Detection Engineering

Detection engineering is the discipline of systematically building, validating, and maintaining detection logic that catches real threats while minimizing noise. We approach it as an engineering problem — not a configuration task — with repeatable processes and measurable outcomes.

Engagements start with a coverage assessment: mapping your existing detections against MITRE ATT&CK to identify gaps, redundancies, and over-tuned rules generating alert fatigue. This baseline informs a prioritized detection roadmap aligned to the threat landscape most relevant to your sector and environment.

Detection writing spans SIEM, EDR, and cloud-native platforms — Splunk, Microsoft Sentinel, Elasticsearch, CrowdStrike, and others. Each rule is documented with a clear rationale, expected triggering conditions, tuning guidance, and a mapped MITRE ATT&CK technique. Rules are not delivered as black boxes; your analysts understand what fires and why.

Purple team exercises validate that detections work under realistic adversary conditions before they reach production. We coordinate with offensive teams or use adversary simulation tooling to test each detection against actual TTPs — closing the loop between "rule written" and "rule proven."

For organizations with heterogeneous environments, we build data normalization layers that unify telemetry from multiple products into a consistent schema. This makes detection logic portable, reduces per-platform maintenance overhead, and enables cross-source correlation that siloed platforms miss entirely.