Volume 11, Number 2

Enhanced Fuzzing System for Proactive Security Gap Exposure

  Authors

Linlin Zhang and Ning Luo, Visual Computing Group, Intel Asia-Pacific Research & Development Ltd, China

  Abstract

Lots of safety vulnerabilities have been harming software and hardware. Grey box fuzzer is one of the most successful methods for automatic vulnerability detection. Most research focus on using fuzzer for SW quality check only. This paper introduced how to leverage fuzzer to exposure security gap as early as possible. 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 issuesexposed) and fuzzing efficiency (~2.7 times more efficient) against the baseline AFL for Intel media driver with almost negligible overhead.

  Keywords

Vulnerability detection, automated testing, fuzzing, Grey box fuzzer, security.