OP 06 August, 2025 - 06:39 PM
![[Image: Screenshot-4.png]](https://i.ibb.co/cX1F1H09/Screenshot-4.png)
Requirements
- Basic understanding of how large language models (LLMs) work is helpful, but not required.
- No prior cybersecurity experience needed you’ll learn red teaming concepts from scratch.
- A curiosity to explore how AI systems can be attacked, tested, and secured!
This course takes you deep into the world of LLM security by teaching you how to attack and defend large language models using real-world techniques. You’ll learn the ins and outs of prompt injection, jailbreaks, indirect prompt attacks, and system message manipulation. Whether you're a red teamer aiming to stress-test AI systems, or a developer building safer LLM applications, this course gives you the tools to think like an adversary and defend like a pro.
We’ll walk through direct and indirect injection scenarios, demonstrate how prompt-based exploits are crafted, and explore advanced tactics like multi-turn manipulation and embedding malicious intent in seemingly harmless user inputs. You’ll also learn how to design your own testing frameworks and use open-source tools to automate vulnerability discovery.
By the end of this course, you’ll have a strong foundation in adversarial testing, an understanding of how LLMs can be exploited, and the ability to build more robust AI systems.
If you’re serious about mastering the offensive and defensive side of AI, this is the course for you.
Who this course is for:
- AI enthusiasts, prompt engineers, ethical hackers, and developers curious about LLM security and red teaming.
- Beginner to intermediate learners who want hands-on experience in testing and breaking large language models.
- Anyone building or deploying LLM-based applications who wants to understand and defend against real-world threats.
