CVE-2026-53923
CVE.org · Published
- Record status
- Published
- Identifier year (not publication year)
- 2026
- Source publication
- Source updated
- Imported by cveboard
- Source snapshot
- cve_2026-10-24_midnight_baseline ·
CNA source text (English)
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.
Scoped product and version facts
Fix information unknown; no fixed version is derived here. Missing information does not prove that no fix exists.
Exploitation unknown; this catalogue does not assess exploitation.
vllm
- Vendor
- vllm-project
- Product
- vllm
- Platforms
- Unknown
- Default status
Unknown
| Version (version) | Status (status) | Version scheme (versionType) | Exclusive end (lessThan) | Inclusive end (lessThanOrEqual) | Status changes (at → status) |
|---|---|---|---|---|---|
| >= 0.5.5, < 0.23.1rc0 | affected | Unavailable | Unavailable | Unavailable | None listed |