Towards Agentic Investigation of Security Alerts
Security analysts are overwhelmed by the volume of alerts and the low context provided by many detection systems. Early-stage investigations typically require manual correlation across multiple log sources, a task that is usually time-consuming. In this paper, we present an experimental, agentic workflow that leverages large language models (LLMs) augmented with predefined queries and constrained tool access (structured SQL over Suricata logs and grep-based text search) to automate the first stages of alert investigation. The proposed workflow integrates queries to provide an overview of the available data, and LLM components that selects which queries to use based on the overview results...
| Authors | Even Eilertsen, Vasileios Mavroeidis, Gudmund Grov |
|---|---|
| Primary category | cs.CR |
| Published | 28 April 2026 |
| Last updated at source | 28 April 2026 |
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