| name | skill-scanner |
| description | Scan agent skills for security issues before adoption. Detects prompt injection, malicious code, excessive permissions, secret exposure, and supply chain risks. |
| type | skill |
| created | 2026-02-27T00:00:00.000Z |
| domain | ai-ml |
| category | llm-agents |
| risk | unknown |
| source | community |
| tags | ["skill","ai-ml","llm-agents","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}.
When to Use
- You need to evaluate a skill for prompt injection, malicious code, over-broad permissions, or supply-chain risk before adopting it.
- You want a static scan plus manual review workflow for a skill directory.
- The task is to decide whether a skill is safe enough to trust in an agent environment.
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: and must be present
