skill-scan（技能扫描）

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

1. 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:

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.

## 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