Описание
vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.23.1rc0, ll temperature validation gates use comparison operators (<, >), which silently evaluate to False for NaN and for positive Infinity in Python's IEEE 754 float semantics. Both values pass every guard and propagate to GPU sampling kernels, where they produce undefined behavior or CUDA errors that can crash the inference worker. This vulnerability is fixed in 0.23.1rc0.
A flaw was found in vLLM, an inference and serving engine for large language models (LLMs). The temperature validation gates, which use comparison operators, incorrectly handle Not-a-Number (NaN) and positive Infinity values in Python's IEEE 754 float semantics. These invalid values can bypass validation and propagate to GPU sampling kernels, leading to undefined behavior or CUDA errors that can crash the inference worker. This could allow an attacker to cause a Denial of Service (DoS) by providing specially crafted input.
Отчет
This Moderate impact flaw in vLLM, as used in Red Hat AI Inference Server, Red Hat OpenShift AI, and Red Hat Enterprise Linux AI, allows for a denial of service. Improper validation of floating-point values like Not-a-Number (NaN) or positive Infinity in temperature parameters can bypass security checks, leading to undefined behavior or CUDA errors that crash the inference worker. This could be exploited by providing specially crafted input to the LLM inference engine.
Меры по смягчению последствий
Mitigation for this issue is either not available or the currently available options do not meet the Red Hat Product Security criteria comprising ease of use and deployment, applicability to widespread installation base, or stability.
Затронутые пакеты
| Платформа | Пакет | Состояние | Рекомендация | Релиз |
|---|---|---|---|---|
| Red Hat AI Inference Server | rhaiis/vllm-cpu-rhel9 | Fix deferred | ||
| Red Hat AI Inference Server | rhaiis/vllm-neuron-rhel9 | Fix deferred | ||
| Red Hat AI Inference Server | rhaiis/vllm-spyre-rhel9 | Fix deferred | ||
| Red Hat AI Inference Server | rhaiis/vllm-tpu-rhel9 | Fix deferred | ||
| Red Hat AI Inference Server | rhaii/vllm-cpu-rhel9 | Fix deferred | ||
| Red Hat AI Inference Server | rhaii/vllm-gaudi-rhel9 | Fix deferred | ||
| Red Hat AI Inference Server | rhaii/vllm-neuron-rhel9 | Fix deferred | ||
| Red Hat AI Inference Server | rhaii/vllm-spyre-rhel9 | Fix deferred | ||
| Red Hat AI Inference Server | rhaii/vllm-tpu-rhel9 | Fix deferred | ||
| Red Hat Enterprise Linux AI (RHEL AI) 3 | rhelai3/bootc-aws-cuda-rhel9 | Fix deferred |
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Дополнительная информация
Статус:
EPSS
6.5 Medium
CVSS3
Связанные уязвимости
vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.23.1rc0, ll temperature validation gates use comparison operators (<, >), which silently evaluate to False for NaN and for positive Infinity in Python's IEEE 754 float semantics. Both values pass every guard and propagate to GPU sampling kernels, where they produce undefined behavior or CUDA errors that can crash the inference worker. This vulnerability is fixed in 0.23.1rc0.
vLLM is an inference and serving engine for large language models (LLM ...
vLLM: temperature=NaN and temperature=Infinity bypass validation and propagate to GPU kernels
EPSS
6.5 Medium
CVSS3