz):  2090  2087  2090  2092  2090  2090  2090\\n2T CPU Freq (MHz): 199% 2080   199% 2084\\n\\nRAM size:  2063589 MB,  # CPU hardware threads: 192\\nRAM usage:    444 MB,  # Benchmark threads:      2\\n\\n                       Compressing  |                  Decompressing\\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\\n\\n22:       9629   201   4652   9368  |      82713   188   3763   7062\\n23:       9734   187   5290   9918  |      63014   185   2947   5454\\n24:       9831   191   5527  10571  |      55239   158   3078   4849\\n25:       9970   196   5794  11384  |      54778   153   3176   4876\\n----------------------------------  | ------------------------------\\nAvr:      9791   194   5316  10310  |      63936   171   3241   5560\\nTot:             183   4278   7935\\n\\n=== Running with 4 threads ===\\n\\n\\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\\n 64-bit locale=en_US.UTF-8 Threads:192 OPEN_MAX:1024\\n\\n mt4\\nCompiler: 13.2.0 GCC 13.2.0: SSE2\\nLinux : 6.13.0-rc2-tdxvfio : #1 SMP PREEMPT_DYNAMIC Sat Jan 25 06:35:55 UTC 2025 : x86_64\\nPageSize:4KB THP:madvise hwcap:6 hwcap2:2\\nINTEL(R) XEON(R) PLATINUM 8558 (C06F2)\\n\\n1T CPU Freq (MHz):  2082  2086  2085  2086  2090  2092  2090\\n4T CPU Freq (MHz): 399% 2085   398% 2078\\n\\nRAM size:  2063589 MB,  # CPU hardware threads: 192\\nRAM usage:    889 MB,  # Benchmark threads:      4\\n\\n                       Compressing  |                  Decompressing\\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\\n\\n22:      19588   349   5456  19056  |     111937   393   2428   9550\\n23:      19538   362   5498  19908  |     110701   385   2488   9579\\n24:      19514   384   5467  20982  |     110283   398   2431   9678\\n25:      16941   389   4972  19343  |     105827   398   2366   9419\\n----------------------------------  | ------------------------------\\nAvr:     18895   371   5348  19822  |     109687   394   2428   9556\\nTot:             382   3888  14689\\n\\n=== Running with 8 threads ===\\n\\n\\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\\n 64-bit locale=en_US.UTF-8 Threads:192 OPEN_MAX:1024\\n\\n mt8\\nCompiler: 13.2.0 GCC 13.2.0: SSE2\\nLinux : 6.13.0-rc2-tdxvfio : #1 SMP PREEMPT_DYNAMIC Sat Jan 25 06:35:55 UTC 2025 : x86_64\\nPageSize:4KB THP:madvise hwcap:6 hwcap2:2\\nINTEL(R) XEON(R) PLATINUM 8558 (C06F2)\\n\\n1T CPU Freq (MHz):  2060  2087  2088  2088  2084  2079  2080\\n8T CPU Freq (MHz): 796% 2074   798% 2083\\n\\nRAM size:  2063589 MB,  # CPU hardware threads: 192\\nRAM usage:   1779 MB,  # Benchmark threads:      8\\n\\n                       Compressing  |                  Decompressing\\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\\n\\n22:      37361   758   4794  36346  |     223172   797   2389  19030\\n23:      34559   778   4529  35212  |     218566   792   2388  18906\\n24:      33963   802   4555  36517  |     216762   794   2396  19019\\n25:      30123   785   4381  34393  |     211360   791   2378  18806\\n----------------------------------  | ------------------------------\\nAvr:     34001   781   4565  35617  |     217465   793   2387  18941\\nTot:             787   3476  27279\\n\\n=== Running with 16 threads ===\\n\\n\\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\\n 64-bit locale=en_US.UTF-8 Threads:192 OPEN_MAX:1024\\n\\n mt16\\nCompiler: 13.2.0 GCC 13.2.0: SSE2\\nLinux : 6.13.0-rc2-tdxvfio : #1 SMP PREEMPT_DYNAMIC Sat Jan 25 06:35:55 UTC 2025 : x86_64\\nPageSize:4KB THP:madvise hwcap:6 hwcap2:2\\nINTEL(R) XEON(R) PLATINUM 8558 (C06F2)\\n\\n1T CPU Freq (MHz):  2080  2080  2080  2080  2080  2080  2081\\n16T CPU Freq (MHz): 1573% 2044   1593% 2073\\n\\nRAM size:  2063589 MB,  # CPU hardware threads: 192\\nRAM usage:   3559 MB,  # Benchmark threads:     16\\n\\n                       Compressing  |                  Decompressing\\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\\n\\n22:      73737  1535   4672  71731  |     441686  1581   2383  37662\\n23:      68911  1549   4532  70213  |     440096  1591   2393  38071\\n24:      73625  1515   5224  79162  |     438819  1588   2425  38503\\n25:      71295  1551   5249  81403  |     427981  1560   2440  38078\\n----------------------------------  | ------------------------------\\nAvr:     71892  1538   4919  75627  |     437145  1580   2410  38079\\nTot:            1559   3665  56853\\n\\n=== Running with 32 threads ===\\n\\n\\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\\n 64-bit locale=en_US.UTF-8 Threads:192 OPEN_MAX:1024\\n\\n mt32\\nCompiler: 13.2.0 GCC 13.2.0: SSE2\\nLinux : 6.13.0-rc2-tdxvfio : #1 SMP PREEMPT_DYNAMIC Sat Jan 25 06:35:55 UTC 2025 : x86_64\\nPageSize:4KB THP:madvise hwcap:6 hwcap2:2\\nINTEL(R) XEON(R) PLATINUM 8558 (C06F2)\\n\\n1T CPU Freq (MHz):  2076  2090  2089  2090  2092  2091  2091\\n32T CPU Freq (MHz): 3171% 2068   3177% 2079\\n\\nRAM size:  2063589 MB,  # CPU hardware threads: 192\\nRAM usage:   7119 MB,  # Benchmark threads:     32\\n\\n                       Compressing  |                  Decompressing\\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\\n\\n22:     149480  2869   5068 145415  |     878111  3076   2434  74867\\n23:     106687  2507   4336 108701  |     753529  2601   2506  65191\\n24:     139532  2916   5145 150025  |     784756  2598   2650  68860\\n25:      88521  2469   4094 101070  |     772136  2261   3038  68697\\n----------------------------------  | ------------------------------\\nAvr:    121055  2690   4661 126303  |     797133  2634   2657  69404\\nTot:            2662   3659  97853\\n```\"},{\"role\":\"assistant\",\"mainText\":\"# 7-Zip 基准测试结果分析\\n\\n根据提供的7-Zip基准测试结果，我将分析多线程性能扩展性，评估系统是否充分利用了多核性能。\\n\\n## 硬件配置\\n\\n- CPU: Intel Xeon Platinum 8558\\n- 硬件线程数: 192\\n- RAM: 约2TB (2,063,589 MB)\\n\\n## 多线程性能扩展分析\\n\\n### 总评分(Tot Rating)随线程数的增长:\\n\\n| 线程数 | 总评分 | 线性理想值 | 实际效率 |\\n|--------|--------|------------|----------|\\n| 1      | 4,544  | 4,544      | 100%     |\\n| 2      | 7,935  | 9,088      | 87.3%    |\\n| 4      | 14,689 | 18,176     | 80.8%    |\\n| 8      | 27,279 | 36,352     | 75.0%    |\\n| 16     | 56,853 | 72,704     | 78.2%    |\\n| 32     | 97,853 | 145,408    | 67.3%    |\\n\\n### CPU使用率分析:\\n\\n1. **单线程测试**: 100% CPU使用率，基准线\\n2. **2线程测试**: 183% CPU使用率 (理想为200%)，效率91.5%\\n3. **4线程测试**: 382% CPU使用率 (理想为400%)，效率95.5%\\n4. **8线程测试**: 787% CPU使用率 (理想为800%)，效率98.4%\\n5. **16线程测试**: 1559% CPU使用率 (理想为1600%)，效率97.4%\\n6. **32线程测试**: 2662% CPU使用率 (理想为3200%)，效率83.2%\\n\\n### 压缩速度(KiB/s)扩展性:\\n\\n| 线程数 | 平均压缩速度 | 相对于单线程的倍数 |\\n|--------|--------------|-------------------|\\n| 1      | 4,992        | 1.0x              |\\n| 2      | 9,791        | 1.96x             |\\n| 4      | 18,895       | 3.78x             |\\n| 8      | 34,001       | 6.81x             |\\n| 16     | 71,892       | 14.40x            |\\n| 32     | 121,055      | 24.25x            |\\n\\n### 解压缩速度(KiB/s)扩展性:\\n\\n| 线程数 | 平均解压缩速度 | 相对于单线程的倍数 |\\n|--------|----------------|-------------------|\\n| 1      | 43,200         | 1.0x              |\\n| 2      | 63,936         | 1.48x             |\\n| 4      | 109,687        | 2.54x             |\\n| 8      | 217,465        | 5.03x             |\\n| 16     | 437,145        | 10.12x            |\\n| 32     | 797,133        | 18.45x            |\\n\\n## 结论\\n\\n1. **良好的线性扩展性**: \\n   - 在32线程时，压缩性能达到单线程的24.25倍，接近理想的32倍\\n   - 解压缩性能扩展性较差，32线程时仅达到单线程的18.45倍\\n\\n2. **CPU利用率**:\\n   - 在较低线程数(1-16)时，CPU利用率非常高(>95%)\\n   - 32线程时效率下降到83.2%，表明开始出现资源竞争或调度开销\\n\\n3. **总体效率**:\\n   - 随着线程数增加，效率逐渐下降，从单线程的100%降至32线程的67.3%\\n   - 这是多核系统中常见的现象，主要受内存带宽、缓存竞争等因素影响\\n\\n4. **多核性能利用评估**:\\n   - 系统在32线程时仍能保持较高的扩展性，说明多核性能被充分利用\\n   - 但未测试更高线程数(如64、128或全部192线程)，无法评估在更高并发下的表现\\n\\n**建议**:\\n- 对于压缩任务，增加线程数持续带来性能提升，可以使用更多线程\\n- 对于解压缩任务，线程数超过32后可能收益递减\\n- 考虑测试更高线程数(64-192)以确定最佳线程配置\\n- 系统整体表现良好，多核性能得到了有效利用\"}]"
  }
]

