Course Overview
This course identifies different attack vectors where malicious actors could abuse AI agents and proposes a defense-in-depth strategy, using a multi-layered approach to guard against attacks. These include guardrails on content, identity and access management of users and agents, network security, discoverability and observability.
Who should attend
Architects, Cloud Developers, AI Engineers, Security Experts.
Prerequisites
Working knowledge of building ADK agents and deploying them to Agent Runtime.
Course Objectives
- Deploy Agent Gateway as the centralized solution for managing network and content security.
- Implement content security guardrails using Model Armor and Cloud DLP to mitigate semantic threats like prompt injection and data leakage.
- Establish a zero-trust security perimeter using unique Agent Identity with mTLS, per-tool authorization with REQUEST_AUTHZ, and granular CEL policies.
- Discover agent tools through the Agent Registry and ensure end-to-end observability and threat detection using Cloud Trace and Security Command Center.