Augmenting threat intelligence: A framework for integrating LLMs, AI Agents, and RAG in cybersecurity analysis

This comprehensive framework for integrating advanced artificial intelligence technologies into threat intelligence workflows addresses the increasing volume and complexity of cybersecurity data. The strategic deployment of Large Language Models (LLMs), AI agents, and Retrieval-Augmented Generation (RAG) across the threat intelligence lifecycle—from data collection and processing to analysis and dissemination—demonstrates significant potential for automating routine tasks, enhancing analytical capabilities, extracting actionable insights from vast datasets, and improving the timeliness of intelligence reporting. Through detailed examination of implementation strategies and technical considerations, the transformative impact on traditional threat intelligence practices becomes evident while complementing human analyst expertise. The practical methodologies presented enable security teams to leverage generative AI in identifying and responding to emerging threats more effectively.