Response:

Analyze - Benchmark

Model: claude-3-7-sonnet-202502192025-06-24 05:42:19

Context:

[
  {
    "role": "user",
    "content": "分析下列7b benchmark的结果 看看是否充分动用了多核性能：\n\n```\n=== Running with 1 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=en_US.UTF-8 Threads:192 OPEN_MAX:1024\n\n mt1\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.13.0-rc2-tdxvfio : #1 SMP PREEMPT_DYNAMIC Sat Jan 25 06:35:55 UTC 2025 : x86_64\nPageSize:4KB THP:madvise hwcap:6 hwcap2:2\nINTEL(R) XEON(R) PLATINUM 8558 (C06F2)\n\n1T CPU Freq (MHz):  2088  2086  2084  2088  2083  2080  2077\n\nRAM size:  2063589 MB,  # CPU hardware threads: 192\nRAM usage:    437 MB,  # Benchmark threads:      1\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:       3817   100   3724   3714  |      27971   100   2384   2388\n23:       3841   100   3931   3914  |      41032   100   3544   3552\n24:       6752   100   7278   7260  |      52090   100   4577   4573\n25:       5558   100   6343   6347  |      51706   100   4595   4602\n----------------------------------  | ------------------------------\nAvr:      4992   100   5319   5309  |      43200   100   3775   3779\nTot:             100   4547   4544\n\n=== Running with 2 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=en_US.UTF-8 Threads:192 OPEN_MAX:1024\n\n mt2\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.13.0-rc2-tdxvfio : #1 SMP PREEMPT_DYNAMIC Sat Jan 25 06:35:55 UTC 2025 : x86_64\nPageSize:4KB THP:madvise hwcap:6 hwcap2:2\nINTEL(R) XEON(R) PLATINUM 8558 (C06F2)\n\n1T CPU Freq (MHz):  2090  2087  2090  2092  2090  2090  2090\n2T CPU Freq (MHz): 199% 2080   199% 2084\n\nRAM size:  2063589 MB,  # CPU hardware threads: 192\nRAM usage:    444 MB,  # Benchmark threads:      2\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:       9629   201   4652   9368  |      82713   188   3763   7062\n23:       9734   187   5290   9918  |      63014   185   2947   5454\n24:       9831   191   5527  10571  |      55239   158   3078   4849\n25:       9970   196   5794  11384  |      54778   153   3176   4876\n----------------------------------  | ------------------------------\nAvr:      9791   194   5316  10310  |      63936   171   3241   5560\nTot:             183   4278   7935\n\n=== Running with 4 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=en_US.UTF-8 Threads:192 OPEN_MAX:1024\n\n mt4\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.13.0-rc2-tdxvfio : #1 SMP PREEMPT_DYNAMIC Sat Jan 25 06:35:55 UTC 2025 : x86_64\nPageSize:4KB THP:madvise hwcap:6 hwcap2:2\nINTEL(R) XEON(R) PLATINUM 8558 (C06F2)\n\n1T CPU Freq (MHz):  2082  2086  2085  2086  2090  2092  2090\n4T CPU Freq (MHz): 399% 2085   398% 2078\n\nRAM size:  2063589 MB,  # CPU hardware threads: 192\nRAM usage:    889 MB,  # Benchmark threads:      4\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:      19588   349   5456  19056  |     111937   393   2428   9550\n23:      19538   362   5498  19908  |     110701   385   2488   9579\n24:      19514   384   5467  20982  |     110283   398   2431   9678\n25:      16941   389   4972  19343  |     105827   398   2366   9419\n----------------------------------  | ------------------------------\nAvr:     18895   371   5348  19822  |     109687   394   2428   9556\nTot:             382   3888  14689\n\n=== Running with 8 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=en_US.UTF-8 Threads:192 OPEN_MAX:1024\n\n mt8\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.13.0-rc2-tdxvfio : #1 SMP PREEMPT_DYNAMIC Sat Jan 25 06:35:55 UTC 2025 : x86_64\nPageSize:4KB THP:madvise hwcap:6 hwcap2:2\nINTEL(R) XEON(R) PLATINUM 8558 (C06F2)\n\n1T CPU Freq (MHz):  2060  2087  2088  2088  2084  2079  2080\n8T CPU Freq (MHz): 796% 2074   798% 2083\n\nRAM size:  2063589 MB,  # CPU hardware threads: 192\nRAM usage:   1779 MB,  # Benchmark threads:      8\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:      37361   758   4794  36346  |     223172   797   2389  19030\n23:      34559   778   4529  35212  |     218566   792   2388  18906\n24:      33963   802   4555  36517  |     216762   794   2396  19019\n25:      30123   785   4381  34393  |     211360   791   2378  18806\n----------------------------------  | ------------------------------\nAvr:     34001   781   4565  35617  |     217465   793   2387  18941\nTot:             787   3476  27279\n\n=== Running with 16 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=en_US.UTF-8 Threads:192 OPEN_MAX:1024\n\n mt16\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.13.0-rc2-tdxvfio : #1 SMP PREEMPT_DYNAMIC Sat Jan 25 06:35:55 UTC 2025 : x86_64\nPageSize:4KB THP:madvise hwcap:6 hwcap2:2\nINTEL(R) XEON(R) PLATINUM 8558 (C06F2)\n\n1T CPU Freq (MHz):  2080  2080  2080  2080  2080  2080  2081\n16T CPU Freq (MHz): 1573% 2044   1593% 2073\n\nRAM size:  2063589 MB,  # CPU hardware threads: 192\nRAM usage:   3559 MB,  # Benchmark threads:     16\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:      73737  1535   4672  71731  |     441686  1581   2383  37662\n23:      68911  1549   4532  70213  |     440096  1591   2393  38071\n24:      73625  1515   5224  79162  |     438819  1588   2425  38503\n25:      71295  1551   5249  81403  |     427981  1560   2440  38078\n----------------------------------  | ------------------------------\nAvr:     71892  1538   4919  75627  |     437145  1580   2410  38079\nTot:            1559   3665  56853\n\n=== Running with 32 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=en_US.UTF-8 Threads:192 OPEN_MAX:1024\n\n mt32\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.13.0-rc2-tdxvfio : #1 SMP PREEMPT_DYNAMIC Sat Jan 25 06:35:55 UTC 2025 : x86_64\nPageSize:4KB THP:madvise hwcap:6 hwcap2:2\nINTEL(R) XEON(R) PLATINUM 8558 (C06F2)\n\n1T CPU Freq (MHz):  2076  2090  2089  2090  2092  2091  2091\n32T CPU Freq (MHz): 3171% 2068   3177% 2079\n\nRAM size:  2063589 MB,  # CPU hardware threads: 192\nRAM usage:   7119 MB,  # Benchmark threads:     32\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:     149480  2869   5068 145415  |     878111  3076   2434  74867\n23:     106687  2507   4336 108701  |     753529  2601   2506  65191\n24:     139532  2916   5145 150025  |     784756  2598   2650  68860\n25:      88521  2469   4094 101070  |     772136  2261   3038  68697\n----------------------------------  | ------------------------------\nAvr:    121055  2690   4661 126303  |     797133  2634   2657  69404\nTot:            2662   3659  97853\n```"
  }
]

