Large Language Models (LLMs) have revolutionized many industries by replacing the need to Google for answers. However, for cybersecurity workloads where current information is critical for accurate analysis, outdated LLM training data often results in hallucinations and incorrect answers. How can we build trust with LLMs for cyber security questions?

This blog explores why Retrieval-Augmented Generation (RAG) is essential to augment LLMs with current threat information. It overviews popular data retrieval techniques used by foundation model providers and why combining LLMs with RAG is the future of agentic cybersecurity analysis.