AdaRare: Telemetry-Guided Joint Profile Control for Greybox Fuzzing

📅 2026-08-18
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🤖 AI Summary
AdaRare通过协调五个内部机制并利用遥测数据指导灰盒模糊测试,提高了AFL++的边缘覆盖率和内存错误检测能力。
📝 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 telemetry-guided selection than fixed-context, random, and round-robin schedules in all 15 target-control comparisons, with 13 Holm-significant comparisons. The experiments do not establish independent No-A6-versus-Shadow or scarcity-bundle 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. Controller-boundary 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.
Problem

Research questions and friction points this paper is trying to address.

greybox fuzzing
profile control
telemetry-guided
Innovation

Methods, ideas, or system contributions that make the work stand out.

telemetry-guided
joint profile control
recency-weighted linear scorer
closed-loop profile-ranking
greybox fuzzing
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