From Investigation Failures to Reliable SOC Agents: Understanding and Improving LLM-Based Alert Triage
Security operations centers (SOCs) must triage large volumes of alerts, most of which are benign, while missed attacks can remain uninvestigated. Tool-using large language model (LLM) agents can retrieve evidence during triage, but it remains unclear how reasoning strategies determine what to gather and when an investigation is sufficient to close an alert. We study five representative approaches spanning single-pass tool use, iterative retrieval, sampled investigations, self-review, and explicit verification. To support this study, we build ALERT-BENCH, an interactive benchmark that replays enterprise telemetry through a live SIEM and requires each system to retrieve evidence. Across 1,2...
| Authors | Saimon Amanuel Tsegai, Alex Kantchelian, Danfeng et al. |
|---|---|
| Primary category | cs.CR |
| Published | 7 October 2026 |
| Last updated at source | 7 October 2026 |
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