This guide outlines a security framework for safely deploying generative AI models in enterprises. It identifies risks like model manipulation, data poisoning, prompt injection, and sensitive data leakage. Palo Alto Networks proposes a layered defense using Prisma Cloud, Cortex XDR, and AI runtime security. Key strategies include securing the model lifecycle (training to inference), enforcing policy controls, and integrating runtime monitoring and threat detection. The paper emphasizes a proactive, risk-based approach that aligns with AI governance and compliance requirements, ensuring that innovations in AI don’t come at the expense of organizational security or regulatory integrity.

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