AdaRare Adaptive Fuzzing

Arxiv pdf 2026-08-01T00:00:00
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Abstract

Greybox fuzzers combine interacting queue, mutation, dictionary, energy, and comparison-solving control surfaces, while prior adaptive systems typically optimize other decision objects or control layers. We present AdaRare, an AFL++ extension that coordinates five internal actuation mechanisms as one bounded in-process profile updated every 5,000 ms. Completed-window, action-induced telemetry feeds an arm-local recency-weighted linear scorer and a profile-conditioned controller target. The scorer borrows the algebraic structure of disjoint LinUCB, but serves as a closed-loop profile-ranking mechanism rather than a calibrated contextual-bandit action-value estimator or statistical confidence bound. Across three sequential repeated-trial phases, Main provides broad integrated-system evidence: AdaRare has higher median edge coverage than vanilla AFL++ on all eight targets, with five Holm-significant comparisons. In the strongest matched result, Full AdaRare has higher median edge coverage than CmpLog-matched AFL++ on all five follow-up targets, with four Holm-significant comparisons. Batch A finds higher medians for telemetryguided selection than fixed-context, random, and roundrobin schedules in all 15 targetcontrol comparisons, with 13 Holm-significant comparisons. The experiments do not establish independent No-A6-versus-Shadow or scarcitybundle effects; A6 evidence is target-dependent and weakens under batch-wide correction. In an unmatched firmware case study, AdaRare-generated inputs exposed five distinct memory-corruption findings, each reproduced in a separate environment and later assigned a CVE identifier. Controllerboundary compute P99 medians are below 6.5 ms for a five-second window; complete-boundary P99 medians including synchronous logging are below 14.7 ms. These measurements characterize boundary latency, not total system overhead.

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