🎩 Top 5 Security and AI Reads - Week #16

Agentic automated cyber ranges, LLMs classifying CVEs, loss functions in deep learning, trajectory-based data poison detection, and RAG compiler fuzzing.

Welcome to the sixteenth instalment of the Stats and Bytes Top 5 Security and AI Reads weekly newsletter. We're kicking off with a grand approach to cyber range automation through agentic RAG systems, showing how LLMs can transform cybersecurity training environment generation. Next, we look at interesting research on whether LLMs can correctly identify CVEs and create CVSS vectors, showing their strengths with clear criteria while pointing out difficulties with subjective judgements. We then dive into a comprehensive 172-page survey of loss functions and metrics in deep learning—an invaluable reference for anyone training neural networks. Following that, we examine a clever technique for detecting poisoned training samples by analysing loss trajectories through spectral analysis, providing a novel defence against third-party data manipulation. We wrap up with an exploration of how RAG-based systems can be used for compiler fuzzing, successfully generating test cases that identified a…