5 papers
FuzzAgent: Multi-Agent System for Evolutionary Library Fuzzing
Yunlong Lyu, Peng Chen, Fengyi Wu +3
Library fuzzing is essential for hardening the software supply chain, but adopting it at scale remains expensive. Practitioners still spend substantial effort on environment setup,…
"Tab, Tab, Bug": Security Pitfalls of Next Edit Suggestions in AI-Integrated IDEs
Yunlong Lyu, Yixuan Tang, Peng Chen +4
Modern AI-integrated IDEs are shifting from passive code completion to proactive Next Edit Suggestions (NES). Unlike traditional autocompletion, NES is designed to construct a rich…
Security of AI Agents
Yifeng He, Ethan Wang, Yuyang Rong +2
AI agents have been boosted by large language models. AI agents can function as intelligent assistants and complete tasks on behalf of their users with access to tools and the abil…
FuzzAug: Data Augmentation by Coverage-guided Fuzzing for Neural Test Generation
Yifeng He, Jicheng Wang, Yuyang Rong +1
Testing is essential to modern software engineering for building reliable software. Given the high costs of manually creating test cases, automated test case generation, particular…
LLAMAFUZZ: Large Language Model Enhanced Greybox Fuzzing
Hongxiang Zhang, Yuyang Rong, Yifeng He +1
Greybox fuzzing has achieved success in revealing bugs and vulnerabilities in programs. However, randomized mutation strategies have limited the fuzzer's performance on structured…