Response:

# 7-Zip 基准测试结果分析根据提供的7-Zip基准测试结果，我将分析多线程性能扩展性，评估系统是否充分利用了多核性能。 ## 硬件配置 - CPU: Intel Xeon Platinum 8558 - 硬件线程数: 192 - RAM: 约2TB (2,063,589 MB) ## 多线程性能扩展分析 ### 总评分(Tot Rating)随线程数的增长: | 线程数 | 总评分 | 线性理想值 | 实际效率 | |--------|--------|------------|----------| | 1 | 4,544 | 4,544 | 100% | | 2 | 7,935 | 9,088 | 87.3% | | 4 | 14,689 | 18,176 | 80.8% | | 8 | 27,279 | 36,352 | 75.0% | | 16 | 56,853 | 72,704 | 78.2% | | 32 | 97,853 | 145,408 | 67.3% | ### CPU使用率分析: 1. **单线程测试**: 100% CPU使用率，基准线 2. **2线程测试**: 183% CPU使用率 (理想为200%)，效率91.5% 3. **4线程测试**: 382% CPU使用率 (理想为400%)，效率95.5% 4. **8线程测试**: 787% CPU使用率 (理想为800%)，效率98.4% 5. **16线程测试**: 1559% CPU使用率 (理想为1600%)，效率97.4% 6. **32线程测试**: 2662% CPU使用率 (理想为3200%)，效率83.2% ### 压缩速度(KiB/s)扩展性: | 线程数 | 平均压缩速度 | 相对于单线程的倍数 | |--------|--------------|-------------------| | 1 | 4,992 | 1.0x | | 2 | 9,791 | 1.96x | | 4 | 18,895 | 3.78x | | 8 | 34,001 | 6.81x | | 16 | 71,892 | 14.40x | | 32 | 121,055 | 24.25x | ### 解压缩速度(KiB/s)扩展性: | 线程数 | 平均解压缩速度 | 相对于单线程的倍数 | |--------|----------------|-------------------| | 1 | 43,200 | 1.0x | | 2 | 63,936 | 1.48x | | 4 | 109,687 | 2.54x | | 8 | 217,465 | 5.03x | | 16 | 437,145 | 10.12x | | 32 | 797,133 | 18.45x | ## 结论 1. **良好的线性扩展性**: - 在32线程时，压缩性能达到单线程的24.25倍，接近理想的32倍 - 解压缩性能扩展性较差，32线程时仅达到单线程的18.45倍 2. **CPU利用率**: - 在较低线程数(1-16)时，CPU利用率非常高(>95%) - 32线程时效率下降到83.2%，表明开始出现资源竞争或调度开销 3. **总体效率**: - 随着线程数增加，效率逐渐下降，从单线程的100%降至32线程的67.3% - 这是多核系统中常见的现象，主要受内存带宽、缓存竞争等因素影响 4. **多核性能利用评估**: - 系统在32线程时仍能保持较高的扩展性，说明多核性能被充分利用 - 但未测试更高线程数(如64、128或全部192线程)，无法评估在更高并发下的表现 **建议**: - 对于压缩任务，增加线程数持续带来性能提升，可以使用更多线程 - 对于解压缩任务，线程数超过32后可能收益递减 - 考虑测试更高线程数(64-192)以确定最佳线程配置 - 系统整体表现良好，多核性能得到了有效利用

Model: claude-3-7-sonnet-202502192025-06-24 05:14:28

Context:

