AI for detection content
David Naylor publicly advocated using AI inside detection pipelines for creating, tuning and decommissioning SIEM detection content rather than limiting AI to a single step. (x.com) His posts frame AI as useful across the lifecycle of rules in SOC workflows — creation, operational tuning, and eventual retirement. (x.com)
Security teams use Security Information and Event Management rules like tripwires: they watch logs, match patterns, and fire alerts when something looks malicious. David Naylor argued that artificial intelligence should help across that full rule lifecycle, not just at the moment a rule is first written. (x.com) In a public X post tied to video ID 2043410761683227007, Naylor said teams should use artificial intelligence to create detection content, tune it after it goes live, and decommission it when it no longer earns its keep. The post framed detection work as an ongoing pipeline inside the Security Operations Center, not a one-time drafting task. (x.com) Detection engineering already works that way in mature programs. Ridgeline Cyber Defence describes the job as a full lifecycle from hypothesis to retirement, and Blackcell’s 2025 white paper says detection engineering includes design, continuous refinement, and integration into operations workflows. (training.ridgelinecyber.com) (blackcell.io) That matters because Security Information and Event Management rules decay. New software, new log formats, and new attacker behavior can turn a once-useful alert into a noisy false positive or a blind spot, and vendors now pitch artificial intelligence as a way to migrate, validate, and tune rules faster. (elastic.co) (cymulate.com) Large vendors have spent the past year pushing that broader story. Elastic said artificial intelligence can convert legacy detection content during Security Information and Event Management migrations, while Microsoft’s February 11, 2026 buyer’s guide said artificial intelligence-ready platforms can accelerate detection and response inside modern Security Operations Centers. (elastic.co) (microsoft.com) Smaller specialists are making the same pitch with more explicit workflow language. Starseer says its platform covers five stages from “the first rule sketch to retirement,” and SIEM Rules says it turns threat intelligence into “highly-tuned detection rules.” (starseer.ai) (siemrules.com) The caution from practitioners is that artificial intelligence does not remove the need for testing. Detection content still has to be checked against real telemetry, measured for false positives, and retired when it duplicates other coverage or stops matching current attacker behavior. (cymulate.com) (training.ridgelinecyber.com) Naylor’s point lands in that gap between marketing and operations. The argument was not that artificial intelligence replaces detection engineers; it was that the same tools can be used to write, tune, and eventually remove rules, which is where most Security Operations Center maintenance work actually sits. (x.com) (training.ridgelinecyber.com)
