216.73.216.133

CVE-2025-46560

· Published 30/04/2025 01:15 · Modified 30/04/2025 14:15

Labels: CVE-2025-46560 2025-04-30CVE-2025-46560CWE-1333[email protected]

Essential information

Published
30/04/2025 01:15
Modified
30/04/2025 14:15
Author
Creator
CVSS
6.5 MEDIUM (v3.1)
CISA KEV
No
CWE
CVSS vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H

CVSS metrics

Description

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.

NVD status

Status
Received — CVE has been recently published to the CVE List and has been received by the NVD.
Source
[email protected]
NVD
View on NVD

Affected products (CPE)

ProductCPE
vllm / vllm cpe:2.3:a:vllm:vllm:0.8.0-0.8.4:*:*:*:*:*:*:*
vllm / vllm cpe:2.3:a:vllm:vllm:0.8.5:*:*:*:*:*:*:*

References