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Research Papers
Tue 11 Oct 2022 14:00 - 14:20 at Banquet B - Technical Session 7 - Fuzzing II Chair(s): Karine Even-MendozaFuzz 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.
DOI Pre-print
We present a public GitHub repository containing the artifact for our ASE’2022 paper “So Many Fuzzers, So Little Time - Experience from Evaluating Fuzzers on the Contiki-NG Network (Hay)Stack”. Our paper contains detailed experiments and experiences from using eight mutation-based and hybrid fuzzers on different Git history points of the code base of Contiki-NG, an Operating System for next generation IoT devices. Our artifact contains the raw data that we have used to create the tables of our paper, and an extensible framework (Dockerfiles and scripts) to reproduce and launch fuzzing campaigns with the paper’s configurations.
DOI