AI-first security scanning with Medusa. 3,000+ detection patterns covering AI/ML, agents, MCP, RAG, prompt injection, and traditional SAST vulnerabilities. Wraps Medusa CLI with SARIF/JSON parsing, structured finding output, OWASP mapping, and remediation guidance.
Scanned 9/6/2026
Install to Claude Code
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---
name: medusa-security
description: >-
AI-first security scanning with Medusa. 3,000+ detection patterns covering AI/ML, agents, MCP,
RAG, prompt injection, and traditional SAST vulnerabilities. Wraps Medusa CLI with SARIF/JSON
parsing, structured finding output, OWASP mapping, and remediation guidance.
version: 1.1.0
category: security
model: sonnet
invoked_by: agent
user_invocable: true
tools: [Read, Write, Edit, Bash, Glob, Grep]
agents: [security-architect, penetration-tester, code-reviewer]
tags: [security, sast, ai-security, mcp-security, prompt-injection, vulnerability-scanning]
best_practices:
- Run full scan before release for comprehensive coverage
- Use ai-only mode for rapid AI/LLM-focused checks
- Use quick mode during development for changed-files-only scanning
- Always review CRITICAL and HIGH findings before deployment
- Use --fail-on high in CI/CD pipelines
error_handling: graceful
streaming: supported
verified: true
lastVerifiedAt: 2026-02-22T00:00:00.000Z
source: builtin
trust_score: 100
provenance_sha: d1460c3e9767a2db
---
# Medusa Security Skill
## Identity
AI-first security scanner integration skill. Leverages Medusa's 76 scanners and 3,000+ detection
patterns for comprehensive security analysis including AI/ML-specific vulnerability detection.
## Capabilities
1. **Full Scan** — All 76 scanners, comprehensive security analysis
2. **AI-Only Scan** — Prompt injection, MCP security, agent security, RAG security
3. **Quick Scan** — Git-changed files only for rapid development feedback
4. **Targeted Scan** — Specific scanner categories (mcp, secrets, prompt-injection, etc.)
5. **SARIF Output Parsing** — Standard SARIF v2.1.0 structured findings
6. **JSON Output Parsing** — Medusa-native JSON format
7. **OWASP Mapping** — Maps findings to OWASP Agentic AI (ASI01-10) and OWASP Top 10 (A01-10)
8. **Remediation Guidance** — Links findings to agent-studio skills and agents
9. **CI/CD Integration** — Fail-on thresholds, SARIF upload for GitHub Code Scanning
## Prerequisites
```
Python 3.10+
pip install medusa-security
```
Check installation: `python -m medusa --version`
## Workflow: Full Security Scan
```bash
# Step 1: Verify installation
python -m medusa --version
# Step 2: Run scan
medusa scan . --format sarif --fail-on high
# Step 3: Parse output (use scripts/main.cjs)
node .claude/skills/medusa-security/scripts/main.cjs --mode full --target .
# Step 4: Review findings by severity
# CRITICAL → immediate fix required
# HIGH → fix before release
# MEDIUM → fix in next sprint
# LOW → track and address
```
## Workflow: AI-Only Scan
```bash
medusa scan . --format sarif --ai-only
```
Scans only: prompt injection (800+ patterns), MCP security (400+ patterns), agent security
(500+ patterns), RAG security (300+ patterns).
## Workflow: Quick Scan (Development)
```bash
medusa scan . --format sarif --quick
```
Only scans git-changed files. Use during development for rapid feedback.
## Workflow: Targeted Scan
```bash
# MCP security only
medusa scan . --format sarif --scanners mcp-server,mcp-config
# Secrets only
medusa scan . --format sarif --scanners secrets,gitleaks,env
# AI context files only
medusa scan . --format sarif --scanners ai-context
```
## Output Processing
The skill uses helper scripts located at `.claude/skills/medusa-security/scripts/`:
| Script | Purpose |
| ----------------------- | ----------------------------------------------- |
| `sarif-parser.cjs` | Parses SARIF v2.1.0 output |
| `json-parser.cjs` | Parses Medusa JSON output |
| `finding-formatter.cjs` | Formats findings with OWASP mapping |
| `main.cjs` | Orchestrates the full pipeline |
| `cli-wrapper.cjs` | Wraps Medusa CLI invocation |
| `security-review.cjs` | Deterministic report writer (no Glob recursion) |
### Using the Pipeline
```bash
# Full scan with structured output
node .claude/skills/medusa-security/scripts/main.cjs --mode full --target .
# AI-only scan
node .claude/skills/medusa-security/scripts/main.cjs --mode ai-only --target .
# Quick scan (git-changed files)
node .claude/skills/medusa-security/scripts/main.cjs --mode quick --target .
