Skill-Scan — Security Auditor for Agent Skills

Multi-layered security scanner for OpenClaw skill packages. Detects malicious code, evasion techniques, prompt injection, and misaligned behavior through static analysis and optional LLM-powered deep inspection. Run this BEFORE installing or enabling any untrusted skill.

Features

• 6 analysis layers — pattern matching, AST/evasion, prompt injection, LLM deep analysis, alignment verification, meta-analysis
• 60+ detection rules — execution threats, credential theft, data exfiltration, obfuscation, behavioral signatures
• Context-aware scoring — reduces false positives for legitimate API skills
• ClawHub integration — scan skills directly from the registry by slug
• Multiple output modes — text report (default), --json, --compact, --quiet
• Exit codes — 0 for safe, 1 for risky (easy scripting integration)

When to Use

MANDATORY before installing or enabling:

• Skills from ClawHub (any skill not authored by you)
• Skills shared by other users or teams
• Skills from public repositories
• Any skill package you haven't personally reviewed

RECOMMENDED for periodic audits of already-installed skills.

Quick Start

# Scan a local skill directory
skill-scan scan /path/to/skill

# Scan a skill from ClawHub before installing it
skill-scan scan-hub some-skill-slug

# Batch scan all installed skills
skill-scan batch /path/to/skills-directory

# JSON output for programmatic use
skill-scan scan-hub some-skill-slug --json

# Quiet mode (just score + verdict)
skill-scan scan-hub some-skill-slug --quiet

Risk Scoring

Exit Codes

• 0 — LOW risk (safe to proceed)
• 1 — MEDIUM or higher (block installation)

LLM Options

skill-scan scan-hub slug --llm        # Always run deep analysis (layers 4-5)
skill-scan scan-hub slug --llm-auto   # LLM only if pattern scan finds MEDIUM+
skill-scan scan-hub slug --llm-only   # Skip patterns, LLM analysis only

Provider auto-detected from environment:

• OPENAI_API_KEY -> gpt-4o-mini
• ANTHROPIC_API_KEY -> claude-sonnet-4-5

For the Agent

When the user asks to install a skill from ClawHub, follow this workflow:

1. Scan first — run skill-scan scan-hub <slug> BEFORE installing
2. Check the result:
   • If LOW risk (exit code 0): proceed with installation
   • If MEDIUM risk: show findings to the user and ask whether to proceed
   • If HIGH or CRITICAL risk: block installation and show the report
3. Report — always show the user the scan summary (score, risk level, finding count)

Alert Format

When a scan finds MEDIUM or higher risk:

🛡️ Skill-Scan Alert: {RISK_LEVEL} ({SCORE}/100)
Skill: {slug}
Findings: {count} issue(s) detected
Top threat: {highest severity finding title}
Action: Installation blocked pending review.

AGENTS.md Integration

To integrate skill-scan into your agent's workflow, add ONE of the following templates to your AGENTS.md (or equivalent agent instructions file).

Option A: Automatic Scanning (Recommended)

All ClawHub skill installs are automatically scanned before installation. No manual step needed.

## Skill-Scan — Automatic Pre-Install Security Scanning

BEFORE installing any skill from ClawHub, you MUST scan it with skill-scan first. This is non-negotiable — never skip the scan.

### Workflow

1. When the user asks to install a skill (e.g. `clawhub install <slug>`), run the scan FIRST:
   ```bash
   skill-scan scan-hub <slug>

2. Check the exit code and output:
   • Exit code 0 (LOW risk) — proceed with clawhub install <slug>
   • Exit code 1 (MEDIUM risk) — show findings to the user, ask whether to proceed
   • Exit code 1 (HIGH/CRITICAL risk) — BLOCK installation, show the full report
3. Never install a HIGH or CRITICAL risk skill without explicit user override
4. Always show the scan summary to the user before proceeding with installation

Periodic Audits

When asked to audit installed skills, batch scan the skills directory:

skill-scan batch {skillsDir}

LLM Deep Analysis

For high-stakes installs or when pattern scan returns MEDIUM, escalate to LLM analysis:

skill-scan scan-hub <slug> --llm-auto

### Option B: Manual On-Demand Scanning

Skills are only scanned when the user explicitly asks. Installation proceeds without automatic checks.

```markdown
## Skill-Scan — On-Demand Skill Security Scanning

skill-scan is available to audit skill packages for security threats. Use it when the user requests a security scan.

### Commands

- **Scan a ClawHub skill**: `skill-scan scan-hub <slug>`
- **Scan a local skill**: `skill-scan scan /path/to/skill`
- **Batch scan installed skills**: `skill-scan batch {skillsDir}`
- **Deep analysis with LLM**: add `--llm` or `--llm-auto` to any scan command

### Risk Levels

- **LOW (80-100)** — safe, no significant threats
- **MEDIUM (50-79)** — review findings, use caution
- **HIGH (20-49)** — serious threats, do not install
- **CRITICAL (0-19)** — multiple critical threats, do not install

### When the User Asks to Scan

1. Run the appropriate scan command
2. Show the scan summary (score, risk level, finding count)
3. If MEDIUM+, list the top findings with severity and description
4. Let the user decide what to do

Install-Time Setup

When this skill is first installed, ask the user:

How should skill-scan integrate with your workflow?

1. Automatic (Recommended) — Every clawhub install is scanned first. HIGH/CRITICAL installs are blocked automatically.
2. Manual — Scanning only happens when you explicitly ask for it.

Based on their choice, add the corresponding template (Option A or Option B above) to the project's AGENTS.md.

Detection Categories

Execution threats — eval(), exec(), child_process, dynamic imports

Credential theft — .env access, API keys, tokens, private keys, wallet files

Data exfiltration — fetch(), axios, requests, sockets, webhooks

Filesystem manipulation — Write/delete/rename operations

Obfuscation — Base64, hex, unicode encoding, string construction

Prompt injection — Jailbreaks, invisible characters, homoglyphs, roleplay framing, encoded instructions

Behavioral signatures — Compound patterns: data exfiltration, trojan skills, evasive malware, persistent backdoors

Requirements

• Python 3.10+
• httpx>=0.27 (for LLM API calls only)
• API key only needed for --llm modes (static analysis is self-contained)

Related Skills

• input-guard — External input scanning
• memory-scan — Agent memory security
• guardrails — Security policy configuration