Detection-as-Code

Detection-as-Code (DaC) treats detection logic — SIEM queries, Sigma rules, YARA signatures — as source code managed in version control systems like Git. Rather than writing rules manually through a GUI, engineers author, test, and deploy detection logic through the same workflows used for application development: pull requests, automated testing, and deployment pipelines.

Ad-hoc detection rule management leads to undocumented changes, regression bugs, and rules that degrade over time without anyone noticing. Detection-as-Code brings accountability and reproducibility: every rule change is tracked, tested against known-good and known-bad samples before deployment, and can be rolled back if it causes noise or misses. It also enables scaling detection engineering across large environments without losing control of rule quality.

Engineers write detection rules in a portable format such as Sigma (for log-based detections) or YARA (for file and memory signatures). Rules are committed to a repository where CI/CD pipelines run automated tests — validating syntax, checking for logic errors, and replaying against historical event samples. On merge, rules are compiled and pushed to target platforms such as a SIEM or EDR. The same pipeline can enforce naming conventions, MITRE ATT&CK tagging, and documentation requirements.