Vllm
CVE-2025-46560
MEDIUM
Severity by source
AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Primary rating from GitHub Advisory.
CVSS VectorGitHub Advisory
Lifecycle Timeline
4DescriptionGitHub Advisory
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.
AnalysisAI
vLLM is a high-throughput and memory-efficient inference and serving engine for LLMs. Rated medium severity (CVSS 6.5), this vulnerability is remotely exploitable, low attack complexity. Public exploit code available and no vendor patch available.
Technical ContextAI
This vulnerability is classified under CWE-1333. 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. Affected products include: Vllm. Version information: prior to 0.8.5.
RemediationAI
No vendor patch is available at time of analysis. Monitor vendor advisories for updates. Apply vendor patches when available. Implement network segmentation and monitoring as interim mitigations.
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Same technique Denial Of Service
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