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.
This vulnerability carries a MEDIUM severity rating with a CVSS v3.1 score of 6.5, indicating it can be exploited remotely over the network with relatively low complexity without requiring user interaction requiring only low-level privileges . The vulnerability impacts and availability (service disruption) for affected systems. Impacting 1 product from vllm organizations running these solutions should prioritize assessment and patching.
Reported in 2025, this vulnerability emerged during an era marked by increased sophistication in supply chain attacks, cloud infrastructure vulnerabilities, and software-as-a-service (SaaS) security challenges. Security practices during this period emphasized zero-trust architectures, container security, and API protection.
2025-11-21T02:15:43.393
2025-12-04T17:40:47.150
Analyzed
CVSSv3.1: 6.5 (MEDIUM)
| Type | Vendor | Product | Version/Range | Vulnerable? |
|---|---|---|---|---|
| Application | vllm | vllm | < 0.11.1 | Yes |
| Application | vllm | vllm | 0.11.1 | Yes |
| Application | vllm | vllm | 0.11.1 | Yes |
SecUtils normalizes and enriches National Vulnerability Database (NVD) records by standardizing vendor and product identifiers, aggregating vulnerability metadata from both NVD and MITRE sources, and providing structured context for security teams. For vllm's affected products, we extract Common Platform Enumeration (CPE) data, Common Weakness Enumeration (CWE) classifications, CVSS severity metrics, and reference data to enable rapid vulnerability prioritization and asset correlation. This record contains no exploit code, proof-of-concept instructions, or attack methodologies—only defensive intelligence necessary for patch management, risk assessment, and security operations.