Vulnerability 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 Score
HIGH
Affected Products
| Vendor | Product | Versions |
|---|---|---|
| Vllm | Vllm | >= 0.10.2, < 0.11.1 |
Related Weaknesses (CWE)
References
- https://github.com/vllm-project/vllm/commit/58fab50d82838d5014f4a14d991fdb9352c9Patch
- https://github.com/vllm-project/vllm/pull/27204Issue TrackingPatchVendor Advisory
- https://github.com/vllm-project/vllm/security/advisories/GHSA-mrw7-hf4f-83pfIssue TrackingVendor Advisory
FAQ
What is CVE-2025-62164?
CVE-2025-62164 is a vulnerability with a CVSS score of 8.8 (HIGH). 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 potenti...
How severe is CVE-2025-62164?
CVE-2025-62164 has been rated HIGH with a CVSS base score of 8.8/10. Review the CVSS metrics above for detailed severity breakdown.
Is there a patch for CVE-2025-62164?
Check the references section above for vendor advisories and patch information. Affected products include: Vllm Vllm.