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Medium 5.3Published Jun 22, 2026

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

Updated under an hour ago ()

Does this affect you?

It affects vllm-project vllm and 1 other product. Add what you run to find out whether that includes you.

No exploitation reported and no EPSS estimate yet.

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 MEDIUM (v4.0, CNA)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
Weakness (CWE)
CWE-681, CWE-200
Known exploited
Not in CISA's KEV catalog
EPSS (exploitation in the next 30 days)
Not loaded for this CVE
Assigned by
GitHub_M
NVD analysis
Analyzed
Record last updated
Jun 23, 2026
First seen by InfoSec Signals
Oct 9, 2026

Affected products

Affected products
vllm-project vllm
vllm_project:vllm (from the name)
from 0.5.5, < 0.23.1rc0
CNA record
vllm vllm
vllm:vllm
from 0.5.5 before 0.23.1
NVD

References

References

The CVE record is authoritative. Products marked “from the name” were identified from the CNA's free-text names, not a CPE, and are matched less certainly. This product uses the NVD API but is not endorsed or certified by the NVD.

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