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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.

CVSS 5.3 · MediumBuzz score 18.9

Buzz score

Why this CVE is surfacing

Buzz score total 18.9

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
Mention score
13.9
3 evidence mentions in the snapshot
Diversity score
5.0
1 sources across 1 categories
KEV score
0.0
No KEV entry observed
OTX score
0.0
0 OTX pulses
PoC score
0.0
0 repos · best confidence N/A
Best PoC traction
0
Maximum stars on a matched PoC repo

Why it matters now

Mention timeline

Total mentions
0
within the 30d window
Peak daily
0
highest bucket

Evidence

Source links by recency

Newest mentions first
3 source links · newest first

Exploit code

Public exploit repository references

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0 repository references · best confidence N/A · max 0 stars
No public PoC repositories have been matched yet.

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