Owasp Top 10 For Llms

Posted By: ELK1nG

Owasp Top 10 For Llms
Published 5/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 416.10 MB | Duration: 1h 54m

Learn the OWASP Top 10 for LLMs | Gain knowledge on AI Security

What you'll learn

Learn the OWASP Top 10 for LLMs

Explore the foundational principles of the Open Web Application Security Project.

Understand the core architecture, functionality, and risks associated with Large Language Models.

Learn to identify and mitigate vulnerabilities from malicious inputs that can alter LLM behavior.

Ensure safe handling and rendering of LLM outputs to prevent unintended data leaks.

Prevent and respond to attacks aiming to corrupt the data used to train LLMs.

Tackle threats that aim to overload or disrupt LLM services, ensuring availability.

Address risks introduced through third-party services and dependencies.

Prevent unintended exposure of sensitive data through LLM interactions.

Securely design and implement plugins or extensions.

Manage and limit the autonomous decision-making capabilities of LLMs.

Educate on the risks and limitations of over-dependence on LLM.

Protect LLM intellectual property from unauthorized access and duplication.

Requirements

Willingness to learn cool stuff!

Basic IT Knowledge

Description

OWASP Top 10 for LLMs by Christopher Nett is a meticulously organized Udemy course designed for IT professionals aiming to master the OWASP Top 10 for LLMs to build, protect and exploit Large Language Models. This course systematically guides you from the basis to advanced concepts of the OWASP Top 10 for LLMs.By mastering the OWASP Top 10 for LLMs, you're developing expertise in essential topics in today's cybersecurity landscape. Through this course, you'll develop expertise in attacking and securing LLMs, a comprehensive and complex topic widely recognized in the industry.This deep dive into the OWASP Top 10 for LLMs equips you with the skills necessary for a cutting-edge career in cybersecurity.Key Benefits for you:OWASP Basics: Explore the foundational principles of the Open Web Application Security Project.LLMs Basics: Understand the core architecture, functionality, and risks associated with Large Language Models.LLM01 - Prompt Injection: Learn to identify and mitigate vulnerabilities from malicious inputs that can alter LLM behavior.LLM02 - Insecure Output Handling: Ensure safe handling and rendering of LLM outputs to prevent unintended data leaks.LLM03 - Training Data Poisoning: Prevent and respond to attacks aiming to corrupt the data used to train LLMs.LLM04 - Model Denial of Service: Tackle threats that aim to overload or disrupt LLM services, ensuring availability.LLM05 - Supply Chain Vulnerabilities: Address risks introduced through third-party services and dependencies.LLM06 - Sensitive Information Disclosure: Prevent unintended exposure of sensitive data through LLM interactions.LLM07 - Insecure Plugin Design: Securely design and implement plugins or extensions.LLM08 - Excessive Agency: Manage and limit the autonomous decision-making capabilities of LLMs.LLM09 - Overreliance: Educate on the risks and limitations of over-dependence on LLM.LLM10 - Model Theft: Protect LLM intellectual property from unauthorized access and duplication.

Overview

Section 1: Introduction

Lecture 1 Welcome

Lecture 2 Course Slides

Lecture 3 IMPORTANT - Basics

Lecture 4 IMPORTANT - Demos

Section 2: Basics - Large Language Models (LLMs)

Lecture 5 What is an LLM?

Lecture 6 What is a Prompt?

Lecture 7 Architecture of an LLM

Section 3: Basics - OWASP

Lecture 8 What is OWASP?

Lecture 9 OWASP Top 10 - Web Application Security Risks

Lecture 10 OWASP Top 10 - API Security Risks

Lecture 11 OWASP Top 10 - LLM Security Risks

Section 4: LLM01: Prompt Injection

Lecture 12 Prompt Injection

Lecture 13 Countermeasures

Lecture 14 Lab Setup

Lecture 15 Demo

Section 5: LLM02: Insecure Handling Output

Lecture 16 Insecure Handling Output

Lecture 17 Countermeasures

Lecture 18 Demo

Section 6: LLM03: Training Data Poisoning

Lecture 19 Training Data Poisoning

Lecture 20 Countermeasures

Section 7: LLM04: Model Denial of Service

Lecture 21 Model Denial of Service

Lecture 22 Countermeasures

Section 8: LLM05: Supply Chain Vulnerabilities

Lecture 23 Supply Chain Vulnerabilities

Lecture 24 Countermeasures

Lecture 25 Demo

Section 9: LLM06: Sensitive Information Disclosure

Lecture 26 Sensitive Information Disclosure

Lecture 27 Countermeasures

Section 10: LLM07: Insecure Plugin Design

Lecture 28 Insecure Plugin Design

Lecture 29 Countermeasures

Section 11: LLM08: Excessive Agency

Lecture 30 Excessive Agency

Lecture 31 Countermeasures

Lecture 32 Demo

Section 12: LLM09: Overreliance

Lecture 33 Overreliance

Lecture 34 Countermeasures

Section 13: LLM10: Model Theft

Lecture 35 Model Theft

Lecture 36 Countermeasures

Section 14: Bonus

Lecture 37 Bonus

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