SynRAG: A Large Language Model Framework for Executable Query Generation in Heterogeneous SIEM System

📝 Original Info

• Title: SynRAG: A Large Language Model Framework for Executable Query Generation in Heterogeneous SIEM System
• ArXiv ID: 2512.24571
• Date: 2025-12-31
• Authors: Md Hasan Saju, Austin Page, Akramul Azim, Jeff Gardiner, Farzaneh Abazari, Frank Eargle

📝 Abstract

Security Information and Event Management (SIEM) systems are essential for large enterprises to monitor their IT infrastructure by ingesting and analyzing millions of logs and events daily. Security Operations Center (SOC) analysts are tasked with monitoring and analyzing this vast data to identify potential threats and take preventive actions to protect enterprise assets. However, the diversity among SIEM platforms, such as Palo Alto Networks Qradar, Google SecOps, Splunk, Microsoft Sentinel and the Elastic Stack, poses significant challenges. As these systems differ in attributes, architecture, and query languages, making it difficult for analysts to effectively monitor multiple platforms without undergoing extensive training or forcing enterprises to expand their workforce. To address this issue, we introduce SynRAG, a unified framework that automatically generates threat detection or incident investigation queries for multiple SIEM platforms from a platform-agnostic specification. SynRAG can generate platformspecific queries from a single high-level specification written by analysts. Without SynRAG, analysts would need to manually write separate queries for eac...

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