CVSS 4.0
Вероятност да бъде експлоатирана в следващите 30 дни (EPSS)
Атакува се
Време до експлоатация
Атакува се по мрежата, без особени условия, без вход и след действие от потребителя.
- Експлоатация: няма данни за експлоатация
- Атаката не може да се автоматизира
Описание
Оригинално описание
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.
Засегнати продукти
- vllm-project vllm: >= 0.5.5, < 0.23.1rc0
Вид слабост
История
- 22 юни 2026 Публикувано
Други уязвимости в vllm-project vllm
Първоизточници
- https://www.cve.org/CVERecord?id=CVE-2026-53923
- https://nvd.nist.gov/vuln/detail/CVE-2026-53923
- https://github.com/vllm-project/vllm/security/advisories/GHSA-5jv2-g5wq-cmr4
- https://github.com/vllm-project/vllm/pull/44971
- https://github.com/vllm-project/vllm/commit/f219788f91952827132fa4fdf916427cd20d225e