Introduction to LLM Vulnerabilities

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1:25:33

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01 - About This Course

01 - Meet your instructor.mp4

01:23

02 - 1. Foundations of Large Language Models

01 - How do LLMs work in applications.mp4

05:23

02 - How are LLMs created.mp4

07:57

03 - What are LLMs and how do they work.mp4

05:19

03 - 2. Language Model Applications

01 - Introduction to language model applications.mp4

01:04

02 - Common types of generative AI applications.mp4

03:34

03 - Overview of an API-based application.mp4

04:55

04 - Overview of an embedded-model application.mp4

04:35

05 - What is a multi-modal application.mp4

06:25

06 - Challenges and highlights of AI applications.mp4

06:13

07 - Summary.mp4

01:31

04 - 3. Model Vulnerabilities

01 - Introduction to model-based vulnerabilities.mp4

00:29

02 - Prompt injection.mp4

03:46

03 - Insecure output handling.mp4

05:11

04 - Model theft.mp4

03:48

05 - Model replication.mp4

03:28

06 - Summary.mp4

00:47

05 - 4. System Vulnerabilties

01 - Introduction to system vulnerabilities.mp4

00:47

02 - Application vulnerabilities.mp4

03:43

03 - Sensitive information disclosure.mp4

04:50

04 - Insecure plugin design.mp4

03:51

05 - Summary.mp4

01:01

06 - Conclusion

01 - Conclusion.mp4

01:22

02 - Other types of vulnerabilities.mp4

04:11

Description

As large language models (LLMs) revolutionize the AI landscape, it’s becoming crucial to understand and address the unique security challenges they present. In this comprehensive course from Pragmatic AI Labs, instructor Alfredo Deza covers the technical knowledge and skills required to identify, mitigate, and prevent security vulnerabilities in your LLM applications. Explore common security threats, such as model theft, prompt injection, and sensitive information disclosure, and learn practical techniques to prevent attackers from exploiting vulnerabilities and compromising your systems. Discover best practices for secure plug-in design, input validation, and sanitization, as well as how to actively monitor dependencies for security updates and vulnerabilities. Along the way, Alfredo outlines strategies for protecting AI systems against unauthorized access and data breaches. By the end of the course, you’ll be prepared to deploy robust, secure, and effective AI solutions.

Note: This course was created by Pragmatic AI Labs. We are pleased to host this training in our library.

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