CVE-2025-62164: Vllm

High severity, CVSS 8.8. EPSS: 0.9% chance of exploitation in the next 30 days.

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.

Affected products

• Vllm Vllm: from 0.10.2, before 0.11.1 (fixed in 0.11.1); version 0.11.1 only

Published 2025-11-21. Last modified 2026-06-17.