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cs.CR2025
Understanding Gaps in LLM Pipelines Towards Scalable Fuzzing Harness Generation: An Empirical Study and Enhancement
Kang Yang, Yunhang Zhang, Zichuan Li +3
Large language model (LLM)-based techniques have achieved notable progress in fuzz harness generation. However, applying them to arbitrary functions \textit{at scale} remains diffi…
cs.CR2024
Harnessing Large Language Models for Seed Generation in Greybox Fuzzing
Wenxuan Shi, Yunhang Zhang, Xinyu Xing +1
Greybox fuzzing has emerged as a preferred technique for discovering software bugs, striking a balance between efficiency and depth of exploration. While research has focused on im…