Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Collecting logs and metrics isn’t enough real API security requires actionable insights and the ability to respond fast. In this clip, Wallarm and Oracle experts explain why telemetry without a clear response plan is useless, and how building detection into your incident response process makes the difference between stopping threats and just observing them.

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.