[
  {
    "role": "user",
    "content": "分析下列7b benchmark的结果 看看是否充分动用了多核性能：\n\n```\n=== Running with 1 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=C.UTF-8 Threads:16 OPEN_MAX:4096\n\n mt1\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.9.0-dstack : #1 SMP PREEMPT_DYNAMIC Thu May 30 14:26:20 UTC 2024 : x86_64 : KVMKVMKVM : [82][BA]\nPageSize:4KB hwcap:6 hwcap2:2\nGenuineIntel (C06F2) \n\n1T CPU Freq (MHz):   920   912  1119  1450  1461  1183   956\n\nRAM size:   15038 MB,  # CPU hardware threads:  16\nRAM usage:    437 MB,  # Benchmark threads:      1\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:       1481   100   1442   1441  |      26336   100   2249   2249\n23:       1631   100   1662   1662  |      19392   100   1680   1679\n24:       2095   100   2253   2253  |      12591   100   1105   1105\n25:       1869   100   2135   2134  |      17956   100   1599   1598\n----------------------------------  | ------------------------------\nAvr:      1769   100   1873   1873  |      19069   100   1658   1658\nTot:             100   1766   1765\n\n=== Running with 2 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=C.UTF-8 Threads:16 OPEN_MAX:4096\n\n mt2\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.9.0-dstack : #1 SMP PREEMPT_DYNAMIC Thu May 30 14:26:20 UTC 2024 : x86_64 : KVMKVMKVM : [82][BA]\nPageSize:4KB hwcap:6 hwcap2:2\nGenuineIntel (C06F2) \n\n1T CPU Freq (MHz):  1611  1638  1675  1618  1888  2868  3136\n2T CPU Freq (MHz): 163% 2033   185% 1808  \n\nRAM size:   15038 MB,  # CPU hardware threads:  16\nRAM usage:    444 MB,  # Benchmark threads:      2\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:       3972   167   2317   3864  |      30471   163   1601   2602\n23:       3125   196   1621   3185  |      27247   173   1363   2359\n24:       2935   157   2014   3156  |      30602   189   1419   2687\n25:       2440   166   1676   2786  |      34671   193   1603   3086\n----------------------------------  | ------------------------------\nAvr:      3118   172   1907   3248  |      30748   179   1496   2683\nTot:             175   1702   2965\n\n=== Running with 4 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=C.UTF-8 Threads:16 OPEN_MAX:4096\n\n mt4\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.9.0-dstack : #1 SMP PREEMPT_DYNAMIC Thu May 30 14:26:20 UTC 2024 : x86_64 : KVMKVMKVM : [82][BA]\nPageSize:4KB hwcap:6 hwcap2:2\nGenuineIntel (C06F2) \n\n1T CPU Freq (MHz):  2022  3386  3030  3252  3345  3081  1498\n4T CPU Freq (MHz): 277% 853   244% 703  \n\nRAM size:   15038 MB,  # CPU hardware threads:  16\nRAM usage:    889 MB,  # Benchmark threads:      4\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:       5744   284   1968   5588  |      50102   329   1298   4274\n23:       4952   313   1610   5046  |      59550   372   1385   5153\n24:       5272   275   2062   5669  |      43215   351   1079   3792\n25:       4162   305   1560   4753  |      52548   329   1421   4677\n----------------------------------  | ------------------------------\nAvr:      5033   294   1800   5264  |      51354   345   1296   4474\nTot:             320   1548   4869\n\n=== Running with 8 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=C.UTF-8 Threads:16 OPEN_MAX:4096\n\n mt8\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.9.0-dstack : #1 SMP PREEMPT_DYNAMIC Thu May 30 14:26:20 UTC 2024 : x86_64 : KVMKVMKVM : [82][BA]\nPageSize:4KB hwcap:6 hwcap2:2\nGenuineIntel (C06F2) \n\n1T CPU Freq (MHz):  1104  1087  1439  1100  1025  1482  1199\n8T CPU Freq (MHz): 649% 598   517% 747  \n\nRAM size:   15038 MB,  # CPU hardware threads:  16\nRAM usage:   1779 MB,  # Benchmark threads:      8\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:      10008   592   1646   9737  |      85502   615   1186   7291\n23:       8433   592   1450   8593  |      88012   619   1231   7613\n24:      10007   626   1719  10760  |      77257   552   1227   6779\n25:       5046   607    949   5762  |      86702   710   1087   7715\n----------------------------------  | ------------------------------\nAvr:      8374   604   1441   8713  |      84368   624   1183   7349\nTot:             614   1312   8031\n\n=== Running with 16 threads ===\n\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=C.UTF-8 Threads:16 OPEN_MAX:4096\n\n mt16\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.9.0-dstack : #1 SMP PREEMPT_DYNAMIC Thu May 30 14:26:20 UTC 2024 : x86_64 : KVMKVMKVM : [82][BA]\nPageSize:4KB hwcap:6 hwcap2:2\nGenuineIntel (C06F2) \n\n1T CPU Freq (MHz):  1173  1476  1433  1308  1265  1194  1063\n8T CPU Freq (MHz): 706% 701   690% 616  \n\nRAM size:   15038 MB,  # CPU hardware threads:  16\nRAM usage:   3559 MB,  # Benchmark threads:     16\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:      15179  1161   1272  14767  |     156672  1207   1107  13359\n23:      13845  1202   1174  14107  |     152933  1296   1021  13230\n24:      12587  1274   1062  13534  |     153447  1221   1102  13464\n25:       8567  1173    834   9782  |     127206  1015   1115  11318\n----------------------------------  | ------------------------------\nAvr:     12544  1202   1085  13047  |     147565  1185   1086  12843\nTot:            1194   1086  12945\n```"
  }
]

Response:

# 7-Zip Benchmark 多线程性能分析根据提供的7-Zip基准测试结果，我将分析该系统是否充分利用了多核性能。 ## 系统配置 - CPU: Intel处理器 (C06F2) - 硬件线程数: 16 - RAM: 15038 MB ## 多线程扩展性分析 ### 1. 总体性能扩展 | 线程数 | 压缩评分 | 解压评分 | 总评分 | 相对单线程倍数 | |--------|---------|---------|--------|--------------| | 1 | 1873 | 1658 | 1765 | 1.00x | | 2 | 3248 | 2683 | 2965 | 1.68x | | 4 | 5264 | 4474 | 4869 | 2.76x | | 8 | 8713 | 7349 | 8031 | 4.55x | | 16 | 13047 | 12843 | 12945 | 7.33x | ### 2. CPU利用率分析测试中报告了CPU使用率百分比： - 2线程: 175% 使用率 (理想值200%) - 4线程: 320% 使用率 (理想值400%) - 8线程: 614% 使用率 (理想值800%) - 16线程: 1194% 使用率 (理想值1600%) ### 3. CPU频率分析测试显示CPU频率随线程数增加而变化： - 单线程: 约920-1461 MHz - 多线程时频率提高: 2-4线程时达到2000-3300 MHz - 高线程数时频率降低: 8-16线程时回落到1000-1400 MHz范围 ## 结论 1. **线程扩展性不理想**：16线程性能仅为单线程的7.33倍，而不是理想的16倍。 2. **CPU利用率不足**：16线程测试中CPU利用率约为1194%，距离理想的1600%有较大差距。 3. **频率调节限制**：在高线程负载下，CPU频率明显降低，这表明系统存在热量或功耗限制。 4. **非线性扩展**：性能扩展呈现明显的非线性特征，随线程数增加，每增加一个线程带来的性能提升逐渐减小。 5. **虚拟化环境影响**：输出中的"KVMKVMKVM"表明这是在KVM虚拟化环境中运行，虚拟化可能限制了物理资源的完全访问。 **总体评估**：系统未能充分利用全部16个核心的性能，这可能受到以下因素影响： - 虚拟化环境的限制 - 热量/功耗限制导致的CPU频率降低 - 内存带宽瓶颈 - 7-Zip工作负载的固有并行化限制建议考虑调整虚拟机配置、检查散热状况或考虑使用更适合多线程的工作负载来充分发挥多核系统的性能。

Model: claude-3-7-sonnet-202502192025-06-24 05:03:33

Context:

