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

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