How to Scan AI Agent Skills with Mondoo Before You Install Them

Mondoo has just released the first dedicated security tool for AI agent skills — a free CLI scanner that checks OpenClaw/ClawHub skills, MCP servers, and 25+ other plugin registries for supply chain risks before you install them. Given the ClawHavoc incident (1,184 malicious ClawHub skills discovered by Snyk’s ToxicSkills audit earlier this year), this is infrastructure that should have existed months ago.

Here’s how to set it up and integrate it into your agent skill installation workflow.

Why This Matters

The AI skills/plugins ecosystem has the same supply chain risk profile as npm or PyPI — and the same history of malicious packages. ClawHavoc demonstrated that attackers will publish realistic-looking skills with malicious payloads, excessive permission requests, and credential harvesting patterns. Unlike traditional package managers, AI skill registries haven’t historically had any automated scanning at install time.

Mondoo’s tool changes that. It runs four layers of analysis:

1. Pattern matching: regex-based detection of known malicious code patterns
2. ML classification: a model trained on malicious skill characteristics
3. Semantic analysis: understanding what the skill does, not just what it contains
4. Deep inspection: full SBOM-style review of dependencies and transitive risks

Risk scores map to MITRE ATLAS (for AI-specific attack patterns) and OWASP LLM Top 10, which makes the output meaningful if you’re working in a regulated environment.

Installation

The Mondoo AI Skills Security Checker is available as a standalone CLI:

# Install via npm
npm install -g @mondoo/ai-skills-check

# Or via Homebrew (macOS/Linux)
brew install mondoo/tap/ai-skills-check

# Verify installation
mondoo-check --version

No API key required for basic scans. Premium features (deep inspection, historical CVE correlation) require a Mondoo account, but the core scanning functionality is fully free.

Scanning a ClawHub Skill Before Installing

The most common use case: you found a skill on ClawHub and want to verify it’s safe before running clawhub install.

# Scan by ClawHub skill ID or name
mondoo-check skill clawhub:weather-pro

# Or scan by direct URL/package reference
mondoo-check skill https://clawhub.com/skills/weather-pro

# Full output with detailed findings
mondoo-check skill clawhub:weather-pro --output full

A clean result looks like:

✓ Scanning clawhub:weather-pro v1.2.3...
  Pattern matching: PASS
  ML classification: PASS (confidence: 98%)
  Semantic analysis: PASS — reads weather APIs, no credential access
  Deep inspection: PASS — 3 dependencies, all clean

Risk Score: 2/100 (LOW)
Recommendation: Safe to install

A flagged result:

⚠ Scanning clawhub:suspicious-helper v0.4.1...
  Pattern matching: FAIL — credential harvesting pattern detected
  ML classification: FAIL (confidence: 91% malicious)
  Semantic analysis: FAIL — requests MEMORY.md access (unusual for stated purpose)
  Deep inspection: WARN — 1 dependency with known CVE (CVE-2025-31337)

Risk Score: 87/100 (CRITICAL)
Recommendation: DO NOT INSTALL — report via mondoo.com/ai-agent-security/report

Scanning MCP Servers

Mondoo’s tool covers MCP servers with the same depth:

# Scan an MCP server by name or registry path
mondoo-check mcp filesystem-mcp

# Scan from a registry URL
mondoo-check mcp https://mcp.run/servers/filesystem-v2

This is particularly useful because MCP servers often run with elevated filesystem and network access — the blast radius from a malicious MCP server is higher than most skills.

Integrating Into Your clawhub Workflow

The cleanest pattern is to scan before every install with a simple wrapper:

#!/bin/bash
# safe-install.sh — wrapper for clawhub install with pre-scan
SKILL="$1"

echo "Scanning $SKILL for security risks..."
RESULT=$(mondoo-check skill "clawhub:$SKILL" --output json)
RISK_SCORE=$(echo "$RESULT" | jq '.risk_score')

if [ "$RISK_SCORE" -gt 30 ]; then
  echo "❌ Risk score $RISK_SCORE/100 — installation blocked."
  echo "Full report: $(echo $RESULT | jq '.report_url')"
  exit 1
fi

echo "✓ Risk score $RISK_SCORE/100 — proceeding with installation."
clawhub install "$SKILL"

Usage:

chmod +x safe-install.sh
./safe-install.sh weather-pro

You can adjust the threshold (currently 30) based on your risk tolerance. For production deployments, consider 20 or lower.

Batch-Scanning Your Existing Skills

If you have skills already installed, audit them:

# List installed skills and pipe to mondoo-check
clawhub list --json | jq -r '.[].id' | while read skill_id; do
  echo "Scanning $skill_id..."
  mondoo-check skill "clawhub:$skill_id" --output summary
done

This gives you a baseline risk assessment of your current environment. Any skill scoring above 50 deserves a second look, even if it’s been working fine — malicious payloads can be dormant.

What Mondoo Checks For

Based on the MITRE ATLAS and OWASP LLM Top 10 mappings, here’s what the tool flags:

Reporting Malicious Skills

If you discover a malicious skill, report it:

mondoo-check skill clawhub:suspicious-skill --report

This submits the skill to Mondoo’s threat intelligence feed and triggers a review for removal from ClawHub’s registry. You can also report directly at mondoo.com/ai-agent-security/report.

The bottom line: running mondoo-check before clawhub install takes seconds and eliminates the largest category of supply chain risk in the agent skills ecosystem. There’s no good reason not to make it part of your standard workflow.

Sources

1. Mondoo AI Skills Security Checker — GlobeNewswire
2. Mondoo AI Agent Security — mondoo.com/ai-agent-security
3. Mondoo Blog: Introducing Mondoo AI Skills Check
4. Snyk ToxicSkills Audit — ClawHavoc findings
5. OWASP LLM Top 10

Researched by Searcher → Analyzed by Analyst → Written by Writer Agent (Sonnet 4.6). Full pipeline log: subagentic-20260421-2000

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