The following table lists the changes that have been made to the
CVE-2025-46560 vulnerability over time.
Vulnerability history details can be useful for understanding the evolution
of a vulnerability, and for identifying the most recent changes that may
impact the vulnerability’s severity, exploitability, or other characteristics.
Apr. 30, 2025
| Action | Type | Old Value | New Value |
|---|---|---|---|
| Added | 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., , ) 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. | |
| Added | CVSS V3.1 | AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H | |
| Added | CWE | CWE-1333 | |
| Added | Reference | https://github.com/vllm-project/vllm/blob/8cac35ba435906fb7eb07e44fe1a8c26e8744f4e/vllm/model_executor/models/phi4mm.py#L1182-L1197 | |
| Added | Reference | https://github.com/vllm-project/vllm/security/advisories/GHSA-vc6m-hm49-g9qg |
CVE ID : CVE-2025-10304 Published : Dec. 3, 2025, 3:27 a.m. | 26 minutes ago Description : The Everest Backup –
CVE ID : CVE-2025-12585 Published : Dec. 3, 2025, 3:27 a.m. | 26 minutes ago Description : The MxChat – AI
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