CVE-2026-53923

CVE-2026-53923 · vLLM GGUF Kernels: int64_t to int truncation of tensor dimensions causes GPU buffer overflow

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vLLM is an inference and serving engine for large language models (LLMs). From 0.5.5 until 0.23.1rc0, integer truncation of tensor dimensions in vLLM's GGUF dequantize kernels (csrc/quantization/gguf/gguf_kernel.cu) causes partial tensor processing. The output tensor is allocated at full size via torch::empty (uninitialized memory), but the dequantize CUDA kernel processes only a truncated number of elements. The unfilled portion of the output tensor retains whatever was previously in GPU memory. In multi-tenant inference deployments, this residual GPU memory may contain tensor data from other users' inference requests, constituting information disclosure. This vulnerability is fixed in 0.23.1rc0.

CVSS 5.3 · Moyenne · EPSS 0,5% · Correctif disponible

Publication

2026-06-22T21:55:42.001Z

Mise à jour

2026-06-23T15:05:21.711Z

Pile logicielle: python

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