| Component | vLLM |
| Severity | high (CVSS 7.1) |
| CVSS vector | CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:H/I:H/A:H |
| Published (NVD) | 2025-12-01 |
| Last modified | 2026-06-17 |
| Affected versions | vllm < 0.11.1 |
| Fixed in | 0.11.1 |
| Weakness | CWE-94 |
| CISA KEV | not listed |
NVD description
vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.11.1, vllm has a critical remote code execution vector in a config class named Nemotron_Nano_VL_Config. When vllm loads a model config that contains an auto_map entry, the config class resolves that mapping with get_class_from_dynamic_module(...) and immediately instantiates the returned class. This fetches and executes Python from the remote repository referenced in the auto_map string. Crucially, this happens even when the caller explicitly sets trust_remote_code=False in vllm.transformers_utils.config.get_config. In practice, an attacker can publish a benign-looking frontend repo whose config.json points via auto_map to a separate malicious backend repo; loading the frontend will silently run the backend’s code on the victim host. This vulnerability is fixed in 0.11.1.
What to do
- Upgrade vLLM to
0.11.1or later. - Do not expose the component's API or UI to the internet without authentication in front of it.
Sources
- NVD: CVE-2025-66448
- https://github.com/vllm-project/vllm/security/advisories/GHSA-8fr4-5q9j-m8gm
- https://github.com/vllm-project/vllm/commit/ffb08379d8870a1a81ba82b72797f196838d0c86
- https://github.com/vllm-project/vllm/pull/28126
Read more
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