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  3. OpenAnolis孵化机密计算和机密容器的创新项目 - 基于CPU TEE的SPDM通信协议
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OpenAnolis孵化机密计算和机密容器的创新项目 - 基于CPU TEE的SPDM通信协议

A advanced general ml competition requiring roughly 24–80 hours for an end-to-end practice run.

Difficulty
Advanced
Estimated effort
24–80 hours
Registration deadline
To be confirmed
Compute
CPU only
OverviewPreparationSource

Overview

Who this competition fits

适合已有机密计算与远程证明背景、能阅读并实现 SPDM 规范的系统/安全开发者。参赛者尤其需要熟悉 Intel SGX SDK 的分区编程模型和 SGX DCAP;有 AMD SEV 或 Intel TDX 经验更合适。

Read the original official blurb
龙蜥社区(OpenAnolis)是一个面向国际的操作系统开源社区及创新平台。社区已成立50+个SIG工作组,本次赛题来自原生机密计算SIG,要求参与者能够理解当前机密计算技术,并结合当前机密计算领域最新的前沿技Device TEE,基SPDM规范定义的消息协议实现CPU TEE绑定协议和代码,编写SPDM for CPU TEE的绑定协议规范草案,未来提交到开源社区和标准组织,最终进行产品落地。 Official category: 实战竞技赛. Organizers: 龙蜥社区(OpenAnolis). Participants: 0.

Preparation

From registration to a first submission

  1. 01

    Rust 全栈开发

  2. 02

    机密计算与远程证明

  3. 03

    Intel SGX SDK 分区编程

  4. 04

    Intel SGX DCAP

  5. 05

    DMTF SPDM 规范

  6. 06

    libspdm 与 spdm-emu

Before you commit: 难点是把原本面向设备的 SPDM 消息流程绑定到 CPU TEE 远程证明:既要设计能覆盖 TEE Attestation 安全特性的消息与 Certificate 融合方案,又要在真实 CPU TEE 平台完成 requester/responder 实现。交付还要求 Rust 实现、SDK 与 Client-Server 两种构建形式、较高单元测试覆盖及端到端验证,并撰写绑定协议标准草案。

Source

How this page was assembled

Competition information is structured from the official page. Scores are platform estimates for decision support; official rules take precedence.

Official competition page
OpenAtom
Last checked
May 12, 2023

Entry assessment

est.
30

Prepare before joining

Overall fit estimate

Beginner fit30/100
Learning value60/100

Confirm eligibility and time commitment before moving into formal preparation.

Entry eligibility needs official confirmation

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Data and review state

Separate what is confirmed from what still needs review. Official rules and deadlines win.

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Source page verifiedMetric confirmedReviewed
Source published
May 12, 2023
Source created
May 12, 2023
Published on this site
Jul 21, 2026

Official metric is not published on the OpenAtom competition listing; verify scoring on the competition page.

reward_value_usd is a rough CNY→USD estimate (×0.14) for ranking only; use reward_summary for the official prize text.