Kunpeng Zhang (Shenzhen International Graduate School, Tsinghua University), Xiaogang Zhu (Swinburne University of Technology), Xi Xiao (Shenzhen International Graduate School, Tsinghua University), Minhui Xue (CSIRO's Data61), Chao Zhang (Tsinghua University), Sheng Wen (Swinburne University of Technology)

Mutation-based fuzzing is popular and effective in discovering unseen code and exposing bugs. However, only a few studies have concentrated on quantifying the importance of input bytes, which refers to the degree to which a byte contributes to the discovery of new code. They often focus on obtaining the relationship between input bytes and path constraints, ignoring the fact that not all constraint-related bytes can discover new code. In this paper, we conduct Shapely analysis to understand the effect of byte positions on fuzzing performance, and find that some byte positions contribute more than others and this property often holds across seeds. Based on this observation, we propose a novel fuzzing solution, ShapFuzz, to guide byte selection and mutation. Specifically, ShapFuzz updates Shapley values (importance) of bytes when each input is tested during fuzzing with a low overhead, and utilizes contextual multi-armed bandit to trade off between mutating high Shapley value bytes and low-frequently chosen bytes. We implement a prototype of this solution based on AFL++, i.e., ShapFuzz. We evaluate ShapFuzz against ten state-of-the-art fuzzers, including five byte schedule-reinforced fuzzers and five commonly used fuzzers. Compared with byte schedule-reinforced fuzzers, ShapFuzz discovers more edges and exposes more bugs than the best baseline on three different sets of initial seeds. Compared with commonly used fuzzers, ShapFuzz exposes 20 more bugs than the best comparison fuzzer, and discovers 6 more CVEs than the best baseline on MAGMA. Furthermore, ShapFuzz discovers 11 new bugs on the latest versions of programs, and 3 of them are confirmed by vendors.

View More Papers

EnclaveFuzz: Finding Vulnerabilities in SGX Applications

Liheng Chen (Institute of Information Engineering, Chinese Academy of Sciences; School of Cyber Security, University of Chinese Academy of Sciences; Institute for Network Science and Cyberspace of Tsinghua University), Zheming Li (Institute for Network Science and Cyberspace of Tsinghua University), Zheyu Ma (Institute for Network Science and Cyberspace of Tsinghua University), Yuan Li (Tsinghua University),…

Read More

Security-Performance Tradeoff in DAG-based Proof-of-Work Blockchain Protocols

Shichen Wu (1. School of Cyber Science and Technology, Shandong University 2. Key Laboratory of Cryptologic Technology and Information Security, Ministry of Education), Puwen Wei (1. School of Cyber Science and Technology, Shandong University 2. Quancheng Laboratory 3. Key Laboratory of Cryptologic Technology and Information Security, Ministry of Education), Ren Zhang (Cryptape Co. Ltd. and…

Read More

GhostType: The Limits of Using Contactless Electromagnetic Interference to...

Qinhong Jiang (Zhejiang University), Yanze Ren (Zhejiang University), Yan Long (University of Michigan), Chen Yan (Zhejiang University), Yumai Sun (University of Michigan), Xiaoyu Ji (Zhejiang University), Kevin Fu (Northeastern University), Wenyuan Xu (Zhejiang University)

Read More

AAKA: An Anti-Tracking Cellular Authentication Scheme Leveraging Anonymous Credentials

Hexuan Yu (Virginia Polytechnic Institute and State University), Changlai Du (Virginia Polytechnic Institute and State University), Yang Xiao (University of Kentucky), Angelos Keromytis (Georgia Institute of Technology), Chonggang Wang (InterDigital), Robert Gazda (InterDigital), Y. Thomas Hou (Virginia Polytechnic Institute and State University), Wenjing Lou (Virginia Polytechnic Institute and State University)

Read More