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Agent Skill · 研究检索

security-auditor(安全审计员)

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。

security-auditor 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为接触敏感数据;许可证为 MIT,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 31,227。

总安装 2,742周安装 112GitHub Stars 98下载 878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

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:security-auditor(安全审计员)
来源仓库:https://github.com/erichowens/some_claude_skills
仓库路径:skills/security-auditor
安装命令:
npx skills add https://github.com/erichowens/some_claude_skills --skill security-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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/erichowens/some_claude_skills --skill security-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。

代码级静态安全扫描,提前识别潜在漏洞和安全隐患。涵盖依赖漏洞检测、密钥泄露排查和 OWASP Top 10 合规检查。提供 actionable 修复建议和 stakeholder 安全态势报告生成。支持预部署审计和 PR 合并前的安全审查流程集成。使用时不能直接采信工具输出结果,必须人工复核关键发现项。

来源仓库内路径:skills/security-auditor

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 Codex、Claude、Cursor、Gemini CLI;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 npx skills add https://github.com/erichowens/some_claude_skills --skill security…;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

security-auditor 怎么安装?

在终端执行 npx skills add https://github.com/erichowens/some_claude_skills --skill security-auditor。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

security-auditor 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。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。

security-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。

security-auditor 是免费的吗?

来源标注的许可证是 MIT。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。

security-auditor 用的人多吗?

公开数据是累计安装 2,742 次,近一周安装 112 次,下载 878 次,GitHub 98 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。

security-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

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,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 Codex,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
security-auditor

安全审计员 · 本页

2,74298接触敏感数据MIT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

Security Auditor

Comprehensive security scanning for codebases. Identifies vulnerabilities before they become incidents. Focuses on actionable findings with remediation guidance.

When to Use

Use for:

  • Pre-deployment security audits
  • Dependency vulnerability scanning
  • Secret/credential leak detection
  • Code-level SAST (Static Application Security Testing)
  • Security posture reports for stakeholders
  • OWASP Top 10 compliance checking
  • Pre-PR security reviews

Do NOT use for:

  • Runtime security (WAF, rate limiting) - use infrastructure tools
  • Network security/firewall rules - use cloud/DevOps skills
  • SOC2/HIPAA/PCI compliance - requires legal/organizational process
  • Penetration testing execution - this is detection, not exploitation

Quick Start

Full Security Audit

# Run comprehensive scan
./scripts/full-audit.sh /path/to/project

# Output: security-report.json + summary

Quick Checks

# Dependency vulnerabilities only
npm audit --json > deps-audit.json

# Secret detection only
./scripts/detect-secrets.sh /path/to/project

# OWASP check specific file
./scripts/owasp-check.py /path/to/file.js

Core Scanning Capabilities

1. Dependency Scanning

Package ManagerCommandSeverity Levels
npmnpm audit --jsoncritical, high, moderate, low
yarnyarn audit --jsonsame as npm
pippip-audit --format jsoncritical, high, medium, low
cargocargo audit --jsonsame

Decision Tree:

Critical severity found?
├── YES → Block deployment, immediate fix required
│   └── Check if patch available → npm audit fix --force
├── NO → High severity?
    ├── YES → Fix within sprint, document if deferred
    └── NO → Low/Moderate → Track, fix during maintenance

2. Secret Detection

High-Risk Patterns:

  • API keys: /[A-Za-z0-9_]{20,}/ near "key", "api", "secret"
  • AWS credentials: AKIA[0-9A-Z]{16}
  • Private keys: -----BEGIN (RSA|EC|OPENSSH) PRIVATE KEY-----
  • JWT tokens: eyJ[A-Za-z0-9_-]+\.eyJ[A-Za-z0-9_-]+\.[A-Za-z0-9_-]+
  • Connection strings: ://[^:]+:[^@]+@

Entropy Analysis:

  • Shannon entropy > 4.5 on strings > 20 chars = suspicious
  • Base64-encoded blobs in source = investigate

False Positive Handling:

Secret-like pattern found?
├── In test file? → Lower severity, document
├── In example/docs? → Check if placeholder
├── High entropy + near "password"/"secret" → High confidence
└── In .env.example? → Acceptable if placeholder values

3. OWASP Top 10 Static Analysis

#VulnerabilityDetection Pattern
A01Broken Access ControlMissing auth checks on routes
A02Cryptographic FailuresWeak algorithms (MD5, SHA1 for passwords)
A03InjectionUnparameterized queries, eval(), innerHTML
A04Insecure DesignHardcoded credentials, missing rate limits
A05Security MisconfigurationDebug mode in prod, default credentials
A06Vulnerable ComponentsKnown CVEs in dependencies
A07Auth FailuresWeak password policies, session issues
A08Integrity FailuresUnsigned updates, untrusted deserialization
A09Logging FailuresSensitive data in logs, missing audit trails
A10SSRFUnvalidated URL inputs to fetch/request

