Securing LLMs Online Course

Securing LLMs Online Course

This intensive workshop, led by cybersecurity expert Clint Bodungen, equips you with hands-on skills to secure enterprise-grade LLM applications against the OWASP Top 10 risks. You’ll explore unique attack vectors targeting generative models and learn practical defenses, from protecting against supply chain vulnerabilities to preventing data theft and dataset poisoning. Through interactive examples, you’ll practice filtering malicious input, sanitizing outputs, and applying strong validation methods. The workshop also emphasizes prompt engineering as a key technique to enforce secure guardrails, helping you strengthen the overall security posture of your LLM-based systems.

Who should take this course?

This course is designed for AI practitioners, developers, and cybersecurity professionals who want to learn how to secure large language models (LLMs). It’s also ideal for researchers and engineers aiming to protect AI systems from vulnerabilities, misuse, and adversarial attacks.

What you will learn

• How to safeguard your LLM apps from supply chain vulnerabilities
• Ways to prevent data poisoning, unauthorized access, and theft
• Techniques to filter malicious user input and sanitize model output
• Methods to block jailbreaking and misuse of your LLMs
• Tools and frameworks to automate security mechanisms in your stack

Course Outline

LLM Security Workshop – Tackling OWASP's Top 10 Risks Head-On

• LLM Security Workshop – Tackling OWASP's Top 10 Risks Head-On