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Certified Ethical Hacker (CEH): Unit 8

Certified Ethical Hacker (CEH): Unit 8

This course is part of Certified Ethical Hacker (CEH) Specialization

Instructors: Pearson

Included with

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1 module

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

7 hours to complete

Flexible schedule

Learn at your own pace

1 module

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

7 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

Develop a foundational understanding of AI threats and LLM security frameworks.
Master techniques to mitigate risks such as prompt injection and training data poisoning.
Implement best practices for securing AI supply chains and protecting sensitive information.
Enhance AI system resilience through proactive security testing and incident response strategies.

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

7 assignments

Taught in English

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Build your subject-matter expertise

This course is part of the Certified Ethical Hacker (CEH) Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There is 1 module in this course

This course is designed to equip you with the knowledge to protect large language models (LLMs) and AI systems from emerging threats. You will explore critical security challenges such as prompt injection, training data poisoning, and model theft. You will gain insights into frameworks like MITRE ATLAS and NIST, and learn to implement best practices for securing AI ecosystems. By the end of this course, you will be proficient in identifying vulnerabilities, applying mitigation strategies, and enhancing the resilience of AI systems.

This module covers securing generative AI. It begins with an introduction to AI threats and large language model (LLM) security. You will learn about OS Top 10 for LLM applications and the MITRE ATLAS framework. You will learn about the Coalition for Secure AI and the best practices being developed by organizations like NIST and others. You will learn about prompt injection, insecure output handling, training data poisoning, model denial of service, and supply chain security. You'll also learn about other threats, like sensitive information disclosure, insecure plugin design, and excessive agency. You will learn concepts that will help you understand overreliance in AI, model theft attacks, and understanding red teaming of AI models. The module will also cover retrieval-augmented generation (RAG) and its different permutations, as well as explore tools like LangChain, LlamaIndex, LangGraph, and other orchestration libraries used with AI. You will learn how to secure embedding models, secure vector databases, and develop strategies for monitoring and incident response.

What's included

36 videos7 assignments

36 videos Total 224 minutes

Module Introduction 2 minutes
Learning objectives 1 minute
Understanding the Significance of LLMs in the AI Landscape 7 minutes
Exploring the Resources for this Course - GitHub Repositories and Others 3 minutes
Introducing Retrieval Augmented Generation (RAG) 12 minutes
Understanding the OWASP Top-10 Risks for LLMs 6 minutes
Exploring the MITRE ATLAS™ (Adversarial Threat Landscape for Artificial-Intelligence Systems) Framework 6 minutes
Understanding the NIST Taxonomy and Terminology of Attacks and Mitigations 7 minutes
Learning objectives 1 minute
Defining Prompt Injection Attacks 12 minutes
Exploring Real-life Prompt Injection Attacks 4 minutes
Using ChatML for OpenAI API Calls to Indicate to the LLM the Source of Prompt Input 10 minutes
Enforcing Privilege Control on LLM Access to Backend Systems 6 minutes
Best Practices Around API Tokens for Plugins, Data Access, and Function-level Permissions 3 minutes
Understanding Insecure Output Handling Attacks 3 minutes
Using the OWASP ASVS to Protect Against Insecure Output Handling 5 minutes
Learning objectives 1 minute
Understanding Training Data Poisoning Attacks 4 minutes
Exploring Model Denial of Service Attacks 3 minutes
Understanding the Risks of the AI and ML Supply Chain 9 minutes
Best Practices when Using Open-Source Models from Hugging Face and Other Sources 13 minutes
Securing Amazon BedRock, SageMaker, Microsoft Azure AI Services, and Other Environments 16 minutes
Learning objectives 1 minute
Understanding Sensitive Information Disclosure 3 minutes
Exploiting Insecure Plugin Design 3 minutes
Avoiding Excessive Agency 4 minutes
Learning objectives 1 minute
Understanding Overreliance 5 minutes
Exploring Model Theft Attacks 5 minutes
Understanding Red Teaming of AI Models 14 minutes
Learning objectives 1 minute
Understanding the RAG, LangChain, Llama Index, and AI Orchestration 17 minutes
Securing Embedding Models 10 minutes
Securing Vector Databases 12 minutes
Monitoring and Incident Response 8 minutes
Course Summary 8 minutes

7 assignments Total 210 minutes

Introduction to AI Threats and LLM Security Quiz 30 minutes
Understanding Prompt Injection & Insecure Output Handling Quiz 30 minutes
Training Data Poisoning, Model Denial of Service & Supply Chain Vulnerabilities Quiz 30 minutes
Sensitive Information Disclosure, Insecure Plugin Design, and Excessive Agency Quiz 30 minutes
Overreliance, Model Theft, and Red Teaming AI Models Quiz 30 minutes
Protecting Retrieval Augmented Generation (RAG) Implementations Quiz 30 minutes
End of Course Assessment 30 minutes

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Instructors

Pearson

268 Courses 47,449 learners

Offered by

Pearson

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Frequently asked questions

Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.

If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.

Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.

Certified Ethical Hacker (CEH): Unit 8

Certified Ethical Hacker (CEH): Unit 8

What you'll learn

Skills you'll gain

Tools you'll learn

Details to know

See how employees at top companies are mastering in-demand skills

Build your subject-matter expertise

There is 1 module in this course