Special offers now — see discounted courses.
day
:
hour
:
min
:
sec
See special offers
Introduction to LLM Vulnerabilities

Introduction to LLM Vulnerabilities

1h 25mIntermediate2024-09-16

Authors

Pragmatic AI Labs

Pragmatic AI Labs

Alfredo Deza

Alfredo Deza

Course details

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.

Skills covered

Vulnerability ManagementNatural Language Processing (NLP)CybersecurityArtificial Intelligence (AI)One-Off

Concepts

About This Course

  • 01 - Meet your instructor

1. Foundations of Large Language Models

  • 02 - How do LLMs work in applications
  • 03 - How are LLMs created
  • 04 - What are LLMs and how do they work

2. Language Model Applications

  • 05 - Introduction to language model applications
  • 06 - Common types of generative AI applications
  • 07 - Overview of an API-based application
  • 08 - Overview of an embedded-model application
  • 09 - What is a multi-modal application
  • 10 - Challenges and highlights of AI applications
  • 11 - Summary

3. Model Vulnerabilities

  • 12 - Introduction to model-based vulnerabilities
  • 13 - Prompt injection
  • 14 - Insecure output handling
  • 15 - Model theft
  • 16 - Model replication
  • 17 - Summary

4. System Vulnerabilties

  • 18 - Introduction to system vulnerabilities
  • 19 - Application vulnerabilities
  • 20 - Sensitive information disclosure
  • 21 - Insecure plugin design
  • 22 - Summary

Conclusion

  • 23 - Conclusion
  • 24 - Other types of vulnerabilities

About us

LyndaKade is a leading learning platform that helps people learn business, software, technology, and creative skills to achieve personal and professional goals.

Phone numberAparat ChannelTelegram SupportTelegram ChannelInstagram Page

All rights to this site belong to LyndaKade.

Terms of Service|Privacy Policy

نماد الکترونیک enamad در صورت اتصال با آی‌پی داخل کشور، نمایش داده خواهد شد.
logo-samandehi - لوگو ساماندهی
Zarinpal
Zibal