[
  {
    "role": "user",
    "content": "分析下列7b benchmark的结果 看看是否充分动用了多核性能：\n\n```\n(base) jovyan@41bc247494ad:~$ 7z b -mmt1\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=C.UTF-8 Threads:8 OPEN_MAX:4096\n\n mt1\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.9.0-dstack : #1 SMP PREEMPT_DYNAMIC Thu May 30 14:26:20 UTC 2024 : x86_64 : KVMKVMKVM : [82][BA]\nPageSize:4KB hwcap:6 hwcap2:2\nGenuineIntel (C06F2) \n\n1T CPU Freq (MHz):  1541  2636  2974  3163  1899  2645  3184\n\nRAM size:   27112 MB,  # CPU hardware threads:   8\nRAM usage:    437 MB,  # Benchmark threads:      1\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:       2580   100   2508   2510  |      17412   100   1486   1487\n23:       1363   100   1388   1390  |      15126   100   1310   1309\n24:       1606   100   1729   1727  |      19789   100   1738   1737\n25:       1717   100   1962   1961  |      18788   100   1672   1672\n----------------------------------  | ------------------------------\nAvr:      1816   100   1897   1897  |      17779   100   1552   1551\nTot:             100   1724   1724\n(base) jovyan@41bc247494ad:~$ 7z b -mmt2\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=C.UTF-8 Threads:8 OPEN_MAX:4096\n\n mt2\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.9.0-dstack : #1 SMP PREEMPT_DYNAMIC Thu May 30 14:26:20 UTC 2024 : x86_64 : KVMKVMKVM : [82][BA]\nPageSize:4KB hwcap:6 hwcap2:2\nGenuineIntel (C06F2) \n\n1T CPU Freq (MHz):  1033  1748  1566  3387  3137  2304  1460\n2T CPU Freq (MHz): 174% 1800   200% 2245  \n\nRAM size:   27112 MB,  # CPU hardware threads:   8\nRAM usage:    444 MB,  # Benchmark threads:      2\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:       2792   155   1749   2716  |      37579   197   1625   3209\n23:       6177   193   3260   6294  |      35595   173   1776   3081\n24:       4549   186   2632   4891  |      40346   190   1861   3542\n25:       2585   165   1786   2952  |      26165   175   1330   2329\n----------------------------------  | ------------------------------\nAvr:      4026   175   2357   4214  |      34921   184   1648   3040\nTot:             179   2002   3627\n(base) jovyan@41bc247494ad:~$ 7z b -mmt4\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=C.UTF-8 Threads:8 OPEN_MAX:4096\n\n mt4\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.9.0-dstack : #1 SMP PREEMPT_DYNAMIC Thu May 30 14:26:20 UTC 2024 : x86_64 : KVMKVMKVM : [82][BA]\nPageSize:4KB hwcap:6 hwcap2:2\nGenuineIntel (C06F2) \n\n1T CPU Freq (MHz):  1209  1595  1718  1692  1360  2194  3135\n4T CPU Freq (MHz): 315% 1031   344% 831  \n\nRAM size:   27112 MB,  # CPU hardware threads:   8\nRAM usage:    889 MB,  # Benchmark threads:      4\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:       6120   313   1901   5954  |      51146   346   1261   4363\n23:       6138   339   1847   6254  |      54683   339   1394   4732\n24:       4608   321   1545   4955  |      52253   289   1589   4586\n25:       5236   319   1876   5978  |      50402   291   1543   4486\n----------------------------------  | ------------------------------\nAvr:      5525   323   1792   5785  |      52121   316   1447   4542\nTot:             320   1619   5164\n(base) jovyan@41bc247494ad:~$ 7z b -mmt8\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=C.UTF-8 Threads:8 OPEN_MAX:4096\n\n mt8\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.9.0-dstack : #1 SMP PREEMPT_DYNAMIC Thu May 30 14:26:20 UTC 2024 : x86_64 : KVMKVMKVM : [82][BA]\nPageSize:4KB hwcap:6 hwcap2:2\nGenuineIntel (C06F2) \n\n1T CPU Freq (MHz):  1101   874  1015  1129  1307   947   968\n4T CPU Freq (MHz): 308% 807   374% 768  \n\nRAM size:   27112 MB,  # CPU hardware threads:   8\nRAM usage:   1779 MB,  # Benchmark threads:      8\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:       9653   617   1522   9391  |      86140   681   1079   7345\n23:       9788   656   1520   9974  |      84189   609   1196   7283\n24:       8694   654   1430   9349  |      69442   480   1269   6093\n25:       6717   618   1242   7670  |      86076   708   1082   7659\n----------------------------------  | ------------------------------\nAvr:      8713   636   1428   9096  |      81461   619   1156   7095\nTot:             628   1292   8095\n```"
  },
  {
    "role": "assistant",
    "content": "# 分析7-Zip多线程基准测试结果\n\n根据提供的7-Zip基准测试结果，我将分析不同线程数(1、2、4、8)下的性能表现，评估多核性能利用情况。\n\n## 硬件环境\n- CPU: Intel处理器(C06F2)\n- 硬件线程数: 8\n- RAM: 27112 MB\n\n## 性能数据分析\n\n### 总体评分(Tot Rating)对比\n- 单线程(-mmt1): 1724 MIPS\n- 双线程(-mmt2): 3627 MIPS (提升210%)\n- 四线程(-mmt4): 5164 MIPS (提升300%)\n- 八线程(-mmt8): 8095 MIPS (提升469%)\n\n### CPU利用率(Usage)对比\n- 单线程: 100%\n- 双线程: 179% (理想值200%)\n- 四线程: 320% (理想值400%)\n- 八线程: 628% (理想值800%)\n\n### 线程扩展性分析\n\n1. **双线程vs单线程**:\n   - 性能提升了2.1倍，略高于理想的2倍\n   - CPU频率显示\"174% 1800 200% 2245\"，表明双线程负载下CPU频率较高\n\n2. **四线程vs单线程**:\n   - 性能提升了3倍，低于理想的4倍\n   - CPU频率显示\"315% 1031 344% 831\"，频率开始下降\n\n3. **八线程vs单线程**:\n   - 性能提升了4.69倍，远低于理想的8倍\n   - CPU频率进一步下降到\"308% 807 374% 768\"\n\n## 结论\n\n1. **多核利用率分析**:\n   - 系统能够利用多核，但随着线程数增加，每增加一个线程带来的边际性能提升在下降\n   - 8线程时只达到了理想性能的59%(4.69/8)，CPU利用率仅为78.5%(628%/800%)\n\n2. **性能瓶颈**:\n   - CPU频率随线程数增加而降低，表明存在热限制或功耗限制\n   - 8线程时的频率明显低于单线程，这限制了线性扩展性\n\n3. **建议**:\n   - 对于这个特定硬件，使用4-6线程可能是最佳平衡点\n   - 7-Zip的压缩/解压缩工作负载在8线程时未能充分利用所有核心性能\n   - 可能存在内存带宽或缓存争用问题，限制了多线程性能扩展\n\n总体而言，系统确实能够利用多核性能，但8线程配置下未能达到理想的线性扩展，性能扩展效率约为59%。"
  },
  {
    "role": "user",
    "content": "我想依次跑 7z b -mmt1/2/4/8/16 怎么一条指令搞定"
  }
]

Response:

要依次运行 7z b 命令并使用不同的线程数（1、2、4、8、16），你可以使用一条命令行来完成，有几种方式： ## 使用 for 循环 ```bash for threads in 1 2 4 8 16; do echo -e "\n=== Running with $threads threads ===\n"; 7z b -mmt$threads; done ``` ## 使用分号连接多个命令 ```bash echo "=== 1 thread ==="; 7z b -mmt1; echo -e "\n=== 2 threads ==="; 7z b -mmt2; echo -e "\n=== 4 threads ==="; 7z b -mmt4; echo -e "\n=== 8 threads ==="; 7z b -mmt8; echo -e "\n=== 16 threads ==="; 7z b -mmt16 ``` ## 使用 && 运算符（前一个命令成功后才执行下一个） ```bash echo "=== 1 thread ===" && 7z b -mmt1 && echo -e "\n=== 2 threads ===" && 7z b -mmt2 && echo -e "\n=== 4 threads ===" && 7z b -mmt4 && echo -e "\n=== 8 threads ===" && 7z b -mmt8 && echo -e "\n=== 16 threads ===" && 7z b -mmt16 ``` 推荐使用第一种方法（for循环），因为它最简洁且易于修改。如果你想将结果保存到文件中，可以添加重定向： ```bash for threads in 1 2 4 8 16; do echo -e "\n=== Running with $threads threads ===\n"; 7z b -mmt$threads; done > 7z_benchmark_results.txt ``` 这样所有测试结果将被保存到 7z_benchmark_results.txt 文件中。

Model: gpt-4o-mini-2024-07-182025-06-24 04:47:32

Context:

