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Search: “alert-triage”

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Inside Elastic's agentic SOC: How we took AI alert triage from 60% to 92% accuracy

Elastic's InfoSec team raised AI alert-triage accuracy from 60% to 92% using three self-correcting agents integrated into Slack triage.

Elastic's InfoSec team deployed three AI agents that read detection-rule investigation guides and closure reasons from 30 days of historical cases to triage alerts. The agentic pipeline lifted triage accuracy from 60% to 92%. Analysts now clear most alerts with a single click in Slack.

Elastic Security Labs · 21d agoTools

What researchers learned about building an LLM security workflow

Oslo and FFI researchers show structured agentic workflows lift LLM alert-triage accuracy from 0% to about 93% on malicious cases.

Researchers at the University of Oslo and the Norwegian Defence Research Establishment tested GPT-5-mini, Claude 3 Haiku, Qwen3:30B, and Gemma 3:27B on alerts from the AIT Log Data Set V1.1; given only alert descriptions and log summaries, all four models correctly flagged zero percent of true-positive cases involving reconnaissance, brute-force logins, and initial access. Wrapping the same models in a workflow with constrained SQL queries over Suricata logs, an evidence summarizer, and a verdict stage with revision loops raised malicious-case accuracy to an average of 93 percent, with GPT-5-mini identifying every malicious case across 100 runs. The authors flag it as a proof-of-concept on one synthetic scenario and note models skewed conservative on benign alerts, with GPT-5-mini marking every benign case uncertain.

Help Net Security · 22d agoAI research1