4 papers
AFLGopher: Accelerating Directed Fuzzing via Feasibility-Aware Guidance
Weiheng Bai, Kefu Wu, Qiushi Wu +1
Directed fuzzing is a useful testing technique that aims to efficiently reach target code sites in a program. The core of directed fuzzing is the guiding mechanism that directs the…
One Bug, Hundreds Behind: LLMs for Large-Scale Bug Discovery
Qiushi Wu, Yue Xiao, Dhilung Kirat +3
Fixing bugs in large programs is a challenging task that demands substantial time and effort. Once a bug is found, it is reported to the project maintainers, who work with the repo…
What Do They Fix? LLM-Aided Categorization of Security Patches for Critical Memory Bugs
Xingyu Li, Juefei Pu, Yifan Wu +11
Open-source software projects are foundational to modern software ecosystems, with the Linux kernel standing out as a critical exemplar due to its ubiquity and complexity. Although…
APILOT: Navigating Large Language Models to Generate Secure Code by Sidestepping Outdated API Pitfalls
Weiheng Bai, Keyang Xuan, Pengxiang Huang +4
With the rapid development of large language models (LLMs), their applications have expanded into diverse fields, such as code assistance. However, the substantial size of LLMs mak…