Not All Seeds Are Important: Fuzzing Guided by Untouched Edges
Xie Chen, Peng Jia, Pin Yang, Chi Hu, Hongbo Kuang, Genzuo Ye, Xuanquan Hong · Applied Sciences · 2023
Coverage-guided greybox fuzzing (CGF) has become the mainstream technology used in the field of vulnerability mining, which has been proven to be effective. Seed scheduling, the process of selecting seeds from the seeds pool for subsequent fuzzing iterations, is a critical component of CGF. While many seed scheduling strategies have been proposed in academia, they all focus on the explored regions within programs. In response to the inefficiencies of traditional seed scheduling strategies, which often allocate resources to ineffective seeds, we introduce a novel seed scheduling strategy guided by untouched edges. The strategy generates the optional seed set according to the information on the untouched edges. We also present a new instrumentation method to capture unexplored areas and guide the fuzzing process toward them. We implemented the prototype UntouchFuzz on top of American Fuzzy Lop (AFL) and conducted evaluation experiments against the most advanced seed scheduling strategies. Our results demonstrate that UntouchFuzz has improved in code coverage and unique vulnerabilities. Furthermore, the method proposed is transplanted into the fuzzer MOpt, which further proves the scalability of the method. In particular, 13 vulnerabilities were found in the open-source projects, with 7 of them having assigned CVEs.