An AI security deployment needs a supply-chain policy, not just a capable model. In this GPT-6 Cyber campaign installment, the focus is defensive engineering around the agent: which artifacts enter its environment, who approved them, and how operators can withdraw them. This is a proposed reference design, not a report of a new model capability or intrusion.
OWASP places training data, third-party models, and deployment platforms within the LLM supply-chain risk surface.[1] Its guidance recommends component inventories, verifiable sources, signing, and integrity checks.[1] The useful operational question is therefore broader than “did we download the right weights?”: can the team identify and approve everything needed to reproduce this deployment?[1]
