AI Penetration Testing

Master the methodology and tools for penetration testing AI and machine learning systems. Learn to probe ML models for adversarial vulnerabilities, fuzz AI-powered APIs, test inference pipelines, and write professional security assessment reports that help organizations harden their AI deployments.

Start Course → Model Testing
6
Lessons
25+
Examples
~3hr
Total Time
🔧
Hands-On

What You'll Learn

By the end of this course, you will be able to plan and execute penetration tests specifically targeting AI and ML systems.

🔍

AI Pentest Methodology

Learn a structured methodology for scoping, planning, and executing penetration tests against AI systems.

🤖

Model Security Testing

Test ML models for adversarial robustness, data leakage, model extraction, and other AI-specific vulnerabilities.

🔐

API & Infrastructure

Fuzz AI-powered APIs, test authentication, probe rate limits, and assess the security of ML infrastructure.

📄

Report Writing

Write professional penetration test reports with clear findings, risk ratings, and actionable remediation guidance.

Course Lessons

Follow the lessons in order to build comprehensive AI pentesting skills.

Beginner

1. Introduction

What is AI penetration testing? Understand how it differs from traditional pentesting and the unique challenges of testing ML systems.

15 min read →
 Beginner

2. Methodology

Learn the AI pentest methodology: scoping, reconnaissance, threat enumeration, testing, exploitation, and reporting.

20 min read →
 Intermediate

3. Model Testing

Hands-on techniques for testing ML models: adversarial attacks, robustness evaluation, data extraction, and model stealing.

25 min read →
 Intermediate

4. API Testing

Test AI-powered APIs with fuzzing, injection attacks, authentication bypass, rate limit testing, and input validation checks.

20 min read →
 Intermediate

5. Infrastructure

Assess ML infrastructure security: model registries, training pipelines, GPU clusters, container security, and supply chain.

20 min read →
 Advanced

6. Best Practices

Professional report writing, continuous testing, tool selection, legal considerations, and building an AI pentest practice.

15 min read →

Prerequisites

What you need before starting this course.

Before You Begin:
  • Basic understanding of machine learning concepts
  • Familiarity with Python programming
  • General knowledge of penetration testing methodology
  • Understanding of REST APIs and web security basics