Hybrid Taint-Guided Kernel Fuzzing with Selective State Propagation

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Abstract

We integrate static taint analysis with dynamic fuzzing to target high-impact kernel code paths. A pruning mechanism removes irrelevant taint propagation, while symbolic constraints are applied only to tainted regions to control overhead. Evaluated on 18 kernel subsystems, the hybrid fuzzer achieves 44% more taint-relevant path hits, identifying 13 bugs, including buffer overflows and pointer dereferences. Symbolic overhead remains limited (≤18%) through selective propagation. This hybrid design efficiently directs fuzzing toward semantically meaningful kernel logic, demonstrating a productive balance of taint tracking and dynamic mutation.

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