Описание
In mlflow/mlflow versions prior to 3.11.0, the get_or_create_nfs_tmp_dir() function in mlflow/utils/file_utils.py creates temporary directories with world-writable permissions (0o777), and the _create_model_downloading_tmp_dir() function in mlflow/pyfunc/__init__.py creates directories with group-writable permissions (0o770). These insecure permissions allow local attackers to tamper with model artifacts, such as cloudpickle-serialized Python objects, and achieve arbitrary code execution when the tampered artifacts are deserialized via cloudpickle.load(). This vulnerability is particularly critical in environments with shared NFS mounts, such as Databricks, where NFS is enabled by default. The issue is a continuation of the vulnerability class addressed in CVE-2025-10279, which was only partially fixed.
A flaw was found in mlflow/mlflow. Insecure permissions on temporary directories allow local attackers to tamper with model artifacts, such as cloudpickle-serialized Python objects. This manipulation can lead to arbitrary code execution when the tampered artifacts are deserialized. This vulnerability is particularly critical in environments with shared Network File System (NFS) mounts.
Отчет
Important: This flaw in MLflow allows local attackers to achieve arbitrary code execution by tampering with model artifacts in insecurely permissioned temporary directories. This is particularly critical in environments with shared Network File System (NFS) mounts, where default configurations may expose these directories to unauthorized modification.
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 OpenShift AI (RHOAI) | rhoai/odh-mlflow-rhel9 | Not affected | ||
| Red Hat OpenShift AI (RHOAI) | rhoai/odh-pipeline-runtime-datascience-cpu-py312-rhel9 | Not affected | ||
| Red Hat OpenShift AI (RHOAI) | rhoai/odh-pipeline-runtime-pytorch-cuda-py312-rhel9 | Not affected | ||
| Red Hat OpenShift AI (RHOAI) | rhoai/odh-pipeline-runtime-pytorch-llmcompressor-cuda-py312-rhel9 | Not affected | ||
| Red Hat OpenShift AI (RHOAI) | rhoai/odh-pipeline-runtime-pytorch-rocm-py312-rhel9 | Not affected | ||
| Red Hat OpenShift AI (RHOAI) | rhoai/odh-pipeline-runtime-tensorflow-cuda-py312-rhel9 | Not affected | ||
| Red Hat OpenShift AI (RHOAI) | rhoai/odh-th06-cpu-torch210-py312-rhel9 | Not affected | ||
| Red Hat OpenShift AI (RHOAI) | rhoai/odh-th06-cuda130-torch210-py312-rhel9 | Not affected | ||
| Red Hat OpenShift AI (RHOAI) | rhoai/odh-th06-rocm64-torch291-py312-rhel9 | Not affected | ||
| Red Hat OpenShift AI (RHOAI) | rhoai/odh-training-cuda128-torch29-py312-rhel9 | Not affected |
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Дополнительная информация
Статус:
EPSS
7.8 High
CVSS3
Связанные уязвимости
In mlflow/mlflow versions prior to 3.11.0, the `get_or_create_nfs_tmp_dir()` function in `mlflow/utils/file_utils.py` creates temporary directories with world-writable permissions (0o777), and the `_create_model_downloading_tmp_dir()` function in `mlflow/pyfunc/__init__.py` creates directories with group-writable permissions (0o770). These insecure permissions allow local attackers to tamper with model artifacts, such as cloudpickle-serialized Python objects, and achieve arbitrary code execution when the tampered artifacts are deserialized via `cloudpickle.load()`. This vulnerability is particularly critical in environments with shared NFS mounts, such as Databricks, where NFS is enabled by default. The issue is a continuation of the vulnerability class addressed in CVE-2025-10279, which was only partially fixed.
MLFlow Creates a Temporary File With Insecure Permissions
EPSS
7.8 High
CVSS3