CVE-2026-53923CWE-200CWE-681

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

Medium · published June 22, 2026

CVSS v4.0
5.3
EPSS
0%
Percentile
40.8
In the wild
Unconfirmed
What it is

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.

The record
Technical detail
CVSS v4.0
5.3 · MEDIUM
Vector
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:L/VI:L/VA:N/SC:N/SI:N/SA:N
EPSS
0.00484 · 40.8th percentile
Weaknesses
CWE-200 · Exposure of Sensitive Information to an Unauthorized Actor; CWE-681 · Incorrect Conversion between Numeric Types
Published
2026-06-22T21:55Z
EPSS history
Timeline
  • 22 JUN 21:55Z
    vLLM GGUF Kernels: int64_t to int truncation of tensor dimensions causes GPU buffer overflow
    cvelistv5