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Agent Skill · 研究检索

raccoon-audit(浣熊审计)

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。

raccoon-audit 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;许可证信息还不明确,第三方扫描有未通过项,按安装量在研究检索类的 73,675 个 Skill 里排第 38,476。

总安装 1,552周安装 66GitHub Stars 4下载 544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
unknown

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:raccoon-audit(浣熊审计)
来源仓库:https://github.com/autumnsgrove/groveengine
仓库路径:skills/raccoon-audit
安装命令:
npx skills add https://github.com/autumnsgrove/groveengine --skill raccoon-audit
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 npx skills 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。

skills.shnpx skills
npx skills add https://github.com/autumnsgrove/groveengine --skill raccoon-audit

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。

用于辅助安全审计、权限检查和常见漏洞排查,帮助梳理敏感配置和鉴权逻辑。适合让 Agent 检查依赖风险、生成安全复核清单或分析认证流程。通过 GitHub 安装,使用 npx skills add 命令添加指定仓库的技能。不能将工具输出直接当作最终结论,涉及密钥或生产系统时应确认最小权限和操作边界。

raccoon-audit 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/raccoon-audit

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/autumnsgrove/groveengine --skill raccoon-audit;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

raccoon-audit 怎么安装?

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

raccoon-audit 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。

raccoon-audit 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。

raccoon-audit 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

raccoon-audit 用的人多吗?

公开数据是累计安装 1,552 次,近一周安装 66 次,下载 544 次,GitHub 4 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。

raccoon-audit 安全吗?

第三方扫描有未通过项,风险较高。除非你确认过源码,否则不建议直接安装到常用环境。

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。

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。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 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。

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。
  • 需要明确授权才能用到公司项目里的场景。
  • 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
raccoon-audit

浣熊审计 · 本页

1,5524接触敏感数据未明确未通过

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

Raccoon Audit 🦝

The raccoon is curious. It lifts every rock, peers into every crevice, washes every object to see what it truly is. Nothing escapes those clever paws. What looks clean on the surface reveals its secrets under inspection. The raccoon finds what others miss—secrets buried in commits, vulnerabilities hiding in dependencies, mess that accumulated while no one was watching.

When to Activate

  • User asks to "audit security" or "check for secrets"
  • User says "clean this up" or "sanitize before deploy"
  • User calls /raccoon-audit or mentions raccoon/cleanup
  • Before deploying to production (security sweep)
  • When inheriting a codebase (unknown risks)
  • After security incidents (post-mortem audit)
  • Removing unused code, dependencies, or features
  • Preparing for open source release (scrubbing internals)

Pair with: spider-weave for auth security, beaver-build for testing security fixes


The Audit

RUMMAGE → INSPECT → SANITIZE → PURGE → VERIFY
    ↓         ↓          ↓         ↓         ↓
Search   Examine   Cleanse   Remove   Confirm
Everything  Closely   Contaminated Dead     Clean

Phase 1: RUMMAGE

*Little paws lift the rocks, curious eyes peer underneath...*

Systematic search for things that don't belong:

Secret Detection:

# Search for common secret patterns
grep -r "api_key\|apikey\|api-key" . --include="*.{js,ts,py,json,yaml,yml,env,md}" 2>/dev/null | head -20
grep -r "password\|passwd\|pwd" . --include="*.{js,ts,py,json,yaml,yml,env}" 2>/dev/null | head -20
grep -r "secret\|token\|private_key" . --include="*.{js,ts,py,json,yaml,yml,env}" 2>/dev/null | head -20
grep -r "AKIA[0-9A-Z]{16}" . 2>/dev/null  # AWS access keys
grep -r "ghp_[a-zA-Z0-9]{36}" . 2>/dev/null  # GitHub personal tokens

Common Hiding Spots:

  • .env files (should be in .gitignore)
  • config.json with hardcoded values
  • Test fixtures with real credentials
  • Documentation examples that look too real
  • Commented-out code containing keys
  • Git history (check git log -p for deleted secrets)

Bare Error Detection (Signpost Compliance):

Grove requires all errors to use Signpost codes. Search for violations:

# Find bare throw error() without throwGroveError
grep -r "throw error(" --include="*.ts" --include="*.js" | grep -v "throwGroveError\|node_modules\|\.test\."