```
### Deterministic Security Review (Recommended in Claude sessions)
Use this when you need the final security review report and want to avoid recursive `Glob` timeouts:
```bash
node .claude/skills/medusa-security/scripts/security-review.cjs
```
This writes:
`/.claude/context/reports/security/security-review-medusa-scan-2026-02-17.md`
and performs fixed-path checks on:
- `.claude/hooks/`
- `.claude/lib/`
- `.claude/skills/medusa-security/scripts/`
- `.claude/CLAUDE.md`
### Important Runtime Guardrail
- Avoid recursive glob patterns like `.claude/skills/medusa-security/**/*` in long sessions.
- Prefer direct file reads and deterministic script entry points.
## OWASP Mapping
Findings are automatically mapped to:
- **OWASP Agentic AI Top 10** (ASI01-10): Goal Hijacking, Tool Misuse, Context Poisoning, etc.
- **OWASP Top 10** (A01-10): Broken Access Control, Injection, Cryptographic Failures, etc.
## Severity Triage
| Severity | Action | Timeline |
| -------- | ------------------ | ---------------- |
| CRITICAL | Immediate fix | Before any merge |
| HIGH | Fix before release | Same sprint |
| MEDIUM | Fix in next sprint | Next cycle |
| LOW | Track and address | Backlog |
## Agent Integration
| Agent | Usage |
| -------------------- | ----------------------------------------------------------- |
| `security-architect` | Primary consumer. Use for comprehensive security reviews. |
| `penetration-tester` | Use for targeted vulnerability scanning with authorization. |
| `code-reviewer` | Use AI-only scan as part of code review workflow. |
## CI/CD Integration
```yaml
# GitHub Actions example
- name: Security Scan
run: |
pip install medusa-security
medusa scan . --format sarif --fail-on high -o reports/
- name: Upload SARIF
uses: github/codeql-action/upload-sarif@v3
with:
sarif_file: reports/medusa-results.sarif
```
## Iron Laws
1. **ALWAYS** verify Medusa installation before scanning — `python -m medusa --version` first; a missing install produces no output instead of an error, silently masking all vulnerabilities.
2. **NEVER** rely on AI-only mode as the release gate — AI-only mode misses traditional SAST patterns (SQLi, XSS, path traversal); full scan covering all 76 scanners is required for release-gate decisions.
3. **ALWAYS** set `--fail-on high` in CI/CD pipelines — without a fail threshold, pipelines pass even when CRITICAL findings exist, creating false confidence in the security posture.
4. **NEVER** skip SARIF upload to GitHub Code Scanning — local-only SARIF is lost after the build; uploading via `github/codeql-action/upload-sarif@v3` persists findings for PR review, trend tracking, and compliance audit trails.
5. **ALWAYS** fix CRITICAL and HIGH findings before merging — deploying with unresolved high-severity findings expands the attack surface and nullifies the security posture gain from scanning.
## Anti-Patterns
| Anti-Pattern | Why It Fails | Correct Approach |
| ------------------------------------ | ----------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------- |
| Skipping installation check | Missing Medusa produces no output, not an error — all vulnerabilities silently missed | Run `python -m medusa --version` first; abort on non-zero exit |
| Using AI-only mode as a release gate | AI-only misses traditional SAST patterns (SQLi, XSS, path traversal) — 76 scanners needed for full coverage | Use full-scan mode for CI/CD gates; AI-only mode for rapid dev-time feedback only |
| No fail-on threshold in CI | Pipeline passes even when CRITICAL findings exist — false confidence in security posture | Always use `--fail-on high` in CI pipelines; adjust to `--fail-on critical` for high-risk repos |
| Ignoring MEDIUM findings | MEDIUM findings compound into exploitable chains when combined with HIGH findings | Triage MEDIUM findings each sprint; never allow them to accumulate without a tracking issue |
| Not uploading SARIF to Code Scanning | Findings live only in local files, lost after build — no PR-level review or trend tracking | Upload SARIF via `github/codeql-action/upload-sarif@v3` in every CI run |
## Memory Protocol
After scanning:
- Record new vulnerability patterns in `patterns.json`
- Log significant findings in `issues.md`
- Track scan history for trend analysis
- Use `recordGotcha()` for recurring false positives
```javascript
const manager = require('.claude/lib/memory/memory-manager.cjs');
manager.recordGotcha({
text: 'False positive: medusa flags X pattern in Y context',
area: 'security-scanning',
});
manager.recordPattern({
text: 'Prompt injection found in CLAUDE.md context files',
area: 'ai-security',
});
```
## Related Skills
- `security-architect` — Threat modeling and OWASP analysis
- `static-analysis` — CodeQL and Semgrep SARIF analysis
- `semgrep-rule-creator` — Create custom Semgrep rules
- `insecure-defaults` — Detect hardcoded credentials
- `variant-analysis` — Discover vulnerability variants
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