pipeline
$
npx mdskill add H-mmer/pentest-agents/pipelinePrepare the battlefield for: $ARGUMENTS
SKILL.md
.github/skills/pipelineView on GitHub ↗
--- name: pipeline description: "Prepare the battlefield — recon, scanning, and surface ranking. Stops before hunting. Run /hunt or /autopilot after. Usage: /pipeline or /pipeline <target>" disable-model-invocation: false --- Prepare the battlefield for: $ARGUMENTS This command runs recon, scanning, and surface ranking — everything needed BEFORE hunting. It does NOT hunt, validate, or report. Use `/hunt` or `/autopilot` for that. ## Phase 0: SETUP 1. Read `scope.yaml` — resolve and verify targets - If `$ARGUMENTS` is empty: `uv run python3 $CLAUDE_PROJECT_DIR/tools/scope_check.py --list` - If `$ARGUMENTS` is a domain: `uv run python3 $CLAUDE_PROJECT_DIR/tools/scope_check.py $ARGUMENTS` 2. Read `policy.md` — extract policy preamble for all agent dispatches 3. Brain init or brief: - If no brain exists: `uv run python3 $CLAUDE_PROJECT_DIR/tools/brain.py init` - If brain exists: `uv run python3 $CLAUDE_PROJECT_DIR/tools/brain.py brief <target>` ## Phase 1: RECON 4. Dispatch `recon` agent (model: inherit) with policy preamble and scope 5. After recon: dispatch `config-auditor` agent (model: inherit) for header/TLS/cookie review 6. After config: dispatch `js-analyzer` agent (model: inherit) for JavaScript analysis 7. Brain update: `uv run python3 $CLAUDE_PROJECT_DIR/tools/brain.py record <target> recon "<results summary>"` ## Phase 2: SCANNING (parallel, max 3) 8. Dispatch in parallel (all model: inherit, all with policy preamble): - `vuln-scanner` agent with nuclei on discovered hosts - `waf-profiler` agent on primary targets 9. Brain update with scan results ## Phase 3: RANK 10. Dispatch `recon-ranker` agent (model: inherit) with recon data + brain knowledge 11. Output P1/P2/Kill list ## Complete ``` Battlefield ready. P1 targets: [list] P2 targets: [list] Kill list: [list] Next steps: /hunt <target> — manual hunting on a specific target /autopilot — autonomous hunting across all P1 targets /surface — re-rank surface with current brain knowledge ``` Sync brain: `uv run python3 $CLAUDE_PROJECT_DIR/tools/global_brain.py sync-from-local` ## Top-Tier Pipeline Standard The pipeline prepares a battlefield, not a folder of scan files. 1. Scope first: every generated target must be in-scope or tagged `out-of-scope` with reason. 2. Normalize assets into stable inventories: hosts, endpoints, JS files, APIs, auth flows, cloud buckets, repos, mobile packages, and third-party integrations. 3. Rank during collection. Do not wait until the end to identify crown jewels. 4. Preserve raw evidence and parsed summaries. A hunter should be able to replay the exact source of every target. 5. End with `P1`, `P2`, and `Kill` lists plus the best first vuln class for each P1. If no P1 exists, say why and recommend monitoring or a different program.