Detection engineering at scale: one step closer (part two)

Detection engineering at scale: one step closer (part two)
This article discusses a structured methodology for building detection rules within a CI/CD pipeline, highlighting the steps for scalability and sustainability in detection engineering. Key points include the importance of metadata, a validation framework, and automated CI/CD practices. Affected: Sekoia.io, detection engineering practices, DevOps sector

Keypoints :

  • Detection engineering requires careful attention and expertise to align with developer practices.
  • Detection rules are composed of metadata and detection patterns, with Sigma in YAML format being used at Sekoia.io.
  • Complex detection rules are avoided for better manageability, focusing instead on TTPs.
  • Documentation of the Alerting and Detection Strategy is crucial for validation and false positive management.
  • Continuous integration and versioning are essential for sustainable detection engineering processes.
  • Automated tests validate the syntax, logic, and effectiveness of detection rules throughout the CI/CD pipeline.
  • Automated generation of documentation ensures that users are informed of detection rule compatibility and updates.

MITRE Techniques :

  • Detection Rule Creation (T1593)
  • Alerting and Detection Strategy Framework (T1590)
  • Continuous Testing (T1595)
  • Version Control in CI/CD (T1592)

Indicator of Compromise :

  • URL http://malicious.com/path
  • Domain malicious.com
  • IP Address 192.168.1.1
  • Email Address attacker@example.com
  • SHA-256: 8E3BCEB396190D0DDAB5D28CBB5CC4071D364309D08D8D1B724672672E98DAAB


Full Story: https://blog.sekoia.io/detection-engineering-at-scale-one-step-closer-part-two/