2h 30m EN / DE Max 50

Model Armor: Securing AI Deployments

This course explains how to use Model Armor to protect AI applications, specifically large language models (LLMs).The curriculum covers Model Armor's architecture and its role in mitigating threats like malicious URLs, prompt injection, jailbreaking, sensitive data leaks, and improper output handling.Practical skills include defining floor settings, configuring templates, and enabling various detection types. You'll also explore sample audit logs to find details about flagged violations. 

€295,00 excl. VAT

Individual scheduling

The courses are held as dedicated group sessions. Once you've booked, we'll coordinate a date that works for your team and send invitations to all participants.

Prerequisites

  • Working knowledge of APIs.
  • Working knowledge of Google Cloud CLI.
  • Working knowledge of cloud security foundational principles.
  • Familiarity with the Google Cloud console.

What you'll learn

  • Explain the purpose of Model Armor in a company's security portfolio.
  • Define the protections applied to all interactions with the LLM.
  • Identify the OWASP LLM vulnerabilities that Model Armor addresses.
  • Set up the Model Armor API and find flagged violations in Security Command Center (SCC).
  • Identify how the system intercepts and manages prompts and responses to ensure safety.

Course modules
What's in it for me?
About Model Armor LLM security risks
About customization Floor settings Guard rails and confidence levels Templates
About setup API setup Flagged violations
Prompts and responses Application code
What did I learn?
Model Armor: Securing AI Deployments