This whitepaper explores how AI-native systems introduce dynamic and often invisible attack surfaces. The early sections explain that traditional security tools cannot track evolving model interactions, plugins, and data flows. The middle sections identify key risks such as prompt injection, data exfiltration, adversarial inputs, and agentic misbehavior. It introduces AISPM and AI-BOM as solutions for continuous visibility and governance. The later sections emphasize continuous discovery, risk prioritization, and mapping frameworks for AI environments. The key takeaway is that visibility is the foundation of AI security—organizations must continuously map and monitor their AI ecosystems to manage risk effectively.

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