Описание
vLLM is an inference and serving engine for large language models (LLMs). In versions starting from 0.7.0 to before 0.9.0, in the file vllm/multimodal/hasher.py, the MultiModalHasher class has a security and data integrity issue in its image hashing method. Currently, it serializes PIL.Image.Image objects using only obj.tobytes(), which returns only the raw pixel data, without including metadata such as the image’s shape (width, height, mode). As a result, two images of different sizes (e.g., 30x100 and 100x30) with the same pixel byte sequence could generate the same hash value. This may lead to hash collisions, incorrect cache hits, and even data leakage or security risks. This issue has been patched in version 0.9.0.
An image based hash collision flaw was found in vLLM due to insufficient distinct hashing. This flaw allows an attacker to poison the cache in a vLLM instance, which may lead to inconsistent or unexpected output.
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-cuda-rhel9 | Fix deferred | ||
| Red Hat AI Inference Server | rhaiis/vllm-rocm-rhel9 | Fix deferred | ||
| Red Hat Enterprise Linux AI (RHEL AI) | rhelai1/bootc-amd-rhel9 | Fix deferred | ||
| Red Hat Enterprise Linux AI (RHEL AI) | rhelai1/bootc-aws-nvidia-rhel9 | Fix deferred | ||
| Red Hat Enterprise Linux AI (RHEL AI) | rhelai1/bootc-azure-amd-rhel9 | Fix deferred | ||
| Red Hat Enterprise Linux AI (RHEL AI) | rhelai1/bootc-azure-nvidia-rhel9 | Fix deferred | ||
| Red Hat Enterprise Linux AI (RHEL AI) | rhelai1/bootc-gcp-nvidia-rhel9 | Fix deferred | ||
| Red Hat Enterprise Linux AI (RHEL AI) | rhelai1/bootc-intel-rhel9 | Fix deferred | ||
| Red Hat Enterprise Linux AI (RHEL AI) | rhelai1/bootc-nvidia-rhel9 | Fix deferred | ||
| Red Hat Enterprise Linux AI (RHEL AI) | rhelai1/instructlab-amd-rhel9 | Fix deferred |
Показывать по
Ссылки на источники
Дополнительная информация
Статус:
EPSS
4.2 Medium
CVSS3
Связанные уязвимости
vLLM is an inference and serving engine for large language models (LLMs). In versions starting from 0.7.0 to before 0.9.0, in the file vllm/multimodal/hasher.py, the MultiModalHasher class has a security and data integrity issue in its image hashing method. Currently, it serializes PIL.Image.Image objects using only obj.tobytes(), which returns only the raw pixel data, without including metadata such as the image’s shape (width, height, mode). As a result, two images of different sizes (e.g., 30x100 and 100x30) with the same pixel byte sequence could generate the same hash value. This may lead to hash collisions, incorrect cache hits, and even data leakage or security risks. This issue has been patched in version 0.9.0.
vLLM is an inference and serving engine for large language models (LLM ...
vLLM has a Weakness in MultiModalHasher Image Hashing Implementation
Уязвимость класса MultiModalHasher библиотеки для работы с большими языковыми моделями (LLM) vLLM, позволяющая нарушителю раскрыть защищаемую информацию
EPSS
4.2 Medium
CVSS3