CVE-2026-4137— MLflow 安全漏洞

Incomplete Fix for CVE-2025-10279: Insecure Temporary Directory Permissions in mlflow/mlflow

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.

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创建拥有不安全权限的临时文件

MLflow 安全漏洞

MLflow是MLflow开源的一个简化机器学习开发的平台，包括跟踪实验、将代码打包成可重复的运行以及共享和部署模型。 mlflow 3.11.0之前版本存在安全漏洞，该漏洞源于get_or_create_nfs_tmp_dir函数创建具有全局可写权限的临时目录，可能导致本地攻击者篡改模型工件并实现任意代码执行。

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