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Application Security Essentials for Vibe Coders

Packt via Coursera

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Overview

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Learn how to develop secure AI-assisted applications without sacrificing development speed. Apply modern application security practices, validate AI-generated code, implement secure authentication, and automate security reviews throughout the software development lifecycle. Build the skills needed to ship secure software with confidence. This course provides a practical guide to building secure applications while using AI coding assistants, combining proven application security principles with modern AI-assisted development workflows. Through hands-on demonstrations and real-world activities, you will learn how to identify security risks early, validate AI-generated code, and integrate security throughout the software development lifecycle. You will begin by setting up your development environment and learning secure vibe coding practices before exploring threat modeling, OWASP guidance, access control, input validation, authentication, authorization, JWTs, and ASP.NET Core Identity. Throughout the course, you will compare AI-generated solutions with human security reviews while strengthening applications through secure coding techniques and defensive design. The course also covers secrets management, dependency hygiene, supply chain security, automated security testing, AI-assisted code reviews, secure coding agents, and deployment checklists. By the end of the course, you will be equipped to use AI development tools responsibly, identify and remediate security vulnerabilities, and confidently build, review, test, and deploy secure AI-assisted applications. This course is designed for software developers, .NET developers, application security engineers, DevSecOps practitioners, technical leads, and AI-assisted developers who want to build secure applications while using modern coding assistants. It is ideal for professionals seeking practical guidance on secure coding, threat modeling, authentication, AI code review, and secure software delivery. Basic knowledge of C#, .NET, and web application development is recommended. Learn through hands-on demonstrations, guided security reviews, and practical coding activities. Apply secure development practices while building and improving an AI-assisted application. Reinforce every concept through real-world security scenarios and AI-assisted development workflows. This course is based on Application Security Essentials for Vibe Coders, by Trevoir Williams. This course is licensed and distributed by Packt. All rights reserved. Packt is one of the world's most prolific publishers of cutting-edge technical content. For over two decades we've made it our mission to curate and publish the knowledge of only the very best technical experts. We focus on real-world courses that help our customers get the job done, with coverage that extends across a wide range of established and cutting-edge technical topics. If you're an individual or an organisation that embraces learning by doing, Packt is the perfect fit for you.

Syllabus

  • Introduction
    • This module provides an overview of the course structure, learning goals, and the importance of developing secure AI-assisted applications. Learners will gain insight into the target audience and strategies for effective learning throughout the course.
  • