In this episode we talk about the different ways companies are using AI, and specially LLMs, to improve their cybersecurity processes. We will talk about information gathering, protection, detection and response and what are known applications of AI in each of these areas.

During this episode I mention multiple references that I'm sharing here:

IntelEX: A LLM-driven Attack-level Threat Intelligence Extraction Framework https://arxiv.org/abs/2412.10872 

Comparison of Static Application Security Testing Tools and Large Language Models for Repo-level Vulnerability Detection https://arxiv.org/abs/2407.16235 

Leveling Up Fuzzing: Finding more vulnerabilities with AI https://security.googleblog.com/2024/11/leveling-up-fuzzing-finding-more.html 

RedFlag https://github.com/Addepar/RedFlag

LLMSecConfig: An LLM-Based Approach for Fixing Software Container Misconfigurations https://arxiv.org/abs/2502.02009

AI and LLM Models to Analyze and Identify Сybersecurity Incidents https://ceur-ws.org/Vol-3746/Short_6.pdf

GenDFIR: Advancing Cyber Incident Timeline Analysis Through Retrieval Augmented Generation and Large Language Models https://arxiv.org/abs/2409.02572