Generative AI Security Masterclass: Threats & Defense - 2025

Secure Generative AI Before It Breaks You — Master Risks, Defenses, and Real-World Protection

What you'll learn
- The fundamentals of generative AI and Large Language Models (LLMs)
- The top security threats: data leakage, prompt injection, deepfakes, hallucinations
- How to perform AI threat modeling using STRIDE and DREAD
- Key differences between public and private LLMs — and when to use each
- How to create and implement an AI security policy
- Hands-on strategies to defend against AI misuse and insider risk
- Practical examples of real-world incidents and how to prevent them

Requirements
- A basic understanding of AI or cybersecurity concepts
- No coding experience required
- Curiosity and commitment to building secure AI systems

Description
Welcome to the Generative AI Security Masterclass — your practical guide to navigating the risks, threats, and defenses in the age of AI.

Generative AI tools like ChatGPT, Bard, Claude, and Midjourney are changing the way we work, code, communicate, and innovate. But with this incredible power comes a new generation of threats — ones that traditional security frameworks weren’t designed to handle.

This course is designed to help youunderstand and manage the unique security risks posed by generative AI and Large Language Models (LLMs)— whether you're a cybersecurity expert, tech leader, risk manager, or just someone working with AI in your daily operations.

What You’ll Learn in This Course

What generative AI and LLMs are — and how they actually work

The full range of AI security risks: data leakage, model hallucinations, prompt injection, unauthorized access, deepfake abuse, and more

How to identify and prioritize AI risks usingthreat modeling frameworkslike STRIDE and DREAD

The difference betweenpublic vs. private LLMs, and how to choose the right deployment for your security and compliance needs

How to create a secure AI usage policy for your team or organization

Step-by-step strategies to preventAI-powered phishing, malware generation, and supply chain attacks

Best practices forsandboxing,API protection, andreal-time AI monitoring

Why This Course Stands Out

This is not just another theoretical AI class.

You’ll explorereal-world security incidents, watch hands-on demos of prompt injection attacks, and build your owncustom AI security policyyou can actually use.

By the end of this course, you’ll be ready to:

Assess the risks of any AI system before it’s deployed

Communicate AI threats and solutions with confidence to your team or executives

Implement technical and governance controls that actually work

Lead the secure adoption of AI tools in your business or organization

Who This Course Is For

This course is for anyone looking to build or secure generative AI systems, including:

Cybersecurity analysts, architects, and engineers

CISOs, CTOs, and IT leaders responsible for AI adoption

Risk and compliance professionals working to align AI with regulatory standards

Developers and AI/ML engineers deploying language models

Product managers, legal teams, and business stakeholders using AI tools

Anyone curious about AI security, even with minimal technical background

No Technical Experience Required

You don’t need to be a programmer or a machine learning expert. If you understand basic cybersecurity principles and have a passion for learning about emerging threats, this course is for you.

Course Project: Your Own AI Security Policy

You’ll apply what you’ve learned by building a generative AI security policy from scratch — tailored for real-world use inside a company, government, or startup.

By the End of This Course, You’ll Be Able To:

Recognize and mitigate generative AI vulnerabilities

Securely integrate tools like ChatGPT and other LLMs

Prevent insider misuse and external attacks

Translate technical threats into strategic action

Confidently lead or contribute to responsible AI adoption

Who this course is for:
- Cybersecurity professionals: Analysts, engineers, architects, red/blue teams
- CISOs and IT leaders: Decision-makers responsible for secure AI adoption
- Compliance and risk officers: Aligning AI with legal, regulatory, and internal frameworks
- AI and IT specialists: Developers, ML engineers, and sysadmins working with LLMs
- Legal advisors, product managers, and innovators looking to understand secure AI use
- Anyone with a basic understanding of AI and cybersecurity who wants to take their knowledge deeper
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