JITterFlip: Uncovering Fault Attack Surfaces in JIT-Compiled LLM Serving
New research maps fault-injection attack surfaces in JIT-compiled LLM serving stacks, showing that host-side compilation artefacts can be tampered to compromise cloud-hosted inference integrity.
Summary written by editorial AI · Source link below
arXiv:2608.29745v1 Announce Type: new Abstract: LLMs are widely deployed through cloud-hosted inference services, where Just-in-Time (JIT) compilation is used to reduce recurring framework and GPU-launch overhead. JIT serving introduces a host-side control plane that selects compiled artifacts and orchestrates their execution on the GPU. Meanwhile, the shared cloud setting has motivated a growing body of bit-flip attacks (BFAs) against LLM/DNN inference. Most existing BFAs target model paramete
Editorial Analysis
Organisations hosting LLM inference on shared cloud GPU infrastructure should consider that JIT compilation introduces a previously overlooked tampering vector.
Audit integrity controls around JIT-compiled artefacts in GPU inference pipelines.
Forward-looking interpretation drafted by editorial AI under human review — not a reproduction of the source. See methodology.
External link — opens at arXiv Crypto & Security in a new tab.
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