DynamiQ: Unlocking the Potential of Dynamic Task Allocation in Parallel Fuzzing
October 06, 2025 Β· Declared Dead Β· π 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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