
The reliance on machine learning (ML) frameworks by organizations for various applications has grown exponentially, raising numerous questions about their security. Recent disclosures by JFrog’s researchers have spotlighted significant vulnerabilities in popular open-source ML frameworks like MLflow, PyTorch, and MLeap. Unlike previous concerns, which mainly revolved around server-side issues, these new flaws make it possible for attackers to exploit ML










