Samrat Ray

As agents connect to external tools and systems, security becomes a first-order concern. Every interaction — from authentication to tool invocation — must be governed, permissioned, and fully auditable. One leaked credential or broken audit trail can break production trust overnight.In this deep dive, we'll show how to secure MCP-based integrations in production on Databricks. You'll learn how to implement authentication and authorization, manage fine-grained access to tools, and ensure every agent action is traceable end-to-end. We'll also share how Databricks applies these patterns internally — using Unity Catalog connections to securely grant MCP access to thousands of users — along with the key risks, design tradeoffs, and best practices.You'll walk away with a production-ready blueprint for protecting data and systems as agents start taking real actions on behalf of your users.

Agentic AI systems—where LLM-powered agents plan, reason, and act across data and tools—are rapidly moving from proof-of-concept to mission-critical production. However, this shift introduces a new security surface: autonomous decision-making, dynamic tool use, and data access at scale. How do you innovate without compromising security, governance, or compliance? In this session, we explore how to build secure, enterprise-ready agentic systems on Databricks. Designed for practitioners and architects, we break down the unique risks of agentic workflows and map them to concrete controls. We will introduce the Databricks Agentic AI Security Framework developed with top researchers from OWASP, NIST, and Fortune 100 companies. Key Takeaways: - Reference architectures for deploying secure agentic AI at scale. - A framework to operationalize and explain your security posture to cyber teams. - Actionable tools, including a worksheet and live demo, to test your deployments and MCP security.

Databricks is shipping a wave of platform security, networking and compliance capabilities that make enterprise-grade protection the default — not an afterthought. In this session, we cover the highlights including Private Network Gateway for managed, secure connectivity to your data sources, context-based ingress policies that bring adaptive network controls to Genie, apps, AI/BI, and agentic workloads and cloudless compute with a cross-cloud backbone that simplifies networking across environments. We’ll also showcase automatic identity management (AIM), which automates identity provisioning and enforces least-privilege at scale. On the compliance side, we’ll announce a new Azure GovCloud environment, expanded AWS GovCloud capabilities and new certifications (ISMAP, HITRUST, FedRAMP High). Plus, secure cross-workspace access, serverless egress logs, account frontend private link, CMK for UC Catalogs and more. Come see how Databricks is making security a platform advantage.

This session is repeated. AI is transforming industries, enhancing customer experiences and automating decisions. As organizations integrate AI into core operations, robust security is essential. The Databricks Security team collaborated with top cybersecurity researchers from OWASP, Gartner, NIST, HITRUST and Fortune 100 companies to evolve the Databricks AI Security Framework (DASF) to version 2.0. In this session, we’ll cover an AI security architecture using Unity Catalog, MLflow, egress controls, and AI gateway. Learn how security teams, AI practitioners and data engineers can secure AI applications on Databricks. Walk away with:• A reference architecture for securing AI applications• A worksheet with AI risks and controls mapped to industry standards like MITRE, OWASP, NIST and HITRUST• A DASF AI assistant tool to test your AI security

Morgan Stanley, a highly regulated financial institution, needs to meet stringent security and regulatory requirements around data storage and processing. Traditionally, this has necessitated maintaining control over data and compute within their own accounts with the associated management overhead. In this session, we will cover how Morgan Stanley has partnered with Databricks on a fully-managed compute and storage solution that allows them to meet their regulatory obligations with significantly reduced effort. This innovative approach enables rapid onboarding of new projects onto the platform, improving operational efficiency while maintaining the highest levels of security and compliance.

Delta Sharing enables cross-domain sharing of data assets for collaboration. A practical concern providers and recipients face in doing so is the need to manually configure network and storage firewalls. This is particularly challenging for large-scale providers and recipients with strict compliance requirements. In this talk, we will describe our solution to fully eliminate these complexities. This enhances user experience, scalability and security, facilitating seamless data collaboration across diverse environments and cloud platforms.