Model2Kernel: Model-Aware Symbolic Execution For Safe CUDA Kernels

ArXi:2603.24595v1 Announce Type: cross The widespread adoption of large language models (LLMs) has made GPU-accelerated inference a critical part of modern computing infrastructure. Production inference systems rely on CUDA kernels to implement core transformer operations, yet these kernels are highly susceptible to memory-safety bugs due to model-dependent tensor layouts, intricate memory indexing, and massive thread-level parallelism. Such bugs can corrupt model weights, crash inference services, or even enable adversarial attacks.