AI Model Security & Governance refers to the set of practices, tools, and frameworks designed to protect artificial intelligence (AI) and machine learning (ML) models throughout their lifecycle. This category addresses risks such as model theft, adversarial attacks, data poisoning, and unauthorized access, while also ensuring compliance with regulatory and ethical standards for AI deployment. Core capabilities include model integrity validation, access control, monitoring for anomalous behavior, and audit logging. Solutions may also provide mechanisms for secure model deployment, explainability, and policy enforcement to manage how models are used and updated. Technical scope often extends to protecting training data, securing inference processes, and managing model versioning and provenance. Typical users are security teams, data scientists, ML engineers, and compliance officers in organizations deploying AI models in production environments. Their objectives include safeguarding intellectual property, maintaining trust in automated decisions, and meeting governance requirements. This category is distinct from general application security, as it focuses specifically on the unique threats and compliance challenges associated with AI and ML systems. Cyberin offers a platform for discovering and comparing AI Model Security & Governance solutions to support informed decision-making.