CVE Database · CVE-2025-62164
CVSS v3.1
8.8
EPSS
0.93%
Published
Nov 20, 2025
Modified
Dec 4, 2025
Public PoC / Exploit
All weaponized →No public PoC or exploit code indexed for this CVE.
Links to public security research (Exploit-DB, Nuclei, Trickest, GitHub) for defensive use only.
Description
vLLM is an inference and serving engine for large language models (LLMs). From versions 0.10.2 to before 0.11.1, a memory corruption vulnerability could lead to a crash (denial-of-service) and potentially remote code execution (RCE), exists in the Completions API endpoint. When processing user-supplied prompt embeddings, the endpoint loads serialized tensors using torch.load() without sufficient validation. Due to a change introduced in PyTorch 2.8.0, sparse tensor integrity checks are disabled by default. As a result, maliciously crafted tensors can bypass internal bounds checks and trigger an out-of-bounds memory write during the call to to_dense(). This memory corruption can crash vLLM and potentially lead to code execution on the server hosting vLLM. This issue has been patched in version 0.11.1.
CVSS Vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:HWeaknesses (CWE)
References (3)