Red Teaming LLM Applications

Learn to identify and evaluate vulnerabilities in large language model (LLM) applications.

What you’ll learn in this course

Learn how to test and find vulnerabilities in your LLM applications to make them safer. In this course, you’ll attack various chatbot applications using prompt injections to see how the system reacts and understand security failures. LLM failures can lead to legal liability, reputational damage, and costly service disruptions. This course helps you mitigate these risks proactively. Learn industry-proven red teaming techniques to proactively test, attack, and improve the robustness of your LLM applications.

In this course:

  • Explore the nuances of LLM performance evaluation, and understand the differences between benchmarking foundation models and testing LLM applications.
  • Get an overview of fundamental LLM application vulnerabilities and how they affect real-world deployments.
  • Gain hands-on experience with both manual and automated LLM red-teaming methods.
  • See a full demonstration of red-teaming assessment, and apply the concepts and techniques covered throughout the course.


  1. Introduction
  2. Overview of LLM Vulnerabilities
  3. Red Teaming LLMs
  4. Red Teaming at Scale
  5. Red Teaming LLMs with LLMs
  6. A Full Red Teaming Assessment
  7. Conclusion

After completing this course, you will have a fundamental understanding of how to experiment with LLM vulnerability identification and evaluation on your own applications.

Price Free
Language English
Duration 1 Hour
Certificate No
Course Pace Self Paced
Course Level Advanced
Course Category LLM
Course Instructor DeepLearning.AI
LLMRed Teaming LLM Applications