Generative AI and autonomous AI agents are rapidly transforming how organizations build applications, process information, and automate business operations. However, these advancements introduce a new class of security challenges that traditional cybersecurity controls were never designed to address.

From prompt injection and jailbreaks to sensitive information disclosure, model manipulation, insecure tool integrations, and malicious Model Context Protocol (MCP) interactions, securing AI-powered applications requires a fundamentally different approach.

This session explores the emerging concept of the AI Firewall and how organizations can build effective security controls around LLM applications and agentic AI systems. It examines real-world attack scenarios, the OWASP Top 10 for LLM Applications, Shadow AI risks, runtime inspection, AI-aware traffic controls, and strategies for protecting interactions between users, models, data sources, and external tools.

Through practical attack demonstrations and defensive architecture patterns, attendees will learn how to identify AI-specific threats, implement layered security controls, and establish a security-first approach to deploying enterprise AI applications.

The objective is to move beyond securing traditional applications and explore what it takes to secure the next generation of intelligent, autonomous systems.