Generative AI Risks & Cybersecurity: LLM Security (Udemy.com)
Data Poisoning, Model Bias, Prompt Injection, AI Ethics & Governance | Protect AI Systems from Cyber Threats
Created by: Dr. Amar Massoud
Last updated September 2026
What you will learn
- Understand the core concepts of generative AI and associated cybersecurity risks.
- Identify and analyze potential vulnerabilities within AI systems.
- Learn strategies to mitigate risks including data poisoning and model bias.
- Explore ethical considerations and best practices in AI development and usage.
- Apply AI governance frameworks and establish security controls to protect generative AI deployments
How it compares
Against the other 523 rated Udemy courses in Hacking on CourseDuck:
- Rating4.4 out of 5higher than 33% of them
- Reviews4,435#53 of 524 by number of reviews
- Length5 hoursshorter than 49% of them
- Last updatedSeptember 2026more recently than 98% of them
Course Description
The course "Risks and Cybersecurity in Generative AI" offers a comprehensive exploration into the intersection of artificial intelligence and cybersecurity. This course is designed to provide you with a thorough understanding of the potential risks and security measures necessary for deploying generative AI technologies safely and responsibly.
Starting with an introduction to the basics of AI and generative models, you will learn about the broad applications and benefits of generative AI, followed by an initial look at AI security considerations. The course progresses into a detailed examination of core cybersecurity risks such as data privacy, breaches at AI service providers, and the evolution of threat actors, equipping you with strategies to protect sensitive information and mitigate risks.
Further, you will delve into specific attack vectors and vulnerabilities unique to AI, including data leakage, prompt injections, and the challenges of inadequate sandboxing. Each module is structured to provide practical knowledge through real-world examples and demonstrative sessions, enhancing your learning experience.
The course also addresses network-level risks and AI-specific attacks, covering critical areas like Server Side Request Forgery (SSRF), DDoS attacks, data poisoning, and model bias. The final modules focus on legal and ethical considerations, guiding you through navigating intellectual property challenges and promoting ethical guidelines in AI development and usage.
By the end of this course, you will be well-prepared to assess, address, and advocate for robust cybersecurity practices in the field of generative AI, ensuring these technologies are developed and deployed with the highest standards of security and ethical considerations.
Instructor Details
- 4.4 Rating
4,435 Reviews
Dr. Amar Massoud
PhD in computer science and IT manager with 36 years technical experience in various fields including IT Security, IT Governance, IT Service Management , Software Development, Project Management, Business Analysis and Software Architecture. I hold 90+ IT certifications such as :
ITIL 4 Master, ITIL 3 Expert
ISO 27001 Auditor, ComptIA Security+, GSEC, CEH, ECSA, CISM, CISSP, CISA
PGMP, MSP
PMP, PMI-ACP, Prince2 Practitioner, Praxis, Scrum Master
COBIT 2019 Implementor, COBIT 5 Assessor/Implementer
TOGAF certified
Lean Specialist, VSM Specialist
CRISC, PMI RMP, ISO 31000 Risk Manager, ISO 22301 Lead Auditor
PMI-PBA, CBAP
Lean Six Sigma Black Belt, ISO 9001 Implementer
Azure Administrator, Azure DevOps Expert, AWS Practitioner
And many more.
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Reviews
By Jeremie Granat on 9/18/2026
Content looked promissing, but execution lacked. Clearly content is AI generated and lecturer did not even take time to double check results - text often overflows slides. Sentences sometime repeats in audio. Html playground - script has numerous bugs - especially in evaluating LLM responces. This is bit pathetic for security course, which stress how it is important to control outputs from AI.
By Richard Powell on 9/18/2026
At this point in the course, I see AI as much more than a tool for automation. I view it as a strategic capability that can improve decision-making, accelerate innovation, increase productivity, and create measurable business value. My understanding has also expanded to include the importance of AI governance, data quality, security, model evaluation, and responsible deployment. AI is only as valuable as the data, architecture, processes, and controls surrounding it. From a CTO/Chief Enterprise Architect perspective, I see my value in helping organizations identify where AI can produce the greatest business impact, establish the architecture and governance required to deploy it responsibly, and connect AI investments to measurable outcomes. The course has reinforced my view that the real value of AI is not simply generating information faster—it is using AI strategically to transform how an organization operates, makes decisions, manages risk, and delivers value to its customers.
By Theo Cudjoe on 9/14/2026
The content is very good, all these items are new to me and explained. I would like to see more diagrams to help explain the content. it can be difficult listening to words all the time. Diagrams would help present the content better
By Arnab Duttaray on 9/7/2026
Awesome experience. Great course ! The course content is very good. The Role plays were helpful in simulating real-world scenarios. The Labs were great for hands-on practice. Together, they reinforced the theoretical learning. The Security Takeaways at the bottom of the Labs are great tips to refer to later. The Capstone project resulted in a "AI Red Team Assessment Report". I can use this in my portfolio to showcase my learning. Also, got free coupons from the Standarity website. Overall, the experience has been very positive and enriching.
By Luis Alfredo Javier Boiero Sanders on 8/28/2026
This training is very revealing and teaches us the many security risks of AI. I see things with different eyes now!
By Florian Stendel on 8/21/2026
Meanwhile I got mixed feelings about this learning: Great things: - Very clear and precise slides and speaker - Nicely executed lab environment (although providing a docker based setup guide would be awesome, so people do not need to install things on their device for a learning) - the role plays are also nice, BUT (see not so greats) Not so great: - Although the Labs are engaging, the assessments feel like adding a big, not accounts for, time to the learning....maybe some sort of form can be added to the lab-index.html where a template for assessment is filled with the AI requests& response which people can use to cut the time for the assessment - Role Plays are way to time restricted and also not that much realistic....if I have a CEO who can write me down 2-3 paragraphs about a topic in barely seconds...he prolly not gonna need me (that said, it somehow contradicts the intent of the learning)
By Bauldoin Atembe on 8/19/2026
Had some issues with areas of using the AI prompt during labs but overall a great learning experience
By Christopher Enebeli on 8/14/2026
The course is very well specified and very well presented on Generative AI risks and cybersecurity. A very important course and full comprehensive. Great Course.
By Nishant Sharma on 6/24/2026
course has right mixture of practical and theory content. It helped me a lot in learning about risks and usage of AI in an Enterprises
By CARLO HAVERKAMP on 5/21/2026
Good informative course that gives an insight in AI security. For example, you learn attack methods, defense methods, preventive measures and also about AI regulations. The labs are quite helpful to better understand the content of the lectures. I understood too late that the lab switched from Gemini to a local Ollama LLM. Luckily Google charged only a few cents for completing the labs ;-) Minor comment: Unfortunately, in some lectures the bottom text on the slides was cut out of the video.
Quality Score
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Overall Score : 88 / 100