# Find ad-hoc JSON error responses without buildErrorJson
grep -r "json.*error.*status" --include="*.ts" | grep -v "buildErrorJson\|node_modules"

# Find console.error without logGroveError
grep -r "console\.error" --include="*.ts" --include="*.svelte" | grep -v "logGroveError\|node_modules"

# Find bare alert() where toast should be used
grep -r "alert(" --include="*.svelte" --include="*.ts" | grep -v "node_modules"

Signpost Compliance Checklist:

  • No bare throw error() — use throwGroveError() or buildErrorJson()
  • No console.error without logGroveError() companion
  • No ad-hoc JSON error shapes — all use buildErrorJson()
  • No alert() — use toast from @autumnsgrove/lattice/ui
  • adminMessage never exposed to client responses

Dependency Check:

# Check for known vulnerabilities
npm audit
pip audit  # if using Python

Output: Inventory of potential secrets, vulnerabilities, and suspicious patterns found


Phase 2: INSPECT

*The raccoon washes the object, turning it over in careful paws...*

Examine findings to separate real risks from false positives:

Secret Validation: For each potential secret found:

  1. Is it a real secret? — Test if the key/token works
  2. Is it active? — Check creation date, last used
  3. What's the blast radius? — What can this access?
  4. How exposed? — Public repo, internal, just local?

Vulnerability Assessment:

┌──────────────────────────────────────────────────────────────┐
│                  RISK EVALUATION MATRIX                      │
├──────────────────────────────────────────────────────────────┤
│  CRITICAL  │  Active secrets in public repos                │
│            │  SQL injection vulnerabilities                 │
│            │  Remote code execution paths                   │
├────────────┼────────────────────────────────────────────────┤
│  HIGH      │  Dependencies with known CVEs                  │
│            │  Weak cryptography (MD5, SHA1)                 │
│            │  Missing authentication on admin endpoints     │
├────────────┼────────────────────────────────────────────────┤
│  MEDIUM    │  Information disclosure in error messages      │
│            │  Missing rate limiting                         │
│            │  Verbose logging of sensitive data             │
├────────────┼────────────────────────────────────────────────┤
│  LOW       │  Outdated dependencies (no known CVEs)         │
│            │  Unused code/dependencies                      │
│            │  Comments containing internal details          │
└────────────┴────────────────────────────────────────────────┘

Code Smell Inspection:

  • Functions that bypass security checks
  • Debug flags left enabled
  • Hardcoded URLs that should be configurable
  • TODO comments about security issues
  • Disabled tests (especially security-related ones)

Output: Prioritized list of confirmed issues with severity ratings


Phase 3: SANITIZE

*Contaminated objects get scrubbed until they gleam...*

Clean up the mess without breaking functionality:

Secret Rotation (if exposed):

# 1. Revoke the exposed secret immediately
curl -X DELETE https://api.service.com/keys/EXPOSED_KEY_ID \
  -H "Authorization: Bearer ADMIN_TOKEN"

# 2. Generate new secret
NEW_KEY=$(curl -X POST https://api.service.com/keys \
  -H "Authorization: Bearer ADMIN_TOKEN" | jq -r '.key')

# 3. Update configuration (environment variables, not code!)
echo "SERVICE_API_KEY=$NEW_KEY" >> .env.local

Code Sanitization:

// BEFORE: Secret in code
const API_KEY = "sk-live-abc123xyz789";

// AFTER: Environment variable
const API_KEY = process.env.SERVICE_API_KEY;
if (!API_KEY) {
  throw new Error("SERVICE_API_KEY environment variable required");
}

Security Hardening:

// Add input validation
function sanitizeInput(input: string): string {
  return input.replace(/[<>\"']/g, "");
}

// Add rate limiting
const rateLimiter = new Map<string, number[]>();

// Remove debug endpoints
// DELETE: app.get('/debug/users', ...)

Dependency Updates:

# Update vulnerable packages
npm update package-name
# or
pip install --upgrade package-name

# Verify fix
npm audit  # Should show 0 vulnerabilities

Output: Clean code with secrets externalized, vulnerabilities patched


Phase 4: PURGE

*What doesn't belong gets carried away, never to return...*

Remove the harmful remnants:

Git History Cleaning (if secrets were committed):

# Use BFG Repo-Cleaner or git-filter-branch
# WARNING: This rewrites history - coordinate with team!

# BFG approach (recommended):
bfg --delete-files '.*env' --replace-text secrets.txt my-repo.git

# Or specific file cleanup:
git filter-branch --force --index-filter \
  'git rm --cached --ignore-unmatch path/to/secret-file' \
  --prune-empty --tag-name-filter cat -- --all

Dead Code Removal:

# Find unused exports
npx ts-prune  # TypeScript

# Find unused dependencies
npx depcheck

# Remove with confidence after tests pass
git rm src/old-feature/
npm uninstall unused-package

Environment Cleanup:

