5 papers
Mitigating Package Hallucinations in Large Language Models via Model Editing
Shuhan Liu, Yukai Zhao, Xing Hu +3
Large language models (LLMs) have demonstrated strong capabilities in software engineering tasks, such as code generation, library recommendation, and dependency configuration. How…
Exploiting LLM Agent Supply Chains via Payload-less Skills
Xinyu Liu, Yukai Zhao, Xing Hu +1
Autonomous agents powered by Large Language Models (LLMs) acquire external functionalities through third-party skills available in open marketplaces. Adopting these integrations br…
Triggering and Detecting Exploitable Library Vulnerability from the Client by Directed Greybox Fuzzing
Yukai Zhao, Menghan Wu, Xing Hu +3
Developers utilize third-party libraries to improve productivity, which also introduces potential security risks. Existing approaches generate tests for public functions to trigger…
HFuzzer: Testing Large Language Models for Package Hallucinations via Phrase-based Fuzzing
Yukai Zhao, Menghan Wu, Xing Hu +1
Large Language Models (LLMs) are widely used for code generation, but they face critical security risks when applied to practical production due to package hallucinations, in which…
Ensemble Fuzzing with Dynamic Resource Scheduling and Multidimensional Seed Evaluation
Yukai Zhao, Shaohua Wang, Jue Wang +2
Fuzzing is widely used for detecting bugs and vulnerabilities, with various techniques proposed to enhance its effectiveness. To combine the advantages of multiple technologies, re…