6 matches found
PYSEC-2026-2022 phi4mm: Quadratic Time Complexity in Input Token Processing leads to denial of service
Summary A critical performance vulnerability has been identified 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...
CVE-2025-46560
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...
CVE-2025-46560 vLLM phi4mm: Quadratic Time Complexity in Input Token Processing leads to denial of service
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...
CVE-2025-46560 vLLM phi4mm: Quadratic Time Complexity in Input Token Processing leads to denial of service
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...
CVE-2025-46560: Inefficient Regular Expression Complexity
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...
GHSA-VC6M-HM49-G9QG vLLM: Quadratic Time Complexity in Input Token Processing leads to denial of service
Summary A critical performance vulnerability has been identified 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...