What you'll learn:
- Review AI-generated C# and .NET code for common security risks before accepting it.
- Use GitHub Copilot, ChatGPT, Cursor, or similar AI coding tools with a secure review workflow.
- Apply OWASP-informed checks for broken access control, injection, insecure defaults, and vulnerable dependencies.
- Harden ASP.NET Core APIs using safer input validation, data access, authentication, and authorization patterns.
- Protect secrets, connection strings, API keys, and environment-specific configuration.
- Generate and review security-focused tests without trusting weak AI-generated test coverage.
- Use dependency checks, scanning, and secure shipping checklists before merge or deployment.
- Build a repeatable Plan, Generate, Inspect, Fix, Test, Checkpoint workflow for AI-assisted development.
AI coding tools can help you build faster, but faster code is not automatically safer code. When developers accept generated output too quickly, they can ship applications with weak validation, broken access control, exposed secrets, risky dependencies, insecure defaults, and other vulnerabilities that are easy to miss during rapid development.
Secure Vibe Coding with GitHub Copilot, C#, and .NET is a practical course for developers who use AI coding tools such as GitHub Copilot, ChatGPT, Cursor, Claude Code, Windsurf, or similar assistants to generate, review, and improve application code. The goal is simple: help you move quickly with AI-assisted development while keeping security, code quality, and developer judgment in the workflow.
This is not a penetration testing course, and it is not designed only for cybersecurity specialists. It is built for developers, software engineers, technical builders, and team leads who want to use AI coding tools responsibly while reducing the risk of insecure code reaching production.
Using hands-on examples in C#, .NET, ASP.NET Core, Entity Framework Core, and GitHub Copilot, you will work through a realistic application workflow where AI helps generate features, tests, reviews, and security improvements. Along the way, you will learn how to inspect AI-generated code critically, recognize insecure patterns, and apply safer development practices before accepting or merging generated changes.
You will explore practical security concerns that commonly appear in AI-assisted development, including insecure input handling, missing authorization checks, unsafe assumptions about authentication, weak data access patterns, exposed secrets, dependency risk, and false confidence from shallow AI-generated tests. You will also learn how to use lightweight security checks, review prompts, checkpoints, and secure shipping checklists to improve the reliability of your workflow.
The course follows a repeatable secure development process:
Plan → Generate → Inspect → Fix → Test → Checkpoint
Tools and Technologies Covered
C# and .NET
ASP.NET Core Web API
Entity Framework Core
SQLite
GitHub Copilot
AI-assisted code review prompts
Secure coding checklists
Dependency review workflows
Security-focused testing
OWASP-informed secure development practices
Prerequisites
You should have basic experience reading and running C# or .NET code. Familiarity with Web APIs, HTTP requests, JSON, controllers, and databases will be helpful.
Access to an AI coding assistant such as GitHub Copilot, ChatGPT, Cursor, Claude Code, or a similar tool is useful, but the security review habits taught in this course apply to tools alike.
No prior experience in cybersecurity, ethical hacking, or penetration testing is required.
By the End of This Course
By the end of this course, you will be able to use AI coding tools more responsibly, review generated code with a security mindset, identify common application security risks, and follow a repeatable workflow for building, reviewing, testing, and shipping safer applications.
You will not just learn how to generate code faster. You will learn how to inspect, improve, and trust your code more carefully before it ships.
