CVE-2025-46560 - LLaMA LLM Multimodal Tokenizer Resource Exhaustion

CVE-2025-46560 - LLaMA LLM Multimodal Tokenizer Resource Exhaustion

https://cvefeed.io/rssfeed/latest.atom / Wed, 04/30/2025 - 05:38
CVE ID : CVE-2025-46560
Published : April 30, 2025, 1:15 a.m. | 56 minutes ago
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.
Severity: 6.5 | MEDIUM
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