Researchers uncovered 22 security vulnerabilities in popular open-source machine learning frameworks like MLflow, PyTorch, H2O, and MLeap, enabling risks such as remote code execution (RCE) and data compromise. Exploiting these flaws could allow attackers to hijack ML clients, backdoor models, and infiltrate organizational pipelines.

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