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Matteo Dora and Luca Martial

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.

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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:

1. Explore the nuances of LLM performance evaluation, and understand the differences between benchmarking foundation models and testing LLM applications.

2. Get an overview of fundamental LLM application vulnerabilities and how they affect real-world deployments.

3. Gain hands-on experience with both manual and automated LLM red-teaming methods.

4. See a full demonstration of red-teaming assessment, and apply the concepts and techniques covered throughout the course.

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

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What's inside

Syllabus

Red Teaming LLM Applications
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: 1. Explore the nuances of LLM performance evaluation, and understand the differences between benchmarking foundation models and testing LLM applications. 2. Get an overview of fundamental LLM application vulnerabilities and how they affect real-world deployments. 3. Gain hands-on experience with both manual and automated LLM red-teaming methods. 4. See a full demonstration of red-teaming assessment, and apply the concepts and techniques covered throughout the course. After completing this course, you will have a fundamental understanding of how to experiment with LLM vulnerability identification and evaluation on your own applications.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Develops testing skills on emerging AI models, which is an in-demand skill in the tech industry
Taught by instructors who are recognized for their work in LLM safety
Teaches industry-proven red teaming techniques, which can help you enhance the robustness of real-world LLM applications
Offers hands-on experience with both manual and automated LLM red-teaming methods, which can help you gain a deep understanding of the vulnerabilities of these applications
Provides a full demonstration of red-teaming assessment, which can help you understand how to apply the concepts and techniques you learn
This course is intended for those who are already familiar with LLM applications and wish to improve the security of these applications

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Red Teaming LLM Applications with these activities:
Review 'Introduction to Machine Learning by Ethem Alpaydin
Provides a strong theoretical overview of machine learning to better grasp the content of the course.
Show steps
  • Read the first two chapters to build a foundation.
  • Summarize the various approaches to machine learning.
  • Describe the core algorithms of supervised and unsupervised learning.
Review Fundamental LLM Applications
Refresh your understanding of the core applications and capabilities of LLM models.
Show steps
  • Study the different types of LLM applications, such as chatbots, language translators, and content generators.
  • Summarize the benefits and challenges of using LLM systems.
Organize Course Notes and Resources
Establish a system to effectively manage and review the course materials.
Show steps
  • Create a designated folder or notebook for course-related materials.
  • Regularly download and organize lecture notes, slides, and assignments.
  • Bookmark important websites and resources for easy access.
Three other activities
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Explore Benchmarking Foundation Models with Hugging Face
Gain familiarity with Hugging Face and learn to evaluate the performance of different LLM models.
Browse courses on Hugging Face
Show steps
  • Set up a Hugging Face account and explore the model hub.
  • Select an appropriate evaluation metric and load a suitable dataset.
  • Run benchmark tests on different LLM models and analyze the results.
Work through LLM Vulnerability Assessment exercises
Conduct practical assessments of chatbot models to gain hands-on experience in identifying vulnerabilities.
Browse courses on Security Testing
Show steps
  • Simulate user queries and test for vulnerabilities.
  • Compose queries to test specific attack vectors.
  • Analyze system reactions to identify exploitability.
Create a Vulnerability Report for a Sample LLM Application
Develop a comprehensive report showcasing your ability to analyze LLM vulnerabilities and communicate findings effectively.
Browse courses on Vulnerability Analysis
Show steps
  • Select a sample LLM application and conduct a thorough assessment.
  • Identify and classify discovered vulnerabilities.
  • Write a detailed report outlining the vulnerabilities, their impact, and mitigation strategies.

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