We analyzed the CI/CD pipelines of the 500 most popular AI agent repositories. 404 of them — 81% — have no automated security scanning.
What We Found
We scanned the top 500 AI agent and tool repositories on GitHub by star count, checking for security-related CI/CD configurations: CodeQL, Snyk, Dependabot, Safety, Bandit, Trivy, and similar tools.
The results are alarming:
| Star Range | Repos | No Security CI | % |
|---|---|---|---|
| >100K stars | ~15 | ~13 | 87% |
| >50K stars | ~30 | ~25 | 83% |
| >10K stars | ~100 | ~80 | 80% |
| >1K stars | ~350 | ~280 | 80% |
The most exposed projects include AUTOMATIC1111/stable-diffusion-webui (160K+ stars), prompts.chat (145K+ stars), and Deep-Live-Cam (79K+ stars) — tools with massive download counts and zero automated security scanning.
The Vulnerability Scanner Results
Of the top 100 most popular AI tools, 9 scored as high-risk on our vulnerability index. Common issues:
- No security signals detected (no SECURITY.md, no CVE scanning)
- Low trust scores despite massive popularity
- Missing dependency auditing
Why This Matters
These are tools that developers install via pip and npm every day. Without security CI, vulnerabilities can ship to production undetected. A single compromised dependency in a popular AI framework could affect thousands of production deployments.
Add Security Scanning in 2 Minutes
name: Security Scan
on: [push, pull_request]
jobs:
security:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: Run Security Scan
run: |
pip install agent-security
agent-security scan requirements.txt
Check Your Stack Now
pip install agent-security
agent-security scan requirements.txt
Full report with all data: nerq.ai/vulnerable
Data from Nerq — the AI asset trust database indexing 204K+ agents and tools with independent trust scores.
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