The Model Context Protocol (MCP) is transforming how AI agents connect with tools and data, introducing a new, dynamic integration layer for intelligent automation. This session examines how MCP alters the security landscape¿exposing novel risks, such as tool poisoning, privilege escalation, and supply chain threats, all of which are beyond what's typically observed in traditional AI environments. The talk will unpack these risks through approachable examples and offer practical steps to guard critical AI-powered workflows and sensitive data. This session is ideal for security teams, AI practitioners, and anyone interested in exploring the next chapter of cybersecurity in AI systems.
By the end of this session, participants will be able to: Explain the purpose of the Model Context Protocol (MCP) and how it enables dynamic integration between AI agents, tools, and data. Identify key security risks introduced by MCP, including tool poisoning, privilege escalation, and supply chain vulnerabilities. Compare how MCP-related risks differ from those in traditional AI environments. Analyze real-world examples of MCP security threats to understand how they might emerge in practice. Evaluate the implications of MCP adoption for both AI practitioners and security teams preparing for next-generation cybersecurity challenges.