Securing AI Applications Across the AI Lifecycle

AI applications are changing and security teams must expand their scope beyond cloud infrastructure to include application-level risk. Cloud context remains foundational, but securing AI applications also requires understanding how they're built, what they're designed to do, and what they're capable of. Without that application context, it's impossible to fully understand AI-native risk or the real attack paths introduced by AI.

Join this session to examine a unified approach to AI application security. We will demonstrate how to map AI applications across custom code, managed AI platforms, and SaaS; uncover AI-native risks across agents, models, MCP servers, and data; prioritize real attack paths using unified cloud and AI context; and detect threats at runtime. Learn how a unified approach to AI application security enables teams to secure the entire AI application lifecycle—from build through production—without impacting development velocity.