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

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

https://cvefeed.io/rssfeed/latest.atom / Fri, 11/21/2025 - 07:49
CVE ID : CVE-2025-62164
Published : Nov. 21, 2025, 2:15 a.m. | 3 hours, 24 minutes ago
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.
Severity: 8.8 | HIGH
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