vLLM is a high-throughput and memory-efficient inference and serving engine for LLMs. Versions starting from 0.8.0 and prior to 0.8.5 are affected by a critical performance vulnerability in the input preprocessing logic of the multimodal tokenizer. The code dynamically replaces placeholder tokens (e.g., <|audio_|>, <|image_|>) with repeated tokens based on precomputed lengths. Due to ??inefficient list concatenation operations??, the algorithm exhibits ??quadratic time complexity (O(n²))??, allowing malicious actors to trigger resource exhaustion via specially crafted inputs. This issue has been patched in version 0.8.5.
References
| Link | Resource |
|---|---|
| https://github.com/vllm-project/vllm/blob/8cac35ba435906fb7eb07e44fe1a8c26e8744f4e/vllm/model_executor/models/phi4mm.py#L1182-L1197 | Product |
| https://github.com/vllm-project/vllm/security/advisories/GHSA-vc6m-hm49-g9qg | Exploit Vendor Advisory |
| https://github.com/vllm-project/vllm/security/advisories/GHSA-vc6m-hm49-g9qg | Exploit Vendor Advisory |
Configurations
History
28 May 2025, 19:15
| Type | Values Removed | Values Added |
|---|---|---|
| First Time |
Vllm vllm
Vllm |
|
| CVSS |
v2 : v3 : |
v2 : unknown
v3 : 7.5 |
| CPE | cpe:2.3:a:vllm:vllm:*:*:*:*:*:*:*:* | |
| References | () https://github.com/vllm-project/vllm/security/advisories/GHSA-vc6m-hm49-g9qg - Exploit, Vendor Advisory | |
| References | () https://github.com/vllm-project/vllm/blob/8cac35ba435906fb7eb07e44fe1a8c26e8744f4e/vllm/model_executor/models/phi4mm.py#L1182-L1197 - Product |
30 Apr 2025, 14:15
| Type | Values Removed | Values Added |
|---|---|---|
| CWE |
30 Apr 2025, 01:15
| Type | Values Removed | Values Added |
|---|---|---|
| New CVE |
Information
Published : 2025-04-30 01:15
Updated : 2025-05-28 19:15
NVD link : CVE-2025-46560
Mitre link : CVE-2025-46560
JSON object : View
Products Affected
vllm
- vllm
CWE
No CWE.