This module guides learners through the essential steps to set up a functional .NET development environment. It covers installing the .NET SDK, configuring an integrated development environment, and preparing a workspace for secure development. Learners will gain the foundational skills needed to start coding effectively.

This module introduces the principles of secure vibe coding, exploring how AI-assisted development impacts software engineering. Learners will understand the risks of AI-generated code, the importance of human oversight, and a structured workflow for secure development. It equips learners with the knowledge to balance speed and safety in AI-assisted coding practices.

This module teaches learners how to effectively plan and structure a software project using AI. It covers defining requirements, generating development plans, and critically evaluating AI-generated solutions to ensure alignment with project goals. Learners will gain skills in using AI as a collaborative tool for project planning and implementation.

This module covers essential security foundations for AI-assisted development, including core security principles, OWASP guidelines, threat modeling, and risk assessment strategies. Learners will gain the knowledge to implement secure practices when working with AI-generated code and traditional application security frameworks.

This module focuses on reviewing and improving access control mechanisms in APIs, with an emphasis on identifying vulnerabilities, leveraging AI for security strategies, and implementing robust security practices. Learners will gain practical skills in evaluating AI-generated recommendations and strengthening access control systems.

This module covers essential techniques for secure input handling, validation, and search implementation. Learners will gain practical skills in protecting applications from risks associated with untrusted input and leveraging AI for secure coding practices. The content emphasizes both theoretical concepts and real-world application strategies.

This module explores the fundamentals of authentication and authorization, clarifying their roles in securing applications. It provides practical insights into identifying security gaps, implementing secure identity management, and evaluating the trade-offs between different authentication mechanisms. Learners will gain hands-on experience with tools like ASP.NET Core Identity and JWTs to strengthen application security.

This module covers best practices for managing secrets and securing software supply chains in AI-assisted development. Learners will explore how to identify and mitigate risks in dependencies and configuration files using AI tools. The focus is on implementing secure, scalable strategies for managing sensitive data and third-party packages.

This module focuses on essential security testing practices for AI-assisted development, equipping learners with the skills to evaluate and enhance the reliability of AI-generated code through structured testing and review processes.

This module explores how to implement secure software release practices using AI-driven tools and structured security reviews. Learners will gain hands-on experience in creating security checklists, configuring AI agents, and automating code analysis. The content emphasizes the integration of AI to enhance code quality and security throughout the development lifecycle.

This module helps learners consolidate their understanding of key application security concepts and provides guidance on how to continue their learning journey in secure AI-assisted development.