• views: 240
• date: 27 May 2026
• posted by: 0nelove

Secure AI apps against prompt injection, broken auth, data leaks, tool abuse, and insecure defaults.
What you'll learn
⚡ Identify common security risks in AI-generated and vibe-coded applications
⚡ Understand prompt injection, indirect prompt injection, and tool abuse in AI agents
⚡ Secure AI agents against broken authentication, authorization, and data leaks
⚡ Reduce blast radius with RBAC, tool validation, and clear data boundaries
⚡ Recognize secrets exposure, insecure defaults, and dependency risks before deployment
⚡ Use security checks and review workflows when building fast with AI tools
Requirements
❗ Basic understanding of web applications is helpful.
❗ Some experience with coding or AI-assisted development will make the course easier to follow.
❗ No advanced cybersecurity background is required.
❗ You should be interested in building AI apps and agents more securely.
Description
AI-assisted development makes it easier than ever to build apps quickly. But it also makes it easier to ship security mistakes quickly.
This course is about securing modern AI-powered apps and web-based AI agents before they become a real problem. You will work through the security risks that appear when a normal web application starts using LLM workflows, tool calling, memory, user data, cloud access, and backend actions.
Instead of only talking about theory, the course follows a practical AI agent application and shows how it can break in realistic ways. You will see how prompt injection, indirect prompt injection, broken access control, excessive permissions, secrets exposure, and data exfiltration can happen in real systems.
You will also learn how to fix these problems with practical defenses: RBAC, tool validation, explicit data boundaries, safer permissions, human-in-the-loop checks, and better review workflows before deployment.
The goal is not to make you paranoid about AI development. The goal is to help you build faster without ignoring the security basics that matter.
By the end of the course, you will understand how traditional application security and AI agent security connect, where vibe-coded apps often go wrong, and how to reduce the risk before shipping AI-powered products.
Who this course is for
⭐ Developers building AI-powered apps, AI agents, or vibe-coded products.
⭐ Security engineers and AppSec teams who want to understand modern AI agent risks.
⭐ Engineering managers, platform teams, and technical leaders responsible for secure AI adoption.
⭐ Anyone who wants to build faster with AI without ignoring security fundamentals.
Homepage

https://anonymz.com/?
https://www.udemy.com/course/ai-security-for-vibe-coders

   
   
   

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