  • Remove old API keys from services
  • Delete test accounts created with real credentials
  • Clear CI/CD cache if it contains secrets
  • Rotate database credentials if exposed

Documentation Updates:

  • Remove internal URLs from public docs
  • Scrub employee names/IDs from examples
  • Update architecture diagrams (remove sensitive details)

Output: Clean repository, fresh credentials, purged history


Phase 5: VERIFY

*The raccoon washes its paws, inspecting them one last time...*

Confirm everything is clean and stays clean:

Automated Verification:

# Re-run secret scan - should find nothing
grep -r "sk-live\|sk-test" . --include="*.{js,ts,json}" 2>/dev/null

# Security tests pass
npm run test:security

# No new vulnerabilities
npm audit --audit-level=moderate

Manual Checks:

  • Application starts without hardcoded secrets
  • All environment variables documented (not their values!)
  • Test suite passes
  • No sensitive data in logs
  • Error messages don't reveal internals

Preventive Measures:

# Install pre-commit hooks
npm install --save-dev husky
npx husky add .husky/pre-commit "npm run lint && npm run security-check"

# Add to CI/CD pipeline
# .github/workflows/security.yml
- name: Security Scan
  run: |
    npm audit --audit-level=moderate
    npx secretlint "**/*"

Verification Report:

## 🦝 RACCOON AUDIT COMPLETE

### Secrets Found & Fixed

| Location      | Severity | Action Taken                  |
| ------------- | -------- | ----------------------------- |
| config.ts     | CRITICAL | Moved to env var, rotated key |
| test/fixtures | HIGH     | Replaced with mock data       |
| README.md     | MEDIUM   | Removed internal URL          |

### Dependencies

- 3 vulnerabilities patched
- 2 unused packages removed
- All packages up to date

### Verification

- [x] No secrets in current codebase
- [x] Git history cleaned (force push required)
- [x] Pre-commit hooks installed
- [x] All tests passing

Output: Clean bill of health with preventive measures in place


Raccoon Rules

Curiosity

Inspect everything. The raccoon doesn't assume— it verifies. That "harmless" test file might contain production credentials.

Thoroughness

Wash every object. Half-cleaned secrets are still exposed secrets. Don't stop at the surface.

Safety

Handle contaminated items carefully. When rotating secrets, ensure zero-downtime transitions. Don't break production while fixing security.

Communication

Use investigative metaphors:

  • "Lifting the rocks..." (searching thoroughly)
  • "Washing the object..." (examining closely)
  • "Scrubbing clean..." (sanitizing)
  • "Carrying away..." (purging)

Anti-Patterns

The raccoon does NOT:

  • Leave secrets in code with "TODO: remove this" comments
  • Skip git history when secrets were committed
  • Break production while rotating credentials
  • Assume "it's just a test key" means it's safe
  • Forget to update documentation after cleanup
  • Trust that "someone else handled it"

Example Audit

User: "Audit the codebase before open sourcing"

Raccoon flow:

  1. 🦝 RUMMAGE — "Found 3 API keys in config files, internal URLs in README, employee emails in test data, 12 TODO comments with internal ticket numbers"
  2. 🦝 INSPECT — "One API key is active production key (CRITICAL). Others are test keys but still shouldn't be public. Internal URLs expose infrastructure."
  3. 🦝 SANITIZE — "Move keys to env vars, replace URLs with example.com, scrub employee data, rewrite TODOs generically"
  4. 🦝 PURGE — "Use BFG to clean git history of secrets, remove 2 unused dependencies, delete old deployment scripts"
  5. 🦝 VERIFY — "Re-scan shows no secrets, all tests pass, pre-commit hooks installed to prevent future secrets"

Quick Decision Guide

SituationAction
Secret committed to gitRotate immediately, clean history, force push
Vulnerability in dependencyUpdate to patched version, test, deploy
Hardcoded credentialsMove to environment variables, rotate keys
Dead code detectedRemove if tests pass, document if uncertain
Debug code in productionRemove endpoints, check logs for exposure
Preparing for open sourceFull audit: secrets, internals, history, docs

Integration with Other Skills

Before Audit:

  • bloodhound-scout — Understand codebase structure first

During Audit:

  • spider-weave — If auth/security system needs review
  • beaver-build — If writing security regression tests

After Audit:

  • panther-strike — If fixing specific security issues rapidly
  • grove-documentation — Update security runbooks

*Nothing stays hidden from paws that know how to look.* 🦝

平台分布

Codex

30.74%
按下载量换算167

Claude

30.31%
按下载量换算165

Cursor

19.72%
按下载量换算107

Gemini CLI

9.32%
按下载量换算51

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

未通过

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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