CVE-2025-46560

Published Apr 30, 2025

Last updated a month ago

Overview

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.
Source
security-advisories@github.com
NVD status
Analyzed

Risk scores

CVSS 3.1

Type
Primary
Base score
7.5
Impact score
3.6
Exploitability score
3.9
Vector string
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
Severity
HIGH

Weaknesses

security-advisories@github.com
CWE-1333

Social media

Hype score
Not currently trending

Configurations