Trust, Track, and Verify - Securing AI Pipelines End-to-End

Learn to secure AI pipelines from development to deployment by implementing comprehensive supply chain security measures for open-source AI systems. Explore critical vulnerabilities in AI workflows including poisoned data, tampered checkpoints, unclear provenance, and unverified dependencies that emerge as foundation models and autonomous agents scale. Master the use of Bill of Materials (BOMs) such as SPDX to capture complete lineage tracking of code, data, and models throughout the AI development lifecycle. Discover AI-specific security controls from CoSAI's supply chain framework and implement Unified AI-Ops practices that integrate MLOps, DataOps, SecOps, and AgentOps. Gain practical knowledge on integrating provenance tracking, cryptographic attestations, and continuous validation techniques to build AI systems that are secure-by-default, observable, and auditable across their entire operational lifecycle.