First Fuzzer for NVIDIA Isaac Sim Finds 11 Bugs in Four Months Where Baselines Found Zero Crashes

arXiv 2608.06088·medium signalXBlueskyLinkedInCopy link

IcFuzz (arXiv 2608.06088, Aug 6) is the first fuzzing approach targeting NVIDIA Isaac Sim, the GPU-accelerated robotics simulator underpinning much embodied-AI development. It uses LLM-based semantic stage segmentation to decompose simulation programs into structured stages capturing object semantics, applies multi-level mutation operators across hierarchical granularities, and schedules those operators with a multi-armed bandit. It achieves roughly 190-205% of baseline code coverage and averages 3.7 unique crashes over three rounds of 12-hour tests while baselines detect none, and has uncovered 11 bugs over about four months, 9 confirmed or fixed by developers.