skill-scanner

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.

7 stars

Best use case

skill-scanner is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

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.

Teams using skill-scanner should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/ai-skill-scanner/SKILL.md --create-dirs "https://raw.githubusercontent.com/Demerzels-lab/elsamultiskillagent/main/public/skills/hugosbl/ai-skill-scanner/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/ai-skill-scanner/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How skill-scanner Compares

Feature / Agentskill-scannerStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

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.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# 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

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