CVE-2025-62164
BaseFortify
Publication date: 2025-11-21
Last updated on: 2025-12-04
Assigner: GitHub, Inc.
Description
Description
CVSS Scores
EPSS Scores
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Meta Information
Affected Vendors & Products
| Vendor | Product | Version / Range |
|---|---|---|
| vllm | vllm | From 0.10.2 (inc) to 0.11.1 (exc) |
| vllm | vllm | 0.11.1 |
| vllm | vllm | 0.11.1 |
Helpful Resources
Exploitability
| CWE ID | Description |
|---|---|
| CWE-787 | The product writes data past the end, or before the beginning, of the intended buffer. |
| CWE-502 | The product deserializes untrusted data without sufficiently ensuring that the resulting data will be valid. |
| CWE-20 | The product receives input or data, but it does not validate or incorrectly validates that the input has the properties that are required to process the data safely and correctly. |
| CWE-123 | Any condition where the attacker has the ability to write an arbitrary value to an arbitrary location, often as the result of a buffer overflow. |
Attack-Flow Graph
AI Powered Q&A
Can you explain this vulnerability to me?
This vulnerability exists in vLLM versions 0.10.2 to before 0.11.1 in the Completions API endpoint. It involves memory corruption caused by loading user-supplied serialized tensors using torch.load() without sufficient validation. Due to a change in PyTorch 2.8.0 disabling sparse tensor integrity checks by default, malicious tensors can bypass bounds checks and cause out-of-bounds memory writes during to_dense(), leading to crashes or potentially remote code execution on the server.
How can this vulnerability impact me? :
The vulnerability can cause denial-of-service by crashing the vLLM service and may allow an attacker to execute arbitrary code remotely on the server hosting vLLM, potentially compromising the system's security and integrity.
What immediate steps should I take to mitigate this vulnerability?
The immediate step to mitigate this vulnerability is to upgrade vLLM to version 0.11.1 or later, where the issue has been patched.