Cisco AI Skill Scanner

Scan agent skills for security threats using the Cisco AI skill-scanner CLI. Triggers on: scan skill for security, check skill safety, audit skill code, skill-scanner, detect prompt injection in skill, skill malware check, scan skills directory, security audit skill, validate skill before publishing, skill threat detection.

Security scanner for agent skills. Detects prompt injection, data exfiltration, credential harvesting, and malicious code patterns using static analysis, behavioral dataflow, and optional LLM-as-a-judge.

Quick Scan (recommended default)

bash

bash scripts/scan.sh /path/to/skill

Commands

Scan a single skill

bash

skill-scanner scan /path/to/skill

Scan with behavioral analysis (dataflow)

bash

skill-scanner scan /path/to/skill --use-behavioral

Full scan (all engines, requires API key)

bash

SKILL_SCANNER_LLM_API_KEY="$ANTHROPIC_API_KEY" \
SKILL_SCANNER_LLM_MODEL="claude-sonnet-4-5" \
skill-scanner scan /path/to/skill --use-behavioral --use-llm --enable-meta --llm-provider anthropic

Scan all skills in a directory

bash

skill-scanner scan-all /root/clawd/skills --recursive --use-behavioral

Scan with detailed markdown report

bash

skill-scanner scan /path/to/skill --use-behavioral --format markdown --detailed

Scan before publishing to ClawHub

bash

skill-scanner scan /path/to/skill --use-behavioral --fail-on-severity medium

Severity Levels

• CRITICAL / HIGH — Do not install/publish. Review and fix immediately.
• MEDIUM — Suspicious patterns. Investigate before use.
• LOW — Minor issues. Document and accept risk or fix.
• INFO — Informational only (e.g. missing license). Safe to publish.
• SAFE (0 findings) — No known threat patterns detected.

Key Flags

Flag	Purpose
--use-behavioral	AST dataflow analysis (recommended, no API key needed)
--use-llm	LLM semantic analysis (requires API key)
--enable-meta	False positive filtering
--fail-on-severity high	Exit non-zero if HIGH/CRITICAL found (CI/CD)
--format markdown	Markdown report
--format html	Interactive HTML report
--detailed	Include per-finding code snippets
--lenient	Tolerate malformed skills

Workflow: Before Publishing a Skill to ClawHub

1. Run: bash scripts/scan.sh /path/to/skill
2. If SAFE (0 findings) → proceed to publish
3. If INFO only → add missing fields (license, homepage, deps) and re-scan
4. If MEDIUM+ → investigate and fix before publishing

Notes

• "No findings" does not guarantee a skill is 100% safe -- it means no known patterns were detected
• The scanner flags the lossless-claw plugin as a false positive (file read + network send is the LCM summarization pipeline -- it is safe)
• Always run at minimum --use-behavioral for dataflow coverage