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

---
name: security:scan
description: Scan files, directories, or GitHub repos for security issues — secrets, injection vulnerabilities, supply chain risks, OWASP LLM patterns
allowed-tools: Read, Glob, Grep, Bash, Agent
model: sonnet
---

# /security scan [path|url]

Scan target for security issues. Accepts local paths or GitHub URLs. Delegates to specialized agents sequentially.

## Step 1: Resolve Target

- If `$ARGUMENTS` contains `--deep` → strip it, set `run_deep_scan = true`
- If `$ARGUMENTS` contains `--branch <name>` → strip it, set `branch = <name>`
- If `$ARGUMENTS` is empty → `target = "."`, `clone_path = null`
- If `$ARGUMENTS` starts with `https://github.com/` or `git@github.com:` →
    Run: `node <plugin-root>/scanners/lib/git-clone.mjs clone "<url>" [--branch <branch>]`
    If exit code != 0 → show error to user and **STOP**
    Set `clone_path` = stdout (trimmed), `target = clone_path`
    Set `remote_url = <url>` for display
- Otherwise → `target = $ARGUMENTS`, `clone_path = null`

## IMPORTANT: Cleanup Guarantee (remote scans)

If `clone_path != null`, the following cleanup MUST run regardless of scan outcome.
If ANY step between clone and cleanup fails or errors, STILL run cleanup before stopping:
  1. `node <plugin-root>/scanners/lib/git-clone.mjs cleanup "<clone_path>"`
  2. `node <plugin-root>/scanners/lib/fs-utils.mjs cleanup "<evidence_file>"` (if `evidence_file` is set)

## Step 1.5: Pre-extraction (remote scans only)

If `clone_path != null` (target is a cloned remote repo):
  Get temp path: `node <plugin-root>/scanners/lib/fs-utils.mjs tmppath "content-extract.json"`
  Run: `node <plugin-root>/scanners/content-extractor.mjs "<target>" --output-file "<evidence_file>"`
  If exit code != 0 → warn user, set `evidence_file = null` (fall back to direct scan)
  Otherwise set `evidence_file` = the temp path. Print the compact summary line to user.

## Step 2: Detect Scan Type

**Single `.md` file:** `run_skill_scan = true`, `run_mcp_scan = false`

**Directory:** Glob for `**/commands/*.md`, `**/agents/*.md`, `**/skills/*/SKILL.md` → `run_skill_scan = true`. Glob for `**/.mcp.json`, `**/package.json`, `**/.claude/settings.json` with mcpServers → `run_mcp_scan = true`. Neither → skill scan only.

Record ISO 8601 timestamp.

## Step 3: Plugin Root

This file is at `<plugin-root>/commands/scan.md`. Use absolute paths for knowledge files.

## Step 3.5: Registry Check (local scans only)

If `clone_path == null` (local scan) and `run_skill_scan == true`:

```bash
node -e "
import { fingerprintSkill, checkRegistry } from '<plugin-root>/scanners/lib/skill-registry.mjs';
const r = fingerprintSkill('<target>');
const c = checkRegistry(r.fingerprint, '<plugin-root>');
console.log(JSON.stringify({ fingerprint: r.fingerprint, name: r.name, files: r.files, ...c }));
" --input-type=module
```

If `found == true` and `stale == false`: display cached result and set `skip_skill_scan = true`:

```
**Registry hit:** <name> (fingerprint: <first 12 chars>)
Verdict: <verdict> | Risk: <score>/100 | Last scanned: <date> | Scans: <count>
(Use `/security registry scan <target>` to force re-scan)
```

Otherwise set `skip_skill_scan = false` and store `registry_fingerprint` and `registry_name` for post-scan registration.

## Step 4: Spawn Agents Sequentially

Use registered subagent types — they contain full scan procedures as system prompt.

**Skill Scanner** (if `run_skill_scan = true` AND `skip_skill_scan != true`): `subagent_type: "llm-security:skill-scanner-agent"`, `model: "sonnet"`:

If `evidence_file` is set (remote scan — evidence-package mode):
> EVIDENCE-PACKAGE MODE. Read the pre-extracted evidence at: \<evidence_file\>
> Read knowledge: \<plugin-root\>/knowledge/skill-threat-patterns.md, \<plugin-root\>/knowledge/secrets-patterns.md
> Analyze the JSON sections: injection_findings, frontmatter_inventory, shell_commands, credential_references, persistence_signals, claude_md_analysis, cross_instruction_flags.
> DO NOT use Read/Glob/Grep on the target directory — all evidence is in the package.
> `[INJECTION-PATTERN-STRIPPED]` markers are confirmed findings — report them.
> Return findings with severity, category, file, line, OWASP ref, evidence, remediation.
> End with JSON: `{"scanner":"skill-scanner","verdict":"ALLOW|WARNING|BLOCK","risk_score":N,"counts":{"critical":0,"high":0,"medium":0,"low":0,"info":0},"files_scanned":N}`