[
  {
    "role": "system",
    "content": "You are an assistant who is good at conversation. You need to summarize the user's conversation into a title of 10 characters or less. It should be in the format of \"Action - Title\". Some examples:\n1. Learn - Bitcoin 2. Code - Web Server 3. Write - An Article"
  },
  {
    "role": "user",
    "content": "[{\"role\":\"user\",\"mainText\":\"分析下列7b benchmark的结果 看看是否充分动用了多核性能：\\n\\n```\\n(base) jovyan@41bc247494ad:~$ 7z b -mmt1\\n\\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\\n 64-bit locale=C.UTF-8 Threads:8 OPEN_MAX:4096\\n\\n mt1\\nCompiler: 13.2.0 GCC 13.2.0: SSE2\\nLinux : 6.9.0-dstack : #1 SMP PREEMPT_DYNAMIC Thu May 30 14:26:20 UTC 2024 : x86_64 : KVMKVMKVM : [82][BA]\\nPageSize:4KB hwcap:6 hwcap2:2\\nGenuineIntel (C06F2) \\n\\n1T CPU Freq (MHz):  1541  2636  2974  3163  1899  2645  3184\\n\\nRAM size:   27112 MB,  # CPU hardware threads:   8\\nRAM usage:    437 MB,  # Benchmark threads:      1\\n\\n                       Compressing  |                  Decompressing\\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\\n\\n22:       2580   100   2508   2510  |      17412   100   1486   1487\\n23:       1363   100   1388   1390  |      15126   100   1310   1309\\n24:       1606   100   1729   1727  |      19789   100   1738   1737\\n25:       1717   100   1962   1961  |      18788   100   1672   1672\\n----------------------------------  | ------------------------------\\nAvr:      1816   100   1897   1897  |      17779   100   1552   1551\\nTot:             100   1724   1724\\n(base) jovyan@41bc247494ad:~$ 7z b -mmt2\\n\\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\\n 64-bit locale=C.UTF-8 Threads:8 OPEN_MAX:4096\\n\\n mt2\\nCompiler: 13.2.0 GCC 13.2.0: SSE2\\nLinux : 6.9.0-dstack : #1 SMP PREEMPT_DYNAMIC Thu May 30 14:26:20 UTC 2024 : x86_64 : KVMKVMKVM : [82][BA]\\nPageSize:4KB hwcap:6 hwcap2:2\\nGenuineIntel (C06F2) \\n\\n1T CPU Freq (MHz):  1033  1748  1566  3387  3137  2304  1460\\n2T CPU Freq (MHz): 174% 1800   200% 2245  \\n\\nRAM size:   27112 MB,  # CPU hardware threads:   8\\nRAM usage:    444 MB,  # Benchmark threads:      2\\n\\n                       Compressing  |                  Decompressing\\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\\n\\n22:       2792   155   1749   2716  |      37579   197   1625   3209\\n23:       6177   193   3260   6294  |      35595   173   1776   3081\\n24:       4549   186   2632   4891  |      40346   190   1861   3542\\n25:       2585   165   1786   2952  |      26165   175   1330   2329\\n----------------------------------  | ------------------------------\\nAvr:      4026   175   2357   4214  |      34921   184   1648   3040\\nTot:             179   2002   3627\\n(base) jovyan@41bc247494ad:~$ 7z b -mmt4\\n\\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\\n 64-bit locale=C.UTF-8 Threads:8 OPEN_MAX:4096\\n\\n mt4\\nCompiler: 13.2.0 GCC 13.2.0: SSE2\\nLinux : 6.9.0-dstack : #1 SMP PREEMPT_DYNAMIC Thu May 30 14:26:20 UTC 2024 : x86_64 : KVMKVMKVM : [82][BA]\\nPageSize:4KB hwcap:6 hwcap2:2\\nGenuineIntel (C06F2) \\n\\n1T CPU Freq (MHz):  1209  1595  1718  1692  1360  2194  3135\\n4T CPU Freq (MHz): 315% 1031   344% 831  \\n\\nRAM size:   27112 MB,  # CPU hardware threads:   8\\nRAM usage:    889 MB,  # Benchmark threads:      4\\n\\n                       Compressing  |                  Decompressing\\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\\n\\n22:       6120   313   1901   5954  |      51146   346   1261   4363\\n23:       6138   339   1847   6254  |      54683   339   1394   4732\\n24:       4608   321   1545   4955  |      52253   289   1589   4586\\n25:       5236   319   1876   5978  |      50402   291   1543   4486\\n----------------------------------  | ------------------------------\\nAvr:      5525   323   1792   5785  |      52121   316   1447   4542\\nTot:             320   1619   5164\\n(base) jovyan@41bc247494ad:~$ 7z b -mmt8\\n\\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\\n 64-bit locale=C.UTF-8 Threads:8 OPEN_MAX:4096\\n\\n mt8\\nCompiler: 13.2.0 GCC 13.2.0: SSE2\\nLinux : 6.9.0-dstack : #1 SMP PREEMPT_DYNAMIC Thu May 30 14:26:20 UTC 2024 : x86_64 : KVMKVMKVM : [82][BA]\\nPageSize:4KB hwcap:6 hwcap2:2\\nGenuineIntel (C06F2) \\n\\n1T CPU Freq (MHz):  1101   874  1015  1129  1307   947   968\\n4T CPU Freq (MHz): 308% 807   374% 768  \\n\\nRAM size:   27112 MB,  # CPU hardware threads:   8\\nRAM usage:   1779 MB,  # Benchmark threads:      8\\n\\n                       Compressing  |                  Decompressing\\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\\n\\n22:       9653   617   1522   9391  |      86140   681   1079   7345\\n23:       9788   656   1520   9974  |      84189   609   1196   7283\\n24:       8694   654   1430   9349  |      69442   480   1269   6093\\n25:       6717   618   1242   7670  |      86076   708   1082   7659\\n----------------------------------  | ------------------------------\\nAvr:      8713   636   1428   9096  |      81461   619   1156   7095\\nTot:             628   1292   8095\\n```\"},{\"role\":\"assistant\",\"mainText\":\"# 分析7-Zip多线程基准测试结果\\n\\n根据提供的7-Zip基准测试结果，我将分析不同线程数(1、2、4、8)下的性能表现，评估多核性能利用情况。\\n\\n## 硬件环境\\n- CPU: Intel处理器(C06F2)\\n- 硬件线程数: 8\\n- RAM: 27112 MB\\n\\n## 性能数据分析\\n\\n### 总体评分(Tot Rating)对比\\n- 单线程(-mmt1): 1724 MIPS\\n- 双线程(-mmt2): 3627 MIPS (提升210%)\\n- 四线程(-mmt4): 5164 MIPS (提升300%)\\n- 八线程(-mmt8): 8095 MIPS (提升469%)\\n\\n### CPU利用率(Usage)对比\\n- 单线程: 100%\\n- 双线程: 179% (理想值200%)\\n- 四线程: 320% (理想值400%)\\n- 八线程: 628% (理想值800%)\\n\\n### 线程扩展性分析\\n\\n1. **双线程vs单线程**:\\n   - 性能提升了2.1倍，略高于理想的2倍\\n   - CPU频率显示\\\"174% 1800 200% 2245\\\"，表明双线程负载下CPU频率较高\\n\\n2. **四线程vs单线程**:\\n   - 性能提升了3倍，低于理想的4倍\\n   - CPU频率显示\\\"315% 1031 344% 831\\\"，频率开始下降\\n\\n3. **八线程vs单线程**:\\n   - 性能提升了4.69倍，远低于理想的8倍\\n   - CPU频率进一步下降到\\\"308% 807 374% 768\\\"\\n\\n## 结论\\n\\n1. **多核利用率分析**:\\n   - 系统能够利用多核，但随着线程数增加，每增加一个线程带来的边际性能提升在下降\\n   - 8线程时只达到了理想性能的59%(4.69/8)，CPU利用率仅为78.5%(628%/800%)\\n\\n2. **性能瓶颈**:\\n   - CPU频率随线程数增加而降低，表明存在热限制或功耗限制\\n   - 8线程时的频率明显低于单线程，这限制了线性扩展性\\n\\n3. **建议**:\\n   - 对于这个特定硬件，使用4-6线程可能是最佳平衡点\\n   - 7-Zip的压缩/解压缩工作负载在8线程时未能充分利用所有核心性能\\n   - 可能存在内存带宽或缓存争用问题，限制了多线程性能扩展\\n\\n总体而言，系统确实能够利用多核性能，但8线程配置下未能达到理想的线性扩展，性能扩展效率约为59%。\"}]"
  }
]

