๐Ÿ” CVE Alert

CVE-2026-53923

UNKNOWN 0.0

vLLM GGUF Kernels: int64_t to int truncation of tensor dimensions causes GPU buffer overflow

CVSS Score
0.0
EPSS Score
0.0%
EPSS Percentile
0th

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.

CWE CWE-681 CWE-200
Vendor vllm-project
Product vllm
Published Jun 22, 2026
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Affected Versions

vllm-project / vllm
>= 0.5.5, < 0.23.1rc0

References

NVD โ†— CVE.org โ†— EPSS Data โ†—
github.com: https://github.com/vllm-project/vllm/security/advisories/GHSA-5jv2-g5wq-cmr4 github.com: https://github.com/vllm-project/vllm/pull/44971 github.com: https://github.com/vllm-project/vllm/commit/f219788f91952827132fa4fdf916427cd20d225e