Skill Guard Pro

Security scanner for ClawHub skills. Analyze before you install.

ClawGuard 🛡️

Scan ClawHub skills for security risks before installing.

ClawGuard performs static code analysis on ClawHub skills to detect:

• 🌐 Network exfiltration (HTTP POST to external URLs)
• 🔑 Credential access (API keys, tokens, passwords)
• ⚡ Shell command execution
• 💥 File destruction (rm -rf, unlink)
• 🎭 Code obfuscation (eval, base64 decode)
• 👻 Hidden files and directories

Usage

Scan by skill name

Download and scan a skill from ClawHub:

bash

uv run {baseDir}/scripts/scan.py --skill <skill-name>

Scan local directory

Scan a skill directory on your local filesystem:

bash

uv run {baseDir}/scripts/scan.py --path /path/to/skill

JSON output

Get results in JSON format:

bash

uv run {baseDir}/scripts/scan.py --skill <skill-name> --json

Examples

Scan the GitHub skill:

bash

uv run {baseDir}/scripts/scan.py --skill github

Scan a local skill:

bash

uv run {baseDir}/scripts/scan.py --path ~/.openclaw/skills/my-skill

Risk Levels

• 🟢 SAFE (0-30): No significant risks detected
• 🟡 CAUTION (31-60): Review flagged items before installing
• 🔴 DANGEROUS (61-100): High-risk patterns detected — DO NOT INSTALL

Exit Codes

• 0: Safe
• 1: Caution
• 2: Dangerous

Requirements

• Python 3.11+
• uv (Python package manager)
• clawhub CLI (optional, for downloading skills)

How It Works

1. Pattern Matching: Regex-based detection of dangerous code patterns
2. AST Analysis: Python AST parsing for eval/exec detection
3. URL Extraction: Identifies all network endpoints
4. Risk Scoring: Weighted severity scoring (0-100)

What It Detects

Category	Weight	Examples
Network exfiltration	25	POST to unknown URL with data
Credential access	20	Reading API keys, tokens
Shell execution	15	exec(), subprocess, system()
File destruction	15	rm -rf, unlink, rmdir
Obfuscation	15	eval(), atob(), Buffer.from
Hidden files	10	Dotfiles, hidden directories

Limitations

• Static analysis only: Cannot detect runtime behavior
• Regex-based: May have false positives/negatives
• JS/TS: Basic pattern matching (no full AST parsing)
• Encrypted/minified code: Cannot analyze obfuscated payloads

Best Practices

1. Always scan before installing untrusted skills
2. Review CAUTION-level findings manually
3. Check network endpoints for unknown domains
4. Never install DANGEROUS skills without verification
5. Report suspicious skills to ClawHub moderators

License

MIT