Response:

Analyze - 7z MTS

Model: claude-3-7-sonnet-202502192025-06-24 04:47:31

Context:

[
  {
    "role": "user",
    "content": "分析下列7b benchmark的结果 看看是否充分动用了多核性能：\n\n```\n(base) jovyan@41bc247494ad:~$ 7z b -mmt1\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=C.UTF-8 Threads:8 OPEN_MAX:4096\n\n mt1\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.9.0-dstack : #1 SMP PREEMPT_DYNAMIC Thu May 30 14:26:20 UTC 2024 : x86_64 : KVMKVMKVM : [82][BA]\nPageSize:4KB hwcap:6 hwcap2:2\nGenuineIntel (C06F2) \n\n1T CPU Freq (MHz):  1541  2636  2974  3163  1899  2645  3184\n\nRAM size:   27112 MB,  # CPU hardware threads:   8\nRAM usage:    437 MB,  # Benchmark threads:      1\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:       2580   100   2508   2510  |      17412   100   1486   1487\n23:       1363   100   1388   1390  |      15126   100   1310   1309\n24:       1606   100   1729   1727  |      19789   100   1738   1737\n25:       1717   100   1962   1961  |      18788   100   1672   1672\n----------------------------------  | ------------------------------\nAvr:      1816   100   1897   1897  |      17779   100   1552   1551\nTot:             100   1724   1724\n(base) jovyan@41bc247494ad:~$ 7z b -mmt2\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=C.UTF-8 Threads:8 OPEN_MAX:4096\n\n mt2\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.9.0-dstack : #1 SMP PREEMPT_DYNAMIC Thu May 30 14:26:20 UTC 2024 : x86_64 : KVMKVMKVM : [82][BA]\nPageSize:4KB hwcap:6 hwcap2:2\nGenuineIntel (C06F2) \n\n1T CPU Freq (MHz):  1033  1748  1566  3387  3137  2304  1460\n2T CPU Freq (MHz): 174% 1800   200% 2245  \n\nRAM size:   27112 MB,  # CPU hardware threads:   8\nRAM usage:    444 MB,  # Benchmark threads:      2\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:       2792   155   1749   2716  |      37579   197   1625   3209\n23:       6177   193   3260   6294  |      35595   173   1776   3081\n24:       4549   186   2632   4891  |      40346   190   1861   3542\n25:       2585   165   1786   2952  |      26165   175   1330   2329\n----------------------------------  | ------------------------------\nAvr:      4026   175   2357   4214  |      34921   184   1648   3040\nTot:             179   2002   3627\n(base) jovyan@41bc247494ad:~$ 7z b -mmt4\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=C.UTF-8 Threads:8 OPEN_MAX:4096\n\n mt4\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.9.0-dstack : #1 SMP PREEMPT_DYNAMIC Thu May 30 14:26:20 UTC 2024 : x86_64 : KVMKVMKVM : [82][BA]\nPageSize:4KB hwcap:6 hwcap2:2\nGenuineIntel (C06F2) \n\n1T CPU Freq (MHz):  1209  1595  1718  1692  1360  2194  3135\n4T CPU Freq (MHz): 315% 1031   344% 831  \n\nRAM size:   27112 MB,  # CPU hardware threads:   8\nRAM usage:    889 MB,  # Benchmark threads:      4\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:       6120   313   1901   5954  |      51146   346   1261   4363\n23:       6138   339   1847   6254  |      54683   339   1394   4732\n24:       4608   321   1545   4955  |      52253   289   1589   4586\n25:       5236   319   1876   5978  |      50402   291   1543   4486\n----------------------------------  | ------------------------------\nAvr:      5525   323   1792   5785  |      52121   316   1447   4542\nTot:             320   1619   5164\n(base) jovyan@41bc247494ad:~$ 7z b -mmt8\n\n7-Zip 23.01 (x64) : Copyright (c) 1999-2023 Igor Pavlov : 2023-06-20\n 64-bit locale=C.UTF-8 Threads:8 OPEN_MAX:4096\n\n mt8\nCompiler: 13.2.0 GCC 13.2.0: SSE2\nLinux : 6.9.0-dstack : #1 SMP PREEMPT_DYNAMIC Thu May 30 14:26:20 UTC 2024 : x86_64 : KVMKVMKVM : [82][BA]\nPageSize:4KB hwcap:6 hwcap2:2\nGenuineIntel (C06F2) \n\n1T CPU Freq (MHz):  1101   874  1015  1129  1307   947   968\n4T CPU Freq (MHz): 308% 807   374% 768  \n\nRAM size:   27112 MB,  # CPU hardware threads:   8\nRAM usage:   1779 MB,  # Benchmark threads:      8\n\n                       Compressing  |                  Decompressing\nDict     Speed Usage    R/U Rating  |      Speed Usage    R/U Rating\n         KiB/s     %   MIPS   MIPS  |      KiB/s     %   MIPS   MIPS\n\n22:       9653   617   1522   9391  |      86140   681   1079   7345\n23:       9788   656   1520   9974  |      84189   609   1196   7283\n24:       8694   654   1430   9349  |      69442   480   1269   6093\n25:       6717   618   1242   7670  |      86076   708   1082   7659\n----------------------------------  | ------------------------------\nAvr:      8713   636   1428   9096  |      81461   619   1156   7095\nTot:             628   1292   8095\n```"
  }
]

Response:

# 分析7-Zip多线程基准测试结果根据提供的7-Zip基准测试结果，我将分析不同线程数(1、2、4、8)下的性能表现，评估多核性能利用情况。 ## 硬件环境 - CPU: Intel处理器(C06F2) - 硬件线程数: 8 - RAM: 27112 MB ## 性能数据分析 ### 总体评分(Tot Rating)对比 - 单线程(-mmt1): 1724 MIPS - 双线程(-mmt2): 3627 MIPS (提升210%) - 四线程(-mmt4): 5164 MIPS (提升300%) - 八线程(-mmt8): 8095 MIPS (提升469%) ### CPU利用率(Usage)对比 - 单线程: 100% - 双线程: 179% (理想值200%) - 四线程: 320% (理想值400%) - 八线程: 628% (理想值800%) ### 线程扩展性分析 1. **双线程vs单线程**: - 性能提升了2.1倍，略高于理想的2倍 - CPU频率显示"174% 1800 200% 2245"，表明双线程负载下CPU频率较高 2. **四线程vs单线程**: - 性能提升了3倍，低于理想的4倍 - CPU频率显示"315% 1031 344% 831"，频率开始下降 3. **八线程vs单线程**: - 性能提升了4.69倍，远低于理想的8倍 - CPU频率进一步下降到"308% 807 374% 768" ## 结论 1. **多核利用率分析**: - 系统能够利用多核，但随着线程数增加，每增加一个线程带来的边际性能提升在下降 - 8线程时只达到了理想性能的59%(4.69/8)，CPU利用率仅为78.5%(628%/800%) 2. **性能瓶颈**: - CPU频率随线程数增加而降低，表明存在热限制或功耗限制 - 8线程时的频率明显低于单线程，这限制了线性扩展性 3. **建议**: - 对于这个特定硬件，使用4-6线程可能是最佳平衡点 - 7-Zip的压缩/解压缩工作负载在8线程时未能充分利用所有核心性能 - 可能存在内存带宽或缓存争用问题，限制了多线程性能扩展总体而言，系统确实能够利用多核性能，但8线程配置下未能达到理想的线性扩展，性能扩展效率约为59%。

Model: claude-3-7-sonnet-202502192025-06-24 04:38:12

Context:

