DynamiQ: Unlocking the Potential of Dynamic Task Allocation in Parallel Fuzzing

October 06, 2025 Β· Declared Dead Β· πŸ› arXiv.org

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Authors Wenqi Yan, Toby Murray, Benjamin I. P. Rubinstein, Van-Thuan Pham arXiv ID 2510.04469 Category cs.SE: Software Engineering Citations 0 Venue arXiv.org Last Checked 5 months ago
Abstract
We present DynamiQ, a full-fledged and optimized successor to AFLTeam that supports dynamic and adaptive parallel fuzzing. Unlike most existing approaches that treat individual seeds as tasks, DynamiQ leverages structural information from the program's call graph to define tasks and continuously refines task allocation using runtime feedback. This design significantly reduces redundant exploration and enhances fuzzing efficiency at scale. Built on top of the state-of-the-art LibAFL framework, DynamiQ incorporates several practical optimizations in both task allocation and task-aware fuzzing. Evaluated on 12 real-world targets from OSS-Fuzz and FuzzBench over 25,000 CPU hours, DynamiQ outperforms state-of-the-art parallel fuzzers in both code coverage and vulnerability discovery, uncovering 9 previously unknown bugs in widely used and extensively fuzzed open-source software.
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