CVE-2025-62372
CVE-2025-62372 · vLLM vulnerable to DoS with incorrect shape of multimodal embedding inputs
Esta página presenta datos de fuentes públicas de vulnerabilidades. Consulta el aviso original antes de actualizar.
vLLM is an inference and serving engine for large language models (LLMs). From version 0.5.5 to before 0.11.1, users can crash the vLLM engine serving multimodal models by passing multimodal embedding inputs with correct ndim but incorrect shape (e.g. hidden dimension is wrong), regardless of whether the model is intended to support such inputs (as defined in the Supported Models page). This issue has been patched in version 0.11.1.
CVSS 8.3 · Alta · EPSS 0,4% · Corrección disponible
- Publicación
- Actualización
Pila tecnológica: python
Productos y versiones afectados
vllm
- Versiones
- >= 0.5.5, < 0.11.1: Afectada
Sin corrección publicada
vllm PyPI
- Versiones
- 0.10.0
- 0.10.1
- 0.10.1.1
- 0.10.2
- 0.11.0
- 0.5.5
- 0.6.0
- 0.6.1
- 0.6.1.post1
- 0.6.1.post2
- 0.6.2
- 0.6.3
- 0.6.3.post1
- 0.6.4
- 0.6.4.post1
- 0.6.5
- 0.6.6
- 0.6.6.post1
- 0.7.0
- 0.7.1
- 0.7.2
- 0.7.3
- 0.8.0
- 0.8.1
- 0.8.2
- 0.8.3
- 0.8.4
- 0.8.5
- 0.8.5.post1
- 0.9.0
- 0.9.0.1
- 0.9.1
- 0.9.2
- Intervalos de versiones afectados
- ECOSYSTEM: ≥ 0.5.5, < 0.11.1
Actualiza a 0.11.1
Fuentes originales
- https://github.com/vllm-project/vllm/security/advisories/GHSA-pmqf-x6x8-p7qw
- https://github.com/vllm-project/vllm/pull/27204
- https://github.com/vllm-project/vllm/pull/6613
- https://github.com/vllm-project/vllm/commit/58fab50d82838d5014f4a14d991fdb9352c9c84b
- https://nvd.nist.gov/vuln/detail/CVE-2025-62372