SuperAPI AI Directory

detection-engineering

Testing & quality

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Updated 10-16 00:06

About this skill

Detection Engineering

Operating Rules

  • Start from a threat behavior, not a single IOC. Rules expire; behaviors persist.
  • Every rule ships with: hypothesis, data source, ATT&CK mapping, false-positive notes, response action, and a test.
  • Tune for analyst time, not raw event volume. A noisy critical is a broken critical.

Authoring Workflow

  1. State hypothesis: actor, technique, observable, data source, confidence.
  2. Identify telemetry: process, file, registry, network, auth, cloud, email, identity, EDR fields.
  3. Draft rule in the platform's native DSL; keep selectors readable; comment non-obvious filters.
  4. Generate matched and unmatched test events; run in a dry-run pipeline.
  5. Validate with Atomic Red Team / Caldera tests; record true positive evidence.
  6. Tune: add allow-lists with reasons and review dates; never silently broaden.
  7. Ship with a runbook: triage steps, expected next queries, containment.

Coverage Strategy

  • Maintain a matrix of ATT&CK techniques × data sources × rule IDs × last-tested date.
  • Track gaps as backlog items with prerequisite telemetry (e.g., enable Sysmon 1/3/10/11).
  • Score detections on durability, fidelity, and response cost.

Output Contract

  • rules/<platform>/<id>.yml with metadata block.
  • tests/<id>/ with positive and negative pcaps, EVTX, or JSON.
  • coverage.csv: ATT&CK × rule × status × last_validated.
  • runbooks/<id>.md: analyst playbook.
  • release-notes.md: what changed, why, expected volume delta.