Model Armor: Securing AI Deployments
Overview
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.
What You'll Learn
- Explain the purpose of Model Armor in a company's security portfolio.
- Define the protections that Model Armor applies to all interactions with the LLM.
- Set up the Model Armor API and find flagged violations.
- Identify how Model Armor manages prompts and responses.
Who Should Attend
Security engineers, AI/ML developers, cloud architects
Prerequisites
Working knowledge of APIs, Google Cloud CLI, cloud security foundational principles, and familiarity with the Google Cloud console.
Products Covered
Course Modules
Course overview
Topics
- What's in it for me?
Learning Outcomes
- Recall the course learning objectives.
Model Armor overview
Topics
- About Model Armor
- LLM security risks
Learning Outcomes
- Explain the purpose of Model Armor in a company's security portfolio.
- Identify the subset of top 10 OWASP LLM vulnerabilities that Model Armor addresses.
- Identify Model Armor key concepts and architecture.
- Map Model Armor features to the security risks they mitigate.
Activities
Customize Model Armor
Topics
- About customization
- Floor settings
- Guard rails and confidence levels
- Templates
Learning Outcomes
- Define the protections that Model Armor applies to all interactions with the LLM.
- Describe floor settings and explain how they work.
- Explain the purpose of a template and how it works with the API.
- Configure the four types of detections in the template.
Activities
Use Model Armor
Topics
- About setup
- API setup
- Flagged violations
Learning Outcomes
- Set up the Model Armor API and find flagged violations.
- Explain the prerequisites that are required to work with the API.
- Describe how to enable the API.
- Set up logging in the template, explore types of audit logs, and find them in SCC.
- Explain how to find floor setting violations in SCC and resolve them.
Activities
Put it all together
Topics
- Prompts and responses
- Application code
Learning Outcomes
- Identify how Model Armor intercepts and manages prompts and responses.
- Explain how Model Armor reviews prompts and reports findings based on content safety flags.
- Explain how Model Armor reviews LLM responses and updates them according to template settings.
- Execute various commands for sanitizing user prompts against different security features.
Activities
Course conclusion
Topics
- What did I learn?
Learning Outcomes
- Summarize the course learning objectives.
Get This Training
No public classes currently scheduled. Express interest below or request private training.
Course Details
- Course Code
- T-MODARM-B
- Duration
- 1 day
- Format
- ILT
- Level
- Introductory
- Modules
- 6
- Activities
- 6
- Price
- Loading...
Questions About This Course?
Contact us for custom scheduling, group discounts, or curriculum customization.
Contact Us