Audit

Skill IamBiswajitSahoo/ClaudeSkills/plugins/bix-utils/skills/audit

bix — A Claude Code plugin marketplace with useful skills for everyday productivity.

Install

npx -y skills add IamBiswajitSahoo/ClaudeSkills --skill audit

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Security audit for Claude Code skills, MCP servers, hooks, and CLAUDE.md files — runs fast pattern scan then parallel deep-analysis agents.

SKILL.md

5.3 KB, as published. Nobody here has run it

Security Audit

Audit Claude Code extension surfaces (skills, MCP servers, hooks, CLAUDE.md) for security risks. Quick pattern scan first, then optional parallel deep analysis.

Phase 1 — Parse & route

Prereq: verify Python 3 with python3 --version 2>/dev/null || python --version 2>/dev/null. Store the working command as {PY}. If neither works or it's Python 2.x, stop and tell the user to install Python 3.

Parse $ARGUMENTS for <mode> [target]:

Modes: skill, mcp, hooks, claudemd, all.
Targets (skill/mcp only): local path, GitHub URL, GitHub subdirectory URL (e.g. .../tree/main/skills/x), or npm package @scope/pkg (mcp only).
If mode is missing/invalid, ask via AskUserQuestion with the 5 modes.
If skill or mcp with remote target and no local target given, ask for one.

Resolve target (skill/mcp with target):

{PY} "${CLAUDE_SKILL_DIR}/scripts/resolve-target.py" "<target>" --type <skill|mcp>

Returns {source, resolved_path, is_temporary, temp_root, error}. On error, stop. If is_temporary, remember temp_root for Phase 4 cleanup and tell the user the target was downloaded.

For mcp without target: run gather-mcp-config.py — if no servers, stop with "No MCP servers configured". For hooks/claudemd: no resolution needed.

Phase 2 — Quick scan

Run the relevant gather + pattern-scan scripts in parallel (multiple Bash calls in one message):

Mode	Gather	Pattern scan
skill	`gather-skill-inventory.py <path>`	`pattern-scan.py <path> --type skill`
mcp	`gather-mcp-config.py <server-or-empty>`	`pattern-scan.py <src>` per server with local files
hooks	`gather-hooks-config.py`	`pattern-scan.py <script>` for each referenced script
claudemd	—	`pattern-scan.py ./CLAUDE.md --type skill` (+ `.claude/CLAUDE.md` if present)
all	all four gather scripts in parallel	`pattern-scan.py . --type plugin`

All scripts are {PY} "${CLAUDE_SKILL_DIR}/scripts/<name>" ....

Show summary:

## Quick Scan Results
Risk Score: {score}/100 — {verdict}
Files scanned: {files_scanned}
Pattern matches: {critical} critical, {high} high, {medium} medium, {low} low

If SAFE (0–20): "No suspicious patterns detected." If CAUTION+: list top 3 findings by severity.

Ask next step via AskUserQuestion:

SAFE: Deep scan / Done
CAUTION+: Deep scan (recommended) / Show findings / Done

Done → Phase 4 with quick-scan results only. Show findings → print all findings by severity, then stop.

Phase 3 — Deep analysis (parallel)

Read templates from ${CLAUDE_SKILL_DIR}/templates/:

Mode	Template(s)	Agent(s) to launch
skill	`agent-skill-audit.md`	1 skill audit agent
mcp	`agent-mcp-audit.md`	1 MCP audit agent
hooks	`agent-hooks-audit.md`	1 hooks audit agent
claudemd	`agent-claudemd-audit.md`	1 CLAUDE.md audit agent
all	all four	up to 4 agents in parallel

Launch all agents in a single message with parallel Agent calls. Each agent receives: its template instructions + relevant quick-scan JSON + inventory/config JSON + target path. Use "model": "sonnet" and a descriptive description per agent.

Wait for completion. Merge findings, sort by severity (Critical > High > Medium > Low > Info). Note any failed/timed-out agents in the report but continue.

Phase 4 — Report & cleanup

Combined score: start with pattern-scan score, add weight for new deep findings, cap at 100.

Score	Verdict
0–20	SAFE — no significant concerns
21–40	CAUTION — minor concerns
41–60	SUSPICIOUS — manual review recommended
61–80	DANGEROUS — do NOT install without expert review
81–100	MALICIOUS — avoid

Build the report using ${CLAUDE_SKILL_DIR}/templates/report.md. Sections: header (target, date, mode, score, verdict), scope audited, critical/high findings in full, medium/low and info in <details> blocks, clean signals, recommendations.

If DANGEROUS or MALICIOUS, prepend:

WARNING: This audit found serious security concerns. Do NOT install or use this without careful manual review.

Include the original GitHub URL or npm package name in the header if the target was remote.

Cleanup: if is_temporary was true, rm -rf "<temp_root>".

Rules

Never auto-remediate — report only, never modify files.
Never fabricate — only report what's observed.
Quick scan always first, even if deep scan will follow.
Parallel agents when multiple surfaces are in scope — never sequential.
Sonnet for sub-agents. Critical > Info ordering in findings.
Scope discipline — auditing a skill does not scan the whole filesystem.
Respect the user — if they say Done, stop; don't push deep analysis.
Context matters — a deployment skill needing Bash is normal; a text-formatting skill needing Bash is suspicious. Assess purpose vs. permissions.