3 citations · 4 across the 5 of their papers we have counts for
6 papers
No, Your Tools Are Not Enough: It's Time to Bring Agents to the Hunt
Ati Priya Bajaj, Xiang Mei, Tiffany Bao +3
Modern software systems are large and complex, demanding scalable and autonomous techniques for vulnerability discovery. Existing approaches still depend on human expertise for dom…
SeedSmith: LLM-Driven Seed Synthesis for Directed Fuzzing
Junmin Zhu, Siyu Liu, Jie Hu +7
Directed fuzzing steers fuzzers toward user-defined sink functions to identify vulnerabilities, but it frequently fails to trigger crashes even after long campaigns. We identify tw…
Root-Cause-Driven Automated Vulnerability Repair
Hulin Wang, Zion Leonahenahe Basque, Jie Hu +13
Recent LLM-based systems have made automated vulnerability repair increasingly practical, but two challenges remain. First, without strong signals about where a bug originates, rep…
Pushan: Trace-Free Deobfuscation of Virtualization-Obfuscated Binaries
Ashwin Sudhir, Zion Leonahenahe Basque, Wil Gibbs +9
In the ever-evolving battle against malware, binary obfuscation techniques are a formidable barrier to effective analysis by both human security analysts and automated systems. In…
BuildBench: Benchmarking LLM Agents on Compiling Real-World Open-Source Software
Zehua Zhang, Ati Priya Bajaj, Divij Handa +14
Automatically compiling open-source software (OSS) projects is a vital, labor-intensive, and complex task, which makes it a good challenge for LLM Agents. Existing methods rely on…
Exploring the Limits of ChatGPT in Software Security Applications
Fangzhou Wu, Qingzhao Zhang, Ati Priya Bajaj +4
Large language models (LLMs) have undergone rapid evolution and achieved remarkable results in recent times. OpenAI's ChatGPT, backed by GPT-3.5 or GPT-4, has gained instant popula…