AI RESEARCH
Retrieval-Augmented LLMs for Security Incident Analysis
arXiv CS.AI
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ArXi:2603.18196v1 Announce Type: cross Investigating cybersecurity incidents requires collecting and analyzing evidence from multiple log sources, including intrusion detection alerts, network traffic records, and authentication events. This process is labor-intensive: analysts must sift through large volumes of data to identify relevant indicators and piece together what happened. We present a RAG-based system that performs security incident analysis through targeted query-based filtering and LLM semantic reasoning.