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  3. Introduction to Prompt Injection Vulnerabilities

Introduction to Prompt Injection Vulnerabilities

In this course, we enter the space of Prompt Injection Attacks, a critical concern for businesses utilizing Large Language Model systems in their AI applications. By exploring practical examples and real-world implications.

Kevin Cardwell
Kevin Cardwell
Cybersecurity | core | 1 hour 30 minutes |   Published: Jan 2024
In partnership with: Coursera

    Discussions

Overview

1KSTUDENTS*
96%RECOMMEND*

This course includes:

  • 1.5 hours of on-demand video  
  • Certificate of completion  
  • Direct access/chat with the instructor 
  • 100% self-paced online 

In this course, we enter the space of Prompt Injection Attacks, a critical concern for businesses utilizing Large Language Model systems in their AI applications. By exploring practical examples and real-world implications, such as potential data breaches, system malfunctions, and compromised user interactions, you will grasp the mechanics of these attacks and their potential impact on AI systems.  As businesses increasingly rely on AI applications, understanding and mitigating Prompt Injection Attacks is essential for safeguarding data and ensuring operational continuity. This course empowers you to recognize vulnerabilities, assess risks, and implement effective countermeasures.  By the end of this course, you will be equipped with actionable insights and strategies to protect your organization's AI systems from the ever-evolving threat landscape, making you an asset in today's AI-driven business environment. 

Skills You Will Gain

Automotive Cybersecurity
Cyber Security Awareness
Cybersecuirty
Cybersecurity Implementation
Cybersecurity management
Cybersecurity Tools

Learning Outcomes (At the end of this program you will be able to)

  • Analyze and discuss various attack methods targeting Large Language Model (LLM) applications. 
  • Demonstrate the ability to identify and comprehend the primary attack method, Prompt Injection, used against LLMs.  
  • Evaluate the risks associated with Prompt Injection attacks and gain an understanding of the different attack scenarios involving LLMs. 
  • Formulate strategies for mitigating Prompt Injection attacks, enhancing their knowledge of security measures against such threats. 

Prerequisites

Learners should have knowledge of computers and their usage as part of a network, as well as familiarity with fundamental cybersecurity concepts, and proficiency in using command-line interfaces (CLI). Prior experience with programming languages (Python, JavaScript, etc.) is beneficial but not mandatory. 

Who Should Attend

This course is for anyone who wants to learn about Large Language Models and their susceptibility to attacks, such as AI Developers, Cybersecurity Professionals, Web Application Security Analysts, AI Enthusiasts.  

Curriculum

Instructors

Frequently Asked Questions

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Yes, we do offer a certification upon completion of our course to showcase your newly acquired skills and expertise.

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*Where courses have been offered multiple times, the “# Students” includes all students who have enrolled. The “%Recommended” shown is also based on this data.
1Module 1: Introduction to Large Language Model Applications
2Module 2: Reviewing the OWASP Top 10 Against LLM Applications
3Module 3: Classifying Prompt Injection Risk
4Module 4: Exploring Common Techniques of Prompt Injection Attacks
5Module 5: Mitigating the Risk of Prompt Injection Attacks

Segment 01 - Demonstration

Segment 2 - Example LLM Application

Segment 3 - Define Large Language Models (LLM)

Segment 04 - Identifying LLM Attack Methods

Segment 05 - LLM Attack

Segment 06 - Exploring the OWASP Top 10

Segment 07 -Ultimate Black Box Technology

Segment 08 - Demonstration Prompt Injection Risk

Segment 09 - Security Testing Challenges

Segment 10 -Demonstration Prompt Injection Attack Techniques

Segment 11 -Concatenation of Prompts

Segment 12 -Passive and Active Methods

Kevin Cardwell

Kevin Cardwell

Kevin Cardwell is a cybersecurity expert with extensive experience working with banks and financial institutions across the Middle East, Europe, and the UK. A former leader of a U.S. Department of Defense Red Team, he achieved an impressive 100% success rate in system compromise operations, demonstrating unparalleled expertise in identifying and exploiting vulnerabilities.

Kevin has led high-impact consulting projects, including engagements with Petroleum Development Oman and the Central Bank of Oman. His work includes the design and implementation of customized security baselines for high-profile clients such as Oman Airport Management Company (OAMC), ensuring resilient protection for critical infrastructure.

He is the author of several acclaimed cybersecurity courses and publications, including Building Virtual Pentesting Labs for Advanced Penetration Testing and Advanced Penetration Testing for Highly Secured Environments, 2nd Edition. His areas of specialization include advanced penetration testing, network defense, and security architecture.

As President of Cyber2Labs and Lead Consultant at CESI, Kevin continues to shape the cybersecurity landscape, helping organizations build strong digital defenses against emerging threats. He holds certifications such as Certified Advanced Network Defender and Certified Advanced Penetration Tester, underscoring his commitment to excellence in information security.

In addition to his hands-on expertise, Kevin is a passionate educator and instructor, dedicated to equipping learners with the knowledge and practical skills necessary to navigate the complex world of cybersecurity with confidence. He actively promotes cutting-edge cybersecurity practices and is a trusted voice in the field for both professionals and organizations.

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Segment 13 - Human Loop

Segment 14 -Principle of Least Services and Privileges__

Segment 15 -Demonstration Segregation

Segment 16 -Segregation and Isolation