ktg-plugin-marketplace/plugins/llm-security/commands/audit.md

name	description	allowed-tools	model
security:audit	Full project security audit with OWASP LLM Top 10 assessment, scoring, and remediation plan	Read, Glob, Grep, Bash, Agent	sonnet

/security audit

Full security audit — 10 categories, OWASP LLM Top 10 aligned, A-F grade.

Step 1: Run Posture Scanner

Run the deterministic posture scanner first for instant category results:

node <this plugin's scanners/posture-scanner.mjs> [cwd]

Parse JSON output. Record: grade, risk score, all category statuses, all findings.

Step 2: Gather Context

1. Read CLAUDE.md for project name and type
2. Glob for: commands/*.md, agents/*.md, .mcp.json, **/.mcp.json, .claude-plugin/plugin.json
3. Determine: has skills/commands? has MCP servers?

Step 3: Skill Scan (if commands/agents found)

Spawn subagent_type: "llm-security:skill-scanner-agent", model: "sonnet":

Scan all commands/ and agents/ at [cwd]. Read: <plugin-root>/knowledge/skill-threat-patterns.md Return findings: file, issue, severity, OWASP ref.

Step 4: MCP Scan (if MCP servers found)

After skill scan, spawn subagent_type: "llm-security:mcp-scanner-agent", model: "sonnet":

Audit MCP configs at [cwd]. Read: <plugin-root>/knowledge/mcp-threat-patterns.md Return trust table and findings with severity.

Step 5: Generate Report

Merge posture scanner JSON + agent findings. Use the posture scanner's grade as the baseline. Recalculate risk_score = min(100, critical*25 + high*10 + medium*4 + low*1) including agent findings.

Output: Risk Dashboard, Executive Summary, 10 Category Sections (use scanner evidence + agent narrative), Summary Table, Action Items (IMMEDIATE → HIGH → MEDIUM).

Close with top 2-3 action items. If grade C or lower: suggest /security threat-model.