Enhanced Grey Box Fuzzing For Intel Media Driver
Linlin Zhang, Ning Luo

TL;DR
This paper presents MediaFuzzer, an intelligent grey box fuzzing approach for the Intel Media driver that selectively targets input fields, significantly increasing vulnerability detection and fuzzing efficiency with minimal overhead.
Contribution
Introduction of MediaFuzzer, a novel grey box fuzzing method that focuses on selective input fields and employs a depth-based power schedule to improve vulnerability discovery.
Findings
Exposes approximately 6.6 times more issues than AFL.
Achieves about 2.7 times higher fuzzing efficiency.
Maintains negligible overhead compared to baseline AFL.
Abstract
Grey box fuzzing is one of the most successful methods for automatic vulnerability detection. However,conventional Grey box Fuzzers like AFL can open perform fuzzing against the whole input and spend more time on smaller seeds with lower execution time, which significantly impact fuzzing efficiency for complicated input types. In this work, we introduce one intelligent grey box fuzzing for Intel Media driver, MediaFuzzer, which can perform effective fuzzing based on selective fields of complicated input. Also, with one novel calling depth-based power schedule biased toward seed corpus which can lead to deeper calling chain, it dramatically improves the vulnerability exposures (~6.6 times more issues exposed) and fuzzing efficiency (~2.7 times more efficient) against the baseline AFL for Intel media driver with almost negligible overhead.
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Taxonomy
TopicsSoftware Testing and Debugging Techniques · Advanced Neural Network Applications · Advanced Malware Detection Techniques
