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High 8.8Published Nov 20, 2025

CVE-2025-62164VLLM deserialization vulnerability leading to DoS and potential RCE

Updated under an hour ago ()

Does this affect you?

It affects vllm-project vllm and 1 other product. Add what you run to find out whether that includes you.

No exploitation reported and no EPSS estimate yet.

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
8.8 HIGH (v3.1, CNA)CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
Weakness (CWE)
CWE-20, CWE-123, CWE-502, CWE-787
Known exploited
Not in CISA's KEV catalog
EPSS (exploitation in the next 30 days)
Not loaded for this CVE
Assigned by
GitHub_M
NVD analysis
Analyzed
Record last updated
Nov 24, 2025
First seen by InfoSec Signals
Oct 9, 2026

Affected products

Affected products
vllm-project vllm
vllm_project:vllm (from the name)
from 0.10.2, < 0.11.1
CNA record
vllm vllm
vllm:vllm
from 0.10.2 before 0.11.1; 0.11.1; 0.11.1
NVD

References

References

The CVE record is authoritative. Products marked “from the name” were identified from the CNA's free-text names, not a CPE, and are matched less certainly. This product uses the NVD API but is not endorsed or certified by the NVD.

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