4. Language-Specific Checks

JavaScript/TypeScript:

  • eval(), new Function() - code injection
  • innerHTML, outerHTML - XSS vectors
  • document.write() - DOM-based XSS
  • child_process.exec() with user input - command injection
  • Regex without timeout - ReDoS vulnerability

Python:

  • pickle.loads() with untrusted data - arbitrary code execution
  • yaml.load() without Loader=SafeLoader - code injection
  • subprocess.shell=True - command injection
  • eval(), exec() - code injection
  • SQL string concatenation - SQL injection

SQL:

  • String concatenation in queries - SQL injection
  • LIKE '%' + input + '%' - injection via wildcards
  • Missing parameterization - critical vulnerability

Anti-Patterns

Anti-Pattern: Security by Obscurity

What it looks like: "Nobody will find this hardcoded password" Why wrong: Secrets in source always leak eventually Instead: Environment variables, secret managers, zero hardcoded secrets

Anti-Pattern: Audit Fatigue

What it looks like: 500 findings, all "medium", team ignores Why wrong: Critical issues buried in noise Instead: Prioritize by exploitability, start with critical/high only

Anti-Pattern: Fix Without Understanding

What it looks like: npm audit fix --force without review Why wrong: May introduce breaking changes, doesn't address root cause Instead: Review each fix, understand the vulnerability, test after

Anti-Pattern: One-Time Audit

What it looks like: "We did a security audit last year" Why wrong: New CVEs daily, code changes constantly Instead: CI/CD integration, weekly automated scans minimum

Security Report Format

{
  "summary": {
    "critical": 0,
    "high": 2,
    "medium": 5,
    "low": 12,
    "informational": 8
  },
  "findings": [
    {
      "id": "SEC-001",
      "severity": "high",
      "category": "A03:Injection",
      "title": "SQL Injection in user search",
      "location": "src/api/users.js:45",
      "description": "User input concatenated directly into SQL query",
      "evidence": "const query = `SELECT * FROM users WHERE name = '${input}'`",
      "remediation": "Use parameterized queries: db.query('SELECT * FROM users WHERE name = $1', [input])",
      "references": ["https://owasp.org/www-community/attacks/SQL_Injection"]
    }
  ],
  "recommendations": [
    "Implement parameterized queries across all database access",
    "Add input validation layer",
    "Enable SQL query logging for monitoring"
  ]
}

CI/CD Integration

GitHub Actions Example

security-scan:
  runs-on: ubuntu-latest
  steps:
    - uses: actions/checkout@v4
    - name: Run security audit
      run: |
        npm audit --json > audit.json
        ./scripts/detect-secrets.sh . > secrets.json
        ./scripts/generate-report.py
    - name: Fail on critical
      run: |
        if jq '.summary.critical > 0' report.json; then
          echo "Critical vulnerabilities found!"
          exit 1
        fi

Scripts (in scripts/ folder)

ScriptPurpose
full-audit.shComprehensive security scan
detect-secrets.shHigh-entropy string and pattern detection
owasp-check.pyOWASP Top 10 static analysis
generate-report.pyCombine findings into unified report

Expert vs Novice Approach

NoviceExpert
Runs audit once before releaseCI/CD integration, every commit
Focuses on tool output onlyUnderstands vulnerability context
Fixes everything or nothingTriages by exploitability
Uses one scannerLayers multiple tools
Ignores false positivesTunes detection rules

Success Metrics

MetricTarget
Critical/High pre-production0
Mean time to remediate critical< 24 hours
False positive rate< 10%
Scan coverage100% of deployable code

Reference Files

  • references/owasp-top-10-2024.md - Detailed OWASP guidance
  • references/secret-patterns.md - Comprehensive regex patterns
  • references/remediation-playbook.md - Fix guidance by vulnerability type
  • references/ci-cd-templates.md - Integration examples
  • scripts/ - Working security scanning scripts

Detects: Dependency CVEs | Secret leaks | Injection vulnerabilities | OWASP violations | Security misconfigurations

Use with: site-reliability-engineer (deployment gates) | code-review (PR security checks)

平台分布

Claude Code

26.41%
按下载量换算232

Codex

23.37%
按下载量换算205

windsurf

18.67%
按下载量换算164

Antigravity

11.22%
按下载量换算99

OpenCode

8.4%
按下载量换算74

Cursor

3.67%
按下载量换算32

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

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。

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