Apprentice
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Adversarial ML & Security Threats
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Module 1: Introduction to Adversarial ML

Module 1: Introduction to Adversarial ML

by NSTC

February 24, 2026

About Module 1: Introduction to Adversarial ML

Module Content

Module 1: Introduction to Adversarial ML

12 Lessons

Chapter 1.1: What is Adversarial ML?

Lesson 1: Lesson 1.1.1: Introduction to Adversarial ML Concept

Lesson 2: Lesson 1.1.2: Importance in the context of AI safety

Lesson 3: Lesson 1.1.3 Real-world examples of adversarial ML

Chapter 1.2: Historical Context and Emerging Importance

Lesson 1: Lesson 1.2.1 Early research in adversarial ML

Lesson 2: Lesson 1.2.2 Milestones in adversarial attack development

Lesson 3: Lesson 1.2.3 The role of adversarial ML in current AI trends

Chapter 1.3: Types of Adversarial Threats (White-box, Black-box, Gray-box)

Lesson 1: Lesson 1.3.1 Understanding White-box Attacks

Lesson 2: Lesson 1.3.2 How Black-box Attacks operate

Lesson 3: Lesson 1.3.3 Insights into Gray-box Attacks and their challenges

Chapter 1.4: Overview of Vulnerabilities in ML Pipelines

Lesson 1: Lesson 1.4.1 Vulnerability analysis in data preprocessing

Lesson 2: Lesson 1.4.2 Model selection and training pitfalls

Lesson 3: Lesson 1.4.3 Evaluation and deployment vulnerabilities

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