Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

AI consumes massive volumes of unstructured data — emails, documents, reports, and prompts. Hidden within them are sensitive details: customer PII, salary data, intellectual property, and confidential financial information. Without the right safeguards, one innocent prompt can lead to costly data leaks, compliance violations, and privacy risks. Traditional security tools like RBAC, DLPs, and prompt filters weren’t designed for AI. They fail because AI doesn’t see folders — it consumes raw context. That’s where Protecto’s Context-Based Access Control (CBAC) comes in.

As enterprises rapidly adopt agentic AI and large language models (LLMs) to automate critical business processes and access sensitive data, the traditional security playbook is no longer sufficient. The Model Context Protocol (MCP), a new connector for AI systems like Amazon Bedrock Agents, is revolutionizing enterprise integration—but it also introduces new risks. Join us for an in-depth session exploring how to secure MCP-based AI architectures using Teleport’s Infrastructure Identity Platform and AWS. We’ll cover.