skill-scanner
PassScan OpenBot/Clawdbot skills for security vulnerabilities, malicious code, and suspicious patterns before installing them. Use when a user wants to audit a skill, check if a ClawHub skill is safe, scan for credential exfiltration, detect prompt injection, or review skill security. Triggers on security audit, skill safety check, malware scan, or trust verification.
Install Skill
Skills are third-party code from public GitHub repositories. SkillHub scans for known malicious patterns but cannot guarantee safety. Review the source code before installing.
Install globally (user-level):
npx skillhub install openclaw/skills/skill-scannerInstall in current project:
npx skillhub install openclaw/skills/skill-scanner --projectSuggested path: ~/.claude/skills/skill-scanner/
AI Review
Scored 68 — substantial security scanning automation with 69KB of Python code covering 15+ threat categories. Good description with 6 trigger phrases. Deducted for niche generality (only useful for skill scanning) and lack of user-facing error handling documentation.
SKILL.md Content
---
name: skill-scanner
description: Scan OpenBot/Clawdbot skills for security vulnerabilities, malicious code, and suspicious patterns before installing them. Use when a user wants to audit a skill, check if a ClawHub skill is safe, scan for credential exfiltration, detect prompt injection, or review skill security. Triggers on security audit, skill safety check, malware scan, or trust verification.
---
# Skill Security Scanner
Scan skills for malicious patterns before installation. Detects credential exfiltration, suspicious network calls, obfuscated code, prompt injection, and other red flags.
## Quick Start
```bash
# Scan a local skill folder
python3 scripts/scan.py /path/to/skill
# Verbose output (show matched lines)
python3 scripts/scan.py /path/to/skill --verbose
# JSON output (for automation)
python3 scripts/scan.py /path/to/skill --json
```
## Workflow: Scan Before Install
1. Download or locate the skill folder
2. Run `python3 scripts/scan.py <skill-path> --verbose`
3. Review findings by severity (CRITICAL/HIGH = do not install)
4. Report results to user with recommendation
## Score Interpretation
| Score | Meaning | Recommendation |
|-------|---------|----------------|
| CLEAN | No issues found | Safe to install |
| INFO | Minor notes only | Safe to install |
| REVIEW | Medium-severity findings | Review manually before installing |
| SUSPICIOUS | High-severity findings | Do NOT install without thorough manual review |
| DANGEROUS | Critical findings detected | Do NOT install — likely malicious |
## Exit Codes
- `0` = CLEAN/INFO
- `1` = REVIEW
- `2` = SUSPICIOUS
- `3` = DANGEROUS
## Rules Reference
See `references/rules.md` for full list of detection rules, severity levels, and whitelisted domains.
## Limitations
- Pattern-based detection — cannot catch all obfuscation techniques
- No runtime analysis — only static scanning
- False positives possible for legitimate tools that access network/files
- Always combine with manual review for HIGH/MEDIUM findings