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Tue 11 Oct 2022 14:00 - 14:20 at Banquet B - Technical Session 7 - Fuzzing II Chair(s): Karine Even-Mendoza

Fuzz testing ("fuzzing'') is a widely-used and effective dynamic technique to discover crashes and security vulnerabilities in software, supported by numerous tools, which keep improving in terms of their detection capabilities and speed of execution. In this paper, we report our findings from using state-of-the-art mutation-based and hybrid fuzzers (AFL, Angora, honggfuzz, Intriguer, MOpt-AFL, QSym, and SymCC) on a non-trivial code base, that of Contiki-NG, to expose and fix serious vulnerabilities in various layers of its network stack, during a period of more than three years. As a by-product, we provide a Git-based platform which allowed us to create and apply a new, quite challenging, open-source bug suite for evaluating fuzzers on real-world software vulnerabilities. Using this bug suite, we present an impartial and extensive evaluation of the effectiveness of these fuzzers, and measure the impact that sanitizers have on it. Finally, we offer our experiences and opinions on how fuzzing tools should be used and evaluated in the future.

Tue 11 Oct

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14:00 - 15:30
Technical Session 7 - Fuzzing IIResearch Papers at Banquet B
Chair(s): Karine Even-Mendoza Imperial College London
14:00
20m
Research paper
So Many Fuzzers, So Little Time - Experience from Evaluating Fuzzers on the Contiki-NG Network (Hay)StackVirtual
Research Papers
Clement Poncelet Uppsala University, Konstantinos (Kostis) Sagonas Uppsala University and Nat. Tech. Univ. of Athens, Nicolas Tsiftes RISE Research Institutes of Sweden
DOI Pre-print
14:20
20m
Research paper
FuzzerAid: Grouping Fuzzed Crashes Based On Fault Signatures
Research Papers
Ashwin Kallingal Joshy Iowa State University, Wei Le Iowa State University
14:40
20m
Research paper
QATest: A Uniform Fuzzing Framework for Question Answering SystemsVirtualACM SIGSOFT Distinguished Paper Award
Research Papers
Zixi Liu Nanjing University, Yang Feng Nanjing University, Yining Yin Nanjing University, China, Jingyu Sun Nanjing University, Zhenyu Chen Nanjing University, Baowen Xu Nanjing University
15:00
20m
Research paper
Effectively Generating Vulnerable Transaction Sequences in Smart Contracts with Reinforcement Learning-guided FuzzingVirtual
Research Papers
Jianzhong Su Sun Yat-sen University, Hong-Ning Dai Hong Kong Baptist University, Lingjun Zhao Sun Yat-sen University, Zibin Zheng School of Data and Computer Science, Sun Yat-sen University, Xiapu Luo Hong Kong Polytechnic University