Secure Development & MLOps Assurance

AI systems are built and operated through complex development pipelines that include code, data, models, dependencies, infrastructure, and deployment automation. Weaknesses within these processes can introduce security vulnerabilities, operational failures, and governance risks. This lesson explores secure development and MLOps assurance, examining secure coding practices, dependency management, CI/CD security, artifact signing, software bills of materials (SBOMs), and open-source governance. Learners will study how organizations secure AI development environments while maintaining accountability, traceability, and operational resilience. Understanding MLOps assurance is essential for AI governance auditors evaluating the security and integrity of AI delivery pipelines.