Описание
Datasets through 5.0.0, fixed in commit f989ef9, contains a path traversal vulnerability in folder-based dataset builders where the file_name metadata field is not properly validated before being joined to the dataset directory. Attackers can supply crafted file_name values with directory traversal sequences to read arbitrary local files, which are then embedded into output when save_to_disk or push_to_hub is called.
A flaw was found in datasets. This path traversal vulnerability allows a remote attacker to read arbitrary local files. By providing specially crafted file names in the metadata, an attacker can trick the system into including sensitive local files when datasets are saved or published, leading to information disclosure.
Отчет
This path traversal vulnerability in the datasets library allows for information disclosure. An attacker could exploit this by providing specially crafted file_name metadata to a folder-based dataset builder, which, upon user interaction with save_to_disk or push_to_hub operations, could embed arbitrary local files into the output. The requirement for user interaction reduces the overall risk.
Меры по смягчению последствий
To mitigate this issue, ensure that all file_name metadata processed by the datasets library, especially within folder-based dataset builders, is thoroughly validated and sanitized. Avoid processing file_name values from untrusted sources without strict input validation to prevent directory traversal sequences. This will prevent the embedding of arbitrary local files during save_to_disk or push_to_hub operations.
Затронутые пакеты
| Платформа | Пакет | Состояние | Рекомендация | Релиз |
|---|---|---|---|---|
| Exploit Intelligence | exploit-intelligence-tech-preview/vulnerability-analysis-rhel9 | Will not fix | ||
| Exploit Intelligence | exploit-intelligence/vulnerability-analysis-rhel9 | Not affected | ||
| Lightspeed Core | lightspeed-core/lightspeed-stack-rhel9 | Fix deferred | ||
| Red Hat AI Inference Server | rhaii/model-opt-cuda-rhel9 | Not affected | ||
| Red Hat AI Inference Server | rhaiis/model-opt-cuda-rhel9 | Not affected | ||
| Red Hat AI Inference Server | rhaiis/vllm-rocm-rhel9 | Not affected | ||
| Red Hat AI Inference Server | rhaiis/vllm-spyre-rhel9 | Not affected | ||
| Red Hat AI Inference Server | rhaii/vllm-rocm-rhel9 | Not affected | ||
| Red Hat AI Inference Server | rhaii/vllm-spyre-rhel9 | Not affected | ||
| Red Hat Enterprise Linux AI (RHEL AI) 3 | R | Not affected |
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Дополнительная информация
Статус:
6.5 Medium
CVSS3
Связанные уязвимости
Datasets through 5.0.0, fixed in commit f989ef9, contains a path traversal vulnerability in folder-based dataset builders where the file_name metadata field is not properly validated before being joined to the dataset directory. Attackers can supply crafted file_name values with directory traversal sequences to read arbitrary local files, which are then embedded into output when save_to_disk or push_to_hub is called.
Datasets through 5.0.0, fixed in f989ef9, contains a path traversal vulnerability in folder-based dataset builders where the file_name metadata field is not properly validated before being joined to the dataset directory. Attackers can supply crafted file_name values with directory traversal sequences to read arbitrary local files, which are then embedded into output when save_to_disk or push_to_hub is called.
6.5 Medium
CVSS3