CVE detail
CVE-2026-53923
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.
Buzz score
Why this CVE is surfacing
This all-time snapshot uses the same composite formula as Trending across a 30-year evidence window, rather than a current rolling window.
Buzz score components · mention 13.9 · diversity 5.0 · KEV 0.0 · OTX 0.0 · PoC 0.0
Why it matters now
Mention timeline
- Total mentions
- 0
- within the 30d window
- Peak daily
- 0
- highest bucket
Evidence
Source links by recency
3 source links · newest first
No excerpt available.
Exploitgithub.comJun 22, 2026, 11:16 PMNo excerpt available.
Exploitgithub.comJun 22, 2026, 11:16 PMNo excerpt available.
Exploitgithub.comJun 22, 2026, 11:16 PM
Exploit code
Public exploit repository references
Public PoC repositories are third-party, potentially unsafe artifacts. Treat their code as untrusted and use it only on authorized systems in an isolated, least-privilege environment. cvebuzz does not execute the code or verify that an exploit works.
0 repository references · best confidence N/A · max 0 stars
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