Foundations of Large Language Models in Software Vulnerability Detection

Abstract

This chapter explores the foundational aspects of large language models (LLMs) and their application in detecting software vulnerabilities. As the complexity of software systems grows, traditional methods of vulnerability detection are often insufficient. LLMs, with their advanced natural language processing capabilities, provide a novel approach to identifying potential security threats in codebases. The chapter delves into the architecture of these models, their training mechanisms, and the challenges they face in the domain of cybersecurity. Additionally, it discusses the ethical implications and future directions for integrating LLMs in automated software vulnerability detection.

Topics & Concepts