skill-scanner
Reduces security risk from AI agent skill misuse by detecting dangerous capability patterns before deployment.
Security scanner for AI agent skills from Cisco AI Defense. Combines pattern-based detection (YAML + YARA rules), LLM-as-a-judge, and behavioral dataflow analysis to catch prompt injection, data exfiltration, and malicious code in skill files before you install them. Supports Codex and Cursor skill formats per the Agent Skills spec, scans Claude Code commands and flat markdown repos with --lenient, and ships SARIF output for CI/CD plus a pre-commit hook.
- Flag skills with file system write/delete permissions before deployment
- Detect skills requesting API keys or credential access patterns
- Identify skills with excessive network permissions or data exfiltration risk
Reduces security risk from AI agent skill misuse by detecting dangerous capability patterns before deployment. Prevents unauthorized data access, lateral movement, or system compromise through unvetted skill implementations.
Security teams and platform engineers vetting third-party or custom Claude skills before production rollout.
https://github.com/cisco-ai-defense/skill-scanner
By cisco-ai-defense
How to Get It
pip install cisco-ai-skill-scanner
Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.
After installing, paste this into Claude:
Help me flag skills with file system write/delete permissions before deployment
Trust Signals Auto-scanned
Community Pulse Active
Discussed on Hacker News, Reddit
- Cisco AI Agent Skills Security Scanner — Hacker News · 3 pts
- Cisco AI Defense Skill Scanner — Hacker News · 3 pts
- Security Scanner for Agent Skills — Hacker News · 2 pts
3 mentions across 1 sources
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 2,030 GitHub stars; contributors unknown; last commit 22d ago; license no license.
Things to check
- Best-effort detection, not certification — the README states plainly that 'no findings' does not mean a skill is safe, coverage is inherently incomplete, and false positives/negatives occur. Cisco recommends pairing scans with human review and threat modeling for high-risk deployments. Python 3.10+ required.
How to evaluate tools before deploying →
Data shown here comes from public APIs and automated scanning. Reviewer notes reflect one person's experience. This is not a security certification or legal recommendation. Always evaluate tools according to your own organization's policies.
Evaluation
Scored from trust signals (evidence-eval-v1): 2,030 GitHub stars; contributors unknown; last commit 22d ago; license no license.