Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation
Large Language Models have become powerful tools for programming. However, they often overlook essential security practices, producing code with vulnerabilities. Despite this risk, existing work offers limited guidance on steering LLMs toward secure code generation and lacks systematic analysis of how effectively LLMs...
Hao Yan, Swapneel Suhas Vaidya, Xiaokuan Zhang et al.
· ACM Transactions on Software... · 0 citations