CVE-2025-62164

A vulnerability in vLLM allows attackers to supply malicious serialized prompt-embedding tensors that are deserialized using torch.load without validation. Due to PyTorch 2.8.0 disabling sparse-tensor integrity checks by default, a crafted tensor can bypass bounds checks and cause an out-of-bound...

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

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...

CVE-2025-62164

The CVE affects vLLM (inference/serving engine) before 0.11.1, where the Completions API loads user-supplied prompt embeddings with torch.load() lacking proper validation. A PyTorch 2.8.0 change disables sparse-tensor invariants checks, allowing crafted tensors to bypass bounds checks and trigger...