[
  {
    "role": "user",
    "content": "怎么跑7z CPU性能测试"
  },
  {
    "role": "assistant",
    "content": "# 如何运行7-Zip的CPU性能测试\n\n7-Zip内置了一个基准测试工具，可以用来测试CPU的性能。以下是运行7-Zip CPU性能测试的步骤：\n\n## 方法一：通过7-Zip文件管理器界面\n\n1. 打开7-Zip文件管理器（通常在开始菜单中可以找到）\n2. 点击顶部菜单栏的\"工具\"选项\n3. 选择\"基准测试\"选项\n4. 在弹出的基准测试窗口中，点击\"开始\"按钮开始测试\n5. 等待测试完成，结果会显示在窗口中\n\n## 方法二：通过命令行运行\n\n1. 打开命令提示符（CMD）\n2. 导航到7-Zip的安装目录（通常是`C:\\Program Files\\7-Zip`）\n3. 输入以下命令：\n   ```\n   7z b\n   ```\n4. 按回车键运行命令，测试将自动开始\n\n## 理解测试结果\n\n测试完成后，7-Zip会显示以下主要指标：\n- **压缩速度**：以KB/s为单位\n- **解压缩速度**：以KB/s为单位\n- **MIPS评分**：每秒百万指令数，这是一个综合性能指标\n- **总评分**：综合压缩和解压缩性能的总分\n\n分数越高表示CPU性能越好。您可以将自己的测试结果与网上其他用户的结果进行比较，以评估您的CPU性能水平。\n\n## 注意事项\n\n- 测试过程中，CPU会被满负荷使用，可能导致系统暂时变慢\n- 建议在运行测试前关闭其他占用CPU资源的程序\n- 对于多核CPU，7-Zip会自动使用所有可用的核心进行测试\n\n希望这些信息对您有所帮助！"
  },
  {
    "role": "user",
    "content": "怎么设置线程数"
  }
]

Response:

# 如何在7-Zip CPU性能测试中设置线程数在7-Zip的CPU性能测试中，您可以自定义线程数来更精确地测试CPU性能或模拟特定使用场景。以下是设置线程数的方法： ## 方法一：通过7-Zip文件管理器界面设置线程数 1. 打开7-Zip文件管理器 2. 点击顶部菜单栏的"工具"选项 3. 选择"基准测试"选项 4. 在弹出的基准测试窗口中，您会看到"字典大小"和"线程数"的设置选项 5. 在"线程数"下拉菜单中，您可以选择： - **1** - 单线程测试 - **2** - 双线程测试 - **4** - 四线程测试 - 等等，直到您的CPU支持的最大线程数 - **\*** - 自动使用所有可用线程（默认设置） 6. 选择所需的线程数后，点击"开始"按钮开始测试 ## 方法二：通过命令行设置线程数 1. 打开命令提示符（CMD） 2. 导航到7-Zip的安装目录 3. 使用以下命令格式设置线程数： ``` 7z b -mmt[N] ``` 其中[N]是您想要使用的线程数。例如： - `7z b -mmt1` - 使用1个线程进行测试 - `7z b -mmt4` - 使用4个线程进行测试 - `7z b -mmt` - 使用所有可用线程（默认设置） ## 线程数设置建议 - **测试单核性能**：设置线程数为1 - **测试多核性能**：设置线程数为CPU的物理核心数 - **测试超线程性能**：设置线程数为CPU的逻辑处理器数（物理核心数×2，如果CPU支持超线程） - **比较不同配置**：可以尝试不同的线程数设置，比较性能差异 ## 注意事项 - 设置过高的线程数（超过CPU实际支持的线程数）不会提高性能，反而可能因为线程切换开销而降低性能 - 对于特定的CPU，某些线程数可能会产生最佳性能，这取决于CPU的架构和缓存设计 - 在进行比较测试时，确保使用相同的线程数设置，以获得公平的比较结果通过调整线程数，您可以更全面地了解CPU在不同负载条件下的性能表现。

Model: gpt-4o-mini-2024-07-182025-06-24 04:37:09

Context:

[
  {
    "role": "system",
    "content": "You are an assistant who is good at conversation. You need to summarize the user's conversation into a title of 10 characters or less. It should be in the format of \"Action - Title\". Some examples:\n1. Learn - Bitcoin 2. Code - Web Server 3. Write - An Article"
  },
  {
    "role": "user",
    "content": "[{\"role\":\"user\",\"mainText\":\"怎么跑7z CPU性能测试\"},{\"role\":\"assistant\",\"mainText\":\"# 如何运行7-Zip的CPU性能测试\\n\\n7-Zip内置了一个基准测试工具，可以用来测试CPU的性能。以下是运行7-Zip CPU性能测试的步骤：\\n\\n## 方法一：通过7-Zip文件管理器界面\\n\\n1. 打开7-Zip文件管理器（通常在开始菜单中可以找到）\\n2. 点击顶部菜单栏的\\\"工具\\\"选项\\n3. 选择\\\"基准测试\\\"选项\\n4. 在弹出的基准测试窗口中，点击\\\"开始\\\"按钮开始测试\\n5. 等待测试完成，结果会显示在窗口中\\n\\n## 方法二：通过命令行运行\\n\\n1. 打开命令提示符（CMD）\\n2. 导航到7-Zip的安装目录（通常是`C:\\\\Program Files\\\\7-Zip`）\\n3. 输入以下命令：\\n   ```\\n   7z b\\n   ```\\n4. 按回车键运行命令，测试将自动开始\\n\\n## 理解测试结果\\n\\n测试完成后，7-Zip会显示以下主要指标：\\n- **压缩速度**：以KB/s为单位\\n- **解压缩速度**：以KB/s为单位\\n- **MIPS评分**：每秒百万指令数，这是一个综合性能指标\\n- **总评分**：综合压缩和解压缩性能的总分\\n\\n分数越高表示CPU性能越好。您可以将自己的测试结果与网上其他用户的结果进行比较，以评估您的CPU性能水平。\\n\\n## 注意事项\\n\\n- 测试过程中，CPU会被满负荷使用，可能导致系统暂时变慢\\n- 建议在运行测试前关闭其他占用CPU资源的程序\\n- 对于多核CPU，7-Zip会自动使用所有可用的核心进行测试\\n\\n希望这些信息对您有所帮助！\"}]"
  }
]

Response:

Test - 7z CPU

Model: claude-3-7-sonnet-202502192025-06-24 04:37:08

Context:

[
  {
    "role": "user",
    "content": "怎么跑7z CPU性能测试"
  }
]

Response:

# 如何运行7-Zip的CPU性能测试 7-Zip内置了一个基准测试工具，可以用来测试CPU的性能。以下是运行7-Zip CPU性能测试的步骤： ## 方法一：通过7-Zip文件管理器界面 1. 打开7-Zip文件管理器（通常在开始菜单中可以找到） 2. 点击顶部菜单栏的"工具"选项 3. 选择"基准测试"选项 4. 在弹出的基准测试窗口中，点击"开始"按钮开始测试 5. 等待测试完成，结果会显示在窗口中 ## 方法二：通过命令行运行 1. 打开命令提示符（CMD） 2. 导航到7-Zip的安装目录（通常是`C:\Program Files\7-Zip`） 3. 输入以下命令： ``` 7z b ``` 4. 按回车键运行命令，测试将自动开始 ## 理解测试结果测试完成后，7-Zip会显示以下主要指标： - **压缩速度**：以KB/s为单位 - **解压缩速度**：以KB/s为单位 - **MIPS评分**：每秒百万指令数，这是一个综合性能指标 - **总评分**：综合压缩和解压缩性能的总分分数越高表示CPU性能越好。您可以将自己的测试结果与网上其他用户的结果进行比较，以评估您的CPU性能水平。 ## 注意事项 - 测试过程中，CPU会被满负荷使用，可能导致系统暂时变慢 - 建议在运行测试前关闭其他占用CPU资源的程序 - 对于多核CPU，7-Zip会自动使用所有可用的核心进行测试希望这些信息对您有所帮助！