Описание
Hugging Face Transformers Perceiver Model Deserialization of Untrusted Data Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Hugging Face Transformers. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file.
The specific flaw exists within the parsing of model files. The issue results from the lack of proper validation of user-supplied data, which can result in deserialization of untrusted data. An attacker can leverage this vulnerability to execute code in the context of the current user. Was ZDI-CAN-25423.
A flaw was found in the Hugging Face Transformers library. The parsing of model files fails to validate user-supplied data, causing a deserialization of untrusted data. An attacker can exploit this issue by providing a malicious Perceiver model or convincing a user to visit a malicious page, resulting in arbitrary code execution in the context of the current process.
Отчет
To exploit this issue, an attacker must convince a user to process a specially crafted Perceiver model file or visiting a malicious page, limiting the possibility of exploitation. Additionally, model files are not typically processed by users with administrative privileges, limiting the potential for a full system compromise. Due to these reasons, this vulnerability has been rated with an important severity.
Меры по смягчению последствий
To mitigate this issue, users should avoid processing Perceiver model files from untrusted or unverified sources. Ensure that all Perceiver model files processed by the Hugging Face Transformers library originate from trusted repositories or have been verified for integrity. If that is not possible, consider processing untrusted models within an isolated sandbox environment.
Затронутые пакеты
| Платформа | Пакет | Состояние | Рекомендация | Релиз |
|---|---|---|---|---|
| OpenShift Lightspeed | openshift-lightspeed/lightspeed-ocp-rag-rhel9 | Not affected | ||
| OpenShift Lightspeed | openshift-lightspeed/lightspeed-service-api-rhel9 | Will not fix | ||
| OpenShift Lightspeed | openshift-lightspeed-tech-preview/lightspeed-rag-tool-rhel9 | Will not fix | ||
| Red Hat AI Inference Server | rhaiis/model-opt-cuda-rhel9 | Affected | ||
| Red Hat AI Inference Server | rhaiis-preview/vllm-cuda-rhel9 | Affected | ||
| Red Hat AI Inference Server | rhaiis/vllm-cuda-rhel9 | Affected | ||
| Red Hat AI Inference Server | rhaiis/vllm-rocm-rhel9 | Affected | ||
| Red Hat AI Inference Server | rhaiis/vllm-spyre-rhel9 | Affected | ||
| Red Hat AI Inference Server | rhaiis/vllm-tpu-rhel9 | Affected | ||
| Red Hat Ansible Automation Platform 2 | ansible-automation-platform-24/de-minimal-rhel8 | Not affected |
Показывать по
Дополнительная информация
Статус:
EPSS
8.8 High
CVSS3
Связанные уязвимости
Hugging Face Transformers Perceiver Model Deserialization of Untrusted Data Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Hugging Face Transformers. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file. The specific flaw exists within the parsing of model files. The issue results from the lack of proper validation of user-supplied data, which can result in deserialization of untrusted data. An attacker can leverage this vulnerability to execute code in the context of the current user. Was ZDI-CAN-25423.
Hugging Face Transformers Perceiver Model Deserialization of Untrusted Data Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Hugging Face Transformers. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file. The specific flaw exists within the parsing of model files. The issue results from the lack of proper validation of user-supplied data, which can result in deserialization of untrusted data. An attacker can leverage this vulnerability to execute code in the context of the current user. Was ZDI-CAN-25423.
EPSS
8.8 High
CVSS3