Detection Engineering is the discipline of creating, testing, and maintaining detection rules that identify threats. It's not enough to have a SIEM - you need rules that actually catch attacks while minimizing false positives. Good detection engineering is both art and science.
Think of detection engineering like setting up a home security system. You don't just install sensors everywhere - you strategically place them where intruders are likely to pass, tune sensitivity so your cat doesn't trigger alarms, and test that they actually work before you need them.
The Detection Gap
Most organizations have detection gaps - attack techniques with no rules to catch them. Detection engineering systematically closes these gaps by mapping coverage to frameworks like MITRE ATT&CK.
Sigma - Universal Detection Language
SigmaHQ Repository
The SigmaHQ repository (github.com/SigmaHQ/sigma) contains thousands of community-contributed detection rules. Start here before writing your own - someone may have already solved your problem!
Detection Rule Design
Writing Effective Rules
Testing Detection Rules
Test in Lab, Not Production
Always test attack simulations in isolated lab environments. Running Atomic Red Team in production can trigger EDR responses and create confusion. Use dedicated testing infrastructure.
Detection Coverage
Rule Tuning
Detection Lifecycle
Detection Engineering Methodology
Creating a Detection Rule
1
ResearchStudy the attack technique and its artifacts
2
Identify DataDetermine which logs capture the activity
3
Write RuleCreate Sigma rule with clear logic
4
TestValidate using attack simulation tools
5
DeployConvert and deploy to production SIEM
6
MonitorTrack alerts and false positive rate
7
TuneRefine based on real-world feedback
Knowledge Check
Challenges
Key Takeaways
- Sigma is the universal language for detection rules
- Good rules balance precision (catch attacks) with low false positives
- Test rules with Atomic Red Team before deploying to production
- Map coverage to MITRE ATT&CK to identify gaps
- Tuning is continuous - monitor and refine based on real alerts
- Document exceptions and reasons for tuning decisions