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Security: nxl801/skill-optimizer

Security

SECURITY.md

Security Policy · 安全策略

本项目与安全强相关:它编排隔离的 Subagent 来盲测和修改 Agent Skill, 并在宿主无法强制角色边界时返回 SAFETY_BLOCKED

This project is security-relevant: it orchestrates isolated subagents to blind-test and patch Agent Skills, and returns SAFETY_BLOCKED when a host cannot enforce role boundaries.

Supported versions · 支持版本

Version Supported
0.1.x

Threat model · 威胁模型

The skill package specifies and validates the optimization protocol. It does not itself enforce isolation — file / tool / network / credential barriers are the host's responsibility (see references/cross-agent-compatibility.md).

  • In scope — 本仓库代码层面的缺陷 / vulnerabilities in this repository's code:

    • Bypass of Runner blindness (a script/adapter leaking a usage pair's expected/ directory, acceptance, rubric, or the A/B blinding map).
    • Path-traversal or symlink escape in scripts/_skill_utils.py's path resolver.
    • Circumvention of the hardcoding/overfitting detector (scripts/detect_case_hardcoding.py) so an unsafe candidate passes CLEAN.
    • A JSON Schema (schemas/) that accepts an unsafe artifact as VALID/CLEAN.
    • Tampering of the run-contract hash chain or unblinding provenance.
  • Out of scope — 超出范围:

    • The host agent's own sandbox / process isolation (report to the host vendor).
    • Model behavior, hallucination, or prompt-injection resistance of any LLM.
    • Misuse by an operator who deliberately disables the safety policy.

If the host cannot enforce the role barriers, the correct outcome is SAFETY_BLOCKED — never a lower-integrity single-agent run.

Reporting a vulnerability · 漏洞上报

🚨 请不要在公开 Issue 中报告安全漏洞。 Do NOT open a public issue for security vulnerabilities.

Please report privately via GitHub Private Security Advisories:

  1. Go to https://github.com/nxl801/skill-optimizer/security/advisories/new
  2. Click "Report a vulnerability".

Or email the maintainer via the GitHub no-reply address (nxl801@users.noreply.github.com) requesting a private channel.

Please include · 请包含:

  • A description of the issue and its impact.
  • The file(s) / line(s) involved (e.g. scripts/_skill_utils.py:NN).
  • A minimal reproduction (the bundled examples/simple-document-review/ is a good base).
  • Any suggested fix.

Commitment · 承诺

  • Acknowledge receipt within 5 business days · 5 个工作日内确认。
  • Provide an initial assessment within 14 days · 14 天内给出初步评估。
  • Coordinate disclosure and publish a fixed release + advisory once a fix is ready.

There aren't any published security advisories