An Empirical Evaluation of LLM-Generated Code Security Across Prompting Methods 事件

An Empirical Evaluation of LLM-Generated Code Security Across Prompting Methods arXiv:2605.24298v1 Announce Type: cross Abstract: The growing use of Large Language Models (LLMs) for automated code generation has enhanced software development efficiency, but often at the cost of security. Generated code frequently overlooks critical concerns, leaving it vulnerable to issues such as weak encryption and improper input validation. To investigate this problem, we present a comprehensive empirical ev