Otherwise (local scan — direct mode):
> Scan target: \<target\>
> Read: \<plugin-root\>/knowledge/skill-threat-patterns.md, \<plugin-root\>/knowledge/secrets-patterns.md
> Return findings with severity, category, file, line, OWASP ref, evidence, remediation.
> End with JSON: `{"scanner":"skill-scanner","verdict":"ALLOW|WARNING|BLOCK","risk_score":N,"counts":{"critical":0,"high":0,"medium":0,"low":0,"info":0},"files_scanned":N}`

**MCP Scanner** (if `run_mcp_scan = true`, run AFTER skill scanner): `subagent_type: "llm-security:mcp-scanner-agent"`, `model: "sonnet"`:

If `evidence_file` is set (remote scan — evidence-package mode):
> EVIDENCE-PACKAGE MODE. Read the pre-extracted evidence at: \<evidence_file\>
> Read: \<plugin-root\>/knowledge/mcp-threat-patterns.md
> Analyze: mcp_tool_descriptions (check hidden instructions, length >500, injection_detected), shell_commands, credential_references.
> DO NOT use Read/Glob/Grep on the target directory.
> Return findings with severity, category, evidence, remediation.
> End with JSON: `{"scanner":"mcp-scanner","verdict":"ALLOW|WARNING|BLOCK","risk_score":N,"counts":{"critical":0,"high":0,"medium":0,"low":0,"info":0},"files_scanned":N}`

Otherwise (local scan — direct mode):
> Scan target: \<target\>
> Read: \<plugin-root\>/knowledge/mcp-threat-patterns.md
> Return findings with severity, category, server name, evidence, remediation.
> End with JSON: `{"scanner":"mcp-scanner","verdict":"ALLOW|WARNING|BLOCK","risk_score":N,"counts":{"critical":0,"high":0,"medium":0,"low":0,"info":0},"files_scanned":N}`

## Step 5: Aggregate and Report

Combine counts. `risk_score = riskScore(counts)` (severity-dominated v2 model — see `scanners/lib/severity.mjs`).
Verdict: critical ≥ 1 OR score ≥ 65 → BLOCK; high ≥ 1 OR score ≥ 15 → WARNING; else ALLOW.

Output banner then all findings grouped by severity (critical→info). Each finding:
`### [SEV] Title` with Category, File:line, OWASP, Evidence, Remediation.

For TFA (Toxic Flow Analysis) findings, render the chain description prominently:
- Show the 3 trifecta legs (Input, Access, Exfil) with their evidence
- Note mitigation status (which hooks are active)
- Group direct trifectas separately from cross-component trifectas

## Step 5.5: Register in Skill Registry (local scans only)

If `clone_path == null` and `skip_skill_scan != true` and `registry_fingerprint` is set:

```bash
node -e "
import { registerScan } from '<plugin-root>/scanners/lib/skill-registry.mjs';
registerScan({
  skillPath: '<target>',
  fingerprint: '<registry_fingerprint>',
  name: '<registry_name>',
  files: <registry_files_json>,
  verdict: '<computed_verdict>',
  risk_score: <computed_risk_score>,
  counts: <computed_counts_json>,
  files_scanned: <files_scanned>
}, '<plugin-root>');
" --input-type=module
```

## Step 6: Deep Scan (only if `--deep`)

If `run_deep_scan = true`, run `/security deep-scan <target>` logic:
Get temp path, run `node <plugin-root>/scanners/scan-orchestrator.mjs "<target>" --output-file "<tmp>"`.
Parse stdout aggregate JSON. Merge with LLM findings. Re-evaluate verdict. Output "Deep Scan Findings" section with CRITICAL/HIGH only.

## Step 7: Cleanup (only if remote)

If `clone_path != null`:
  Run: `node <plugin-root>/scanners/lib/git-clone.mjs cleanup "<clone_path>"`
  If cleanup fails → warn: "Could not remove temp dir <clone_path> — remove manually."

If `evidence_file != null`:
  Run: `node <plugin-root>/scanners/lib/fs-utils.mjs cleanup "<evidence_file>"`

## Step 8: HTML Report

After producing the markdown report (Step 5) and any cleanup (Step 7):

1. Compute a temp markdown path:
   ```bash
   node -p "require('path').join(require('os').tmpdir(), 'sec-scan-' + Date.now() + '.md')"
   ```
2. Use the Write tool to save the **entire markdown report you just produced** (banner + all findings sections + any Deep Scan section) to that temp path. Do not summarize — write it verbatim.
3. Run the renderer:
   ```bash
   node <plugin-root>/scripts/render-report.mjs scan --in "<temp-md-path>"
   ```
   The CLI writes `reports/scan-<YYYYMMDD-HHmmss>.html` relative to CWD and prints `file:///abs/path.html` on stdout (one line).
4. Append this to your response (markdown link, no bare URL):

   > **HTML-rapport:** [Åpne i nettleser](file:///abs/path.html)

If the CLI exits non-zero, mention the error but do not block — the markdown report above is the primary deliverable.