LLM Security Made Simple OWASP Top 10 for GenAI
Published 10/2026
Created by Medhat Gadallah
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Expert | Genre: eLearning | Language: English | Duration: 22 Lectures ( 3h 53m ) | Size: 2.7 GB
Master Prompt Injection, RAG Security, AI Agents, Red Teaming, and Secure Generative AI Application Design
What you’ll learn
Understand how LLM and Generative AI applications work and where their major security boundaries exist.
Identify the OWASP Top 10 security risks affecting LLM and Generative AI applications.
Recognize and mitigate Prompt Injection, sensitive data exposure, poisoning, unsafe output handling, and excessive AI agency.
Secure RAG pipelines, vector databases, AI agents, tools, MCP integrations, prompts, and sensitive data.
Apply threat modeling, guardrails, access controls, monitoring, and defense-in-depth to Generative AI systems.
– Test and evaluate LLM applications using practical AI security testing and red-team techniques.
Requirements
No previous LLM security experience is required.
Basic computer and internet knowledge is enough to start.
Basic understanding of software applications is helpful but not mandatory.
Cybersecurity experience is helpful, but beginners are welcome.
Basic programming knowledge can help with practical examples but is not required to understand the core concepts.
– Most importantly, bring curiosity about AI, cybersecurity, and how modern Generative AI applications can be protected.
Description
This course contains the use of artificial intelligence
Generative AI is rapidly moving from simple chatbots into real applications that can search company knowledge, call tools, access databases, generate code, interact with APIs, and even perform actions autonomously.
That creates an entirely new security challenge.
LLM Security Made Simple: OWASP Top 10 for GenAI is a beginner-friendly practical course designed to help you understand how modern Generative AI systems can fail, how attackers can abuse them, and how developers and security professionals can build stronger defenses.
You will begin by understanding how Large Language Models and LLM-powered applications actually work, including prompts, system instructions, APIs, RAG, embeddings, vector databases, tools, and AI agents.
From there, you will explore theOWASP Top 10 for LLM and Generative AI applications, including Prompt Injection, Sensitive Information Disclosure, Supply Chain risks, Data and Model Poisoning, Improper Output Handling, Excessive Agency, System Prompt Leakage, Vector and Embedding Weaknesses, Misinformation, and Unbounded Consumption.
Throughout the course, you will learn about
LLM and Generative AI application architecture
AI threat modeling and attack surfaces
Prompt Injection and indirect Prompt Injection
Sensitive data and credential leakage
AI supply-chain security
Data and model poisoning
Secure handling of LLM-generated output
AI agents and excessive permissions
System Prompt Leakage
RAG and vector database security
Hallucinations and misinformation
Token abuse and Denial-of-Wallet attacks
AI agents, tools, and MCP security
LLM security testing and AI red teaming
Input and output guardrails
Authentication, authorization, and secrets
Logging and security monitoring
Secure AI development lifecycle
Defense-in-depth architecture
Practical security exercises and a final capstone project
The course does not treat AI security as simply adding a filter around a chatbot. Instead, you will learn how security applies across data, prompts, models, retrieval, tools, permissions, outputs, infrastructure, and monitoring.
You will also bring everything together in a practical capstone where you review and secure a vulnerable Generative AI application. The curriculum specifically culminates in attack-surface mapping, threat modeling, securing RAG and agent permissions, implementing controls, red teaming, and producing a security assessment.
No previous LLM security knowledge is required. Concepts are introduced gradually, with practical examples and security scenarios designed to make difficult topics easier to understand.
Whether you are a developer, cybersecurity learner, AI engineer, AppSec professional, or simply interested in understanding the security risks behind modern Generative AI systems, this course will give you a structured foundation for continuing your journey into AI security.
Start learning how to design, test, and defend more secure Generative AI applications.
Who this course is for
Beginners interested in AI and cybersecurity.
Cybersecurity students who want to understand LLM and Generative AI security.
Software developers building AI-powered applications.
AI and LLM developers who want to build more secure systems.
Application Security and cybersecurity professionals expanding into AI security.
Prompt engineers working with LLM-powered systems.
Developers building RAG applications and AI agents.
Technical professionals who need to understand the risks of adopting Generative AI.
– Hobby learners interested in understanding how AI applications can be attacked and defended.
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