skill-scanner

Skill Security Scanner

Scan agent skills for security issues before adoption. Detects prompt injection, malicious code, excessive permissions, secret exposure, and supply chain risks.

Important: Run all scripts from the repository root using the full path via ${CLAUDE_SKILL_ROOT}.

Bundled Script

scripts/scan_skill.py

Static analysis scanner that detects deterministic patterns. Outputs structured JSON.

uv run ${CLAUDE_SKILL_ROOT}/scripts/scan_skill.py <skill-directory>

Returns JSON with findings, URLs, structure info, and severity counts. The script catches patterns mechanically — your job is to evaluate intent and filter false positives.

Workflow

Phase 1: Input & Discovery

Determine the scan target:

• If the user provides a skill directory path, use it directly
• If the user names a skill, look for it under plugins/*/skills/<name>/ or .claude/skills/<name>/
• If the user says "scan all skills", discover all */SKILL.md files and scan each

Validate the target contains a SKILL.md file. List the skill structure:

ls -la <skill-directory>/
ls <skill-directory>/references/ 2>/dev/null
ls <skill-directory>/scripts/ 2>/dev/null

Phase 2: Automated Static Scan

Run the bundled scanner:

uv run ${CLAUDE_SKILL_ROOT}/scripts/scan_skill.py <skill-directory>

Parse the JSON output. The script produces findings with severity levels, URL analysis, and structure information. Use these as leads for deeper analysis.

Fallback: If the script fails, proceed with manual analysis using Grep patterns from the reference files.

Phase 3: Frontmatter Validation

Read the SKILL.md and check:

• Required fields: name and description must be present
• Name consistency: name field should match the directory name
• Tool assessment: Review allowed-tools — is Bash justified? Are tools unrestricted (*)?
• Model override: Is a specific model forced? Why?
• Description quality: Does the description accurately represent what the skill does?