Course Overview of Vertex AI and Generative AI Security :

This course is specifically tailored for AI practitioners and security engineers who need to integrate generative AI responsibly. Through a security-conscious approach, participants explore the foundational security challenges of Vertex AI, implement identity and access controls, and learn to mitigate unique threats like prompt injection. The curriculum balances infrastructure security with specialized AI safety techniques, including securing Retrieval-Augmented Generation (RAG) systems.

After completing Vertex AI and Generative AI Security, participants will be able to:

  • Identify and mitigate security risks specific to LLMs and Generative AI applications.
  • Restrict access to Vertex AI resources using robust IAM and identity controls.
  • Protect sensitive AI data through encryption strategies and data governance.
  • Monitor Vertex AI operations in real-time with logging and alerting.
  • Defend against prompt hacking and injection attacks.
  • Securely ground generative AI models using RAG architectures.
  • Evaluate and test model responses for safety and accuracy.

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Key Features of Vertex AI and Generative AI Security

  • Specialized AI Security: One of the few courses focusing specifically on the intersection of Generative AI and enterprise security. 

  • Hands-on Defense: Features 8 modules and 7 technical labs, including specific labs on prompt hacking mitigation and RAG security. 

  • End-to-End Protection: Covers infrastructure (IAM/Encryption), operations (Monitoring), and model-specific security (Safety/Testing). 

  • Gemini Integration: Practical labs using the Vertex AI Gemini API for both application building and safeguarding. 

  • Modern Architecture Focus: Dedicated module on securing Retrieval-Augmented Generation (RAG) and function calling. 

Who should Attend Vertex AI and Generative AI Security ?

  • AI Practitioners
  • Security Engineers
  • IT Professionals responsible for AI integration

Prerequisites OF Vertex AI and Generative AI Security

  • Foundational knowledge of Google Cloud (equivalent to Cloud Digital Leader or Associate Cloud Engineer).
  • Basic understanding of Machine Learning and Large Language Models.

    • Why choose CloudThat as your training partner for Vertex AI and Generative AI Security?

    • Specialized GCP Focus: CloudThat specializes in cloud technologies, offering focused and specialized training programs. We are Authorized Trainers for the Google Cloud Platform. This specialization ensures in-depth coverage of GCP services, use cases, best practices, and hands-on experience tailored specifically for GCP.
    • Industry-Recognized Trainers: CloudThat has a strong pool of industry-recognized trainers certified by GCP. These trainers bring real-world experience and practical insights into the training sessions, comprehensively understanding how GCP is applied in different industries and scenarios. 
    • Hands-On Learning Approach: CloudThat emphasizes a hands-on learning approach. Learners can access practical labs, real-world projects, and case studies that simulate actual GCP environments. This approach allows learners to apply theoretical knowledge in practical scenarios, enhancing their understanding and skill set. 
    • Customized Learning Paths: CloudThat understands that learners have different levels of expertise and varied learning objectives. We offer customized learning paths, catering to beginners, intermediate learners, and professionals seeking advanced GCP skills. 
    • Interactive Learning Experience: CloudThat's training programs are designed to be interactive and engaging. We utilize various teaching methodologies like live sessions, group discussions, quizzes, and mentorship to keep learners engaged and motivated throughout the course. 
    • Placement Assistance and Career Support: CloudThat often provides placement assistance and career support services. This includes resume building, interview preparation, and connecting learners with job opportunities through our network of industry partners and companies looking for GCP-certified professionals. 
    • Continuous Learning and Updates: CloudThat ensures that our course content is regularly updated to reflect the latest trends, updates, and best practices within the GCP ecosystem. This commitment to keeping the content current enables learners to stay ahead in their GCP knowledge. 
    • Positive Reviews and Testimonials: Reviews and testimonials from past learners can strongly indicate the quality of training provided. You can Check feedback and reviews about our GCP courses that can provide potential learners with insights into the effectiveness and value of the training. 

    Learning objectives of Vertex AI and Generative AI Security

    • Foundational Knowledge: Establish an understanding of Vertex AI components and their unique security challenges. 
    • Access & Identity: Implement measures to secure resource access and manage identities. 
    • Data Protection: Configure encryption and safeguard sensitive information within AI workflows. 
    • Operational Oversight: Enable real-time monitoring and alerting for AI operations. 
    • Threat Mitigation: Identify and neutralize threats associated with Large Language Models. 
    • Safety & Evaluation: Apply testing techniques to validate model responses and ensure AI safety. 
    • RAG Security: Implement best practices for grounding data sources in RAG systems. 

    Course Outline of Vertex AI and Generative AI Security Download Course Outline

    Lecture Content

    • Foundations and security challenges of AI architectures
    • Establish foundational knowledge of Vertex AI components
    • Identifying unique security surfaces and vectors in AI workloads

    Learning Objectives

    • Establish foundational knowledge of Vertex AI and its unique security challenges

    Lab Content

    • NA

    Lecture Content

    • Access control and resource restriction fundamentals
    • IAM permissions, custom roles, and resource access policies
    • Identity management configurations for AI practitioners

    Learning Objectives

    • Implement identity and access control measures to restrict access to Vertex AI resources Lab Content
    • Lab: Vertex AI Identity and Access Management

    Lecture Content

    • Encryption strategies (at rest, in transit, and in use)
    • Customer-Managed Encryption Keys (CMEK) for AI assets
    • Enterprise data protection and data governance in AI pipelines

    Learning Objectives

    • Configure encryption strategies and protect sensitive information within Vertex AI

    Lab Content

    • Lab: Protecting Data in Vertex AI

    Lecture Content

    • Real-time security oversight methodologies 
    • Cloud Logging and Cloud Monitoring for Vertex AI operations
    • Setting up security alerts, threat detection, and audit logs

    Learning Objectives

    • Enable logging, monitoring, and alerting for real-time security oversight of Vertex AI operations

    Lab Content

    • Lab: Vertex AI Logging and Monitoring

    Lecture Content

    • Security threats facing foundation and Large Language Models 
    • OWASP Top 10 for Large Language Models overview
    • AI safety basics, alignment strategies, and shared responsibility

    Learning Objectives

    • Identify security risks specific to LLMs and generative AI applications
    • Introduce fundamentals of AI Safety

    Lab Content

    • NA

    Lecture Content

    • Prompt hacking methodologies (Prompt Injection, Jailbreaking, and Leaking)
    • Designing application-level defense guards and constraints
    • Injection mitigation strategies using the Vertex AI Gemini API

    Learning Objectives

    • Understand methods for mitigating prompt hacking and injection attacks
    • Explore the fundamentals of securing generative AI models and applications

    Lab Content

    • Lab: Safeguarding with Vertex AI Gemini API 
    • Lab: Gen AI & LLM Security for Developers

    Lecture Content

    • Testing generative AI model responses for security and alignment
    • Evaluating model responses using automation and metrics
    • Fine-Tuning LLMs to reduce risk surfaces and secure application output

    Learning Objectives

    • Implement best practices for testing model responses
    • Apply techniques for improving response security in generative AI applications

    Lab Content

    • Lab: Measure Gen AI Performance with the Generative AI Evaluation Service
    • Lab: Unit Testing Generative AI Applications

    Lecture Content

    • Fundamentals of Retrieval-Augmented Generation (RAG) architectures 
    • Security in RAG systems (vector database poisoning, grounding, data leakage) 
    • Secure introduction to Function Calling and Extensions with Gemini

    Learning Objectives

    • Understand RAG architecture and its associated security implications
    • Implement best practices for grounding and securing data sources in RAG systems

    Lab Content

    • Lab: Multimodal Retrieval Augmented Generation (RAG) Using the Vertex AI Gemini API
    • Lab: Introduction to Function Calling with Gemini

    Certification Details of Vertex AI and Generative AI Security

      CloudThat Course Completion Certificate will be awarded to all learners who complete the training.

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    Course ID: 28725

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    FAQs for Vertex AI and Generative AI Security

    To provide the skills necessary to adopt and integrate Google’s AI technologies securely and responsibly.

    Yes, Module 06 is specifically dedicated to mitigating prompt hacking and injection attacks.

    Retrieval-Augmented Generation (RAG) is a method of grounding models in external data; Module 08 covers how to secure this architecture.

    Yes, the course includes 7 hands-on labs using tools like the Gemini API.

    While it involves technical configuration and API usage, it focuses on the security aspects rather than general development.

    Yes, Module 03 focuses on encryption strategies for protecting sensitive AI data.

    Module 05 and 06 introduce the fundamentals of AI Safety and safeguarding techniques.

    Yes, Module 04 teaches how to set up logging, monitoring, and alerts for Vertex AI.

    AI engineers building apps and security engineers responsible for protecting the organization's cloud environment.

    It is a 2-day instructor-led deep dive.

    Enquire Now