7.5

CVE-2026-53923

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

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.
Daten sind bereitgestellt durch National Vulnerability Database (NVD)
Vllm ≫ Vllm Version >= 0.5.5 < 0.23.1
VulnDex Vulnerability Enrichment
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EPSS Metriken
Typ Quelle Score Percentile
EPSS FIRST.org 0.32% 0.237
CVSS Metriken
Quelle Base Score Exploit Score Impact Score Vector String
nvd@nist.gov 7.5 3.9 3.6
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N
security-advisories@github.com 5.3 0 0
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/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X
CWE-200 Exposure of Sensitive Information to an Unauthorized Actor

The product exposes sensitive information to an actor that is not explicitly authorized to have access to that information.

CWE-681 Incorrect Conversion between Numeric Types

When converting from one data type to another, such as long to integer, data can be omitted or translated in a way that produces unexpected values. If the resulting values are used in a sensitive context, then dangerous behaviors may occur.

https://github.com/vllm-project/vllm/security/advisories/GHSA-5jv2-g5wq-cmr4
Third Party Advisory
https://github.com/vllm-project/vllm/pull/44971
Issue Tracking
https://github.com/vllm-project/vllm/commit/f219788f91952827132fa4fdf916427cd20d225e
Patch