Threat Modeling for Agentic AI Systems with Case Study

Name: Threat Modeling for Agentic AI Systems with Case Study
Rating: 4.5 (44 reviews)

A Practical Guide to Threat Modeling Single and Multi-Agent Agentic AI Systems using MAESTRO Threat Modeling Framework

Role Play

Highest Rated

Created byRaghu The Security Expert

Last updated 4/2026

English

What you'll learn

Understand the Foundations of Agentic AI
Apply the MAESTRO Framework for Threat Modeling
Execute the Four-Step Threat Modeling Process for Agentic AI
Develop and Present a Threat Modeling Report for an Agentic AI Case Study
Explore Emerging Risks and Attack Surfaces in Agentic AI
Integrate Threat Modeling into AI System Development Lifecycle
Compare Traditional vs. Agentic AI Threat Modeling Approaches
Gain Practical Skills with Hands-On Exercises and Tools

Course content

6 sections • 27 lectures • 2h 55m total length

Introduction and Agenda6:53
Explore threat modeling for agentic ai systems, covering architectures, seven layers, risk assessment, and mitigations, using the Maestro framework in a practical case study.

Agentic AI systems - Layer 1 introduction and its Threat Landscape4:29
Agentic AI systems - Layer 2 introduction and its Threat Landscape5:06
Agentic AI systems - Layer 3 introduction and its Threat Landscape5:11
Explore the agent framework layer (layer three) of agentic AI systems, including toolkits and SDKs for data integration, and identify threats like backdoors, compromised components, input validation, supply-chain attacks.
Agentic AI systems - Layer 4 introduction and its Threat Landscape5:00
Explore deployment layer of agentic ai systems, cloud and on-premise setups, threats like compromised container images, resource hijacking, orchestration attacks, infrastructure as code manipulation, denial of service, and lateral movement.
Agentic AI systems - Layer 5 introduction and its Threat Landscape6:42
Agentic AI systems - Layer 6 introduction and its Threat Landscape8:11
Agentic AI systems - Layer 7 introduction and its Threat Landscape7:58
MAESTRO - Threat Modeling Framework for Agentic AI Systems7:49
Apply the Maestro threat modeling framework for agentic ai systems to identify adversarial attacks, prompt injection, and goal manipulation, and to prioritize risks with a risk-based approach in multi-agent environments.

4 Step Process to Threat Model an Agentic AI system3:50
Apply a four-step threat modeling process for an agentic AI system by gathering requester information, reviewing architecture, mapping data flows, and reporting threats with mitigations.
Understanding Case Study and Create Data flow Diagram14:33
Identify Agentic AI Threats using Manual Approach10:08
Identify Agentic AI Threats using Automated Approach8:37
Automated approach to identify Threats in Agentic AI parts of the system
Part 1 - Create Final Threat Modeling Report for Agentic AI System6:45
Part 2 - Create Final Threat Modeling Report for Agentic AI System7:39
Perform Threat Modeling of an Agentic AI System for ABC Corporation

Generative AI - Understanding and some use cases4:25
Generative AI - Basic Terms7:55
Understanding Model in layman terms4:53
What are Tokens and Embeddings in AI Models?7:06
Understand tokens and embeddings as the foundation of ai processing, including tokenization types (word, subword, character), converting tokens to embeddings, and feeding vectors to neural networks to generate outputs.
Let's understand the ML type, Algorithm and Model in ChatGPT3:58

Requirements

Familiarity with core cybersecurity principles (confidentiality, integrity, availability) and common threat modeling concepts (e.g., STRIDE, attack surfaces) will help learners connect new ideas more quickly.
Cybersecurity & Threat Modeling Basics
System Architecture & Design Knowledge

Description

Disclosure: This course contains the use of artificial intelligence.

AI is no longer just about models making predictions — it’s about autonomous agents making decisions, collaborating with other agents, and driving complex workflows. These agentic AI systems are powerful, but with that power comes new security and trust challenges that traditional methods simply don’t cover.

This course is built to help you bridge that gap. You’ll not only learn the core concepts of agentic AI, but also gain practical skills in threat modeling frameworks and techniques that are purpose-built for this new wave of AI.

Here’s what makes this course stand out:

Demystify Agentic AI → Learn the difference between single-agent and multi-agent systems and understand the 7 layers of agentic AI architecture.
Master the MAESTRO Framework → A structured, actionable approach to analyzing and categorizing risks unique to agentic AI.
Hands-On Threat Modeling → Work through the four-step process (identify, analyze, prioritize, mitigate) with guided examples.
Capstone Case Study → Apply everything you’ve learned to a real-world agentic AI system and create a professional threat modeling report you can showcase.

By the end of the course, you won’t just know the theory — you’ll have the confidence to spot vulnerabilities, assess risks, and recommend safeguards for agentic AI systems in real-world settings.

Whether you’re a security professional, AI engineer, or researcher, this course will give you the tools to stay ahead in the rapidly shifting landscape of AI security.

Who this course is for:

Cybersecurity Professionals and Threat Analysts
AI/ML Engineers and Developers
Cloud and Enterprise Architects
Governance, Risk, and Compliance (GRC) Professionals
Researchers, Students, and Innovators in AI Security

Threat Modeling for Agentic AI Systems with Case Study

What you'll learn

Explore related topics

Course content

Introduction1 lecture • 7min

Basics of Agentic AI Systems5 lectures • 33min

Threat Modeling for Agentic AI systems8 lectures • 50min

Case Study - Threat Model an Agentic AI system using MAESTRO and Prepare Report6 lectures • 52min

Appendix - Basics about AI, Machine Learning and its Types5 lectures • 28min

Next Steps3 lectures • 5min

Requirements

Description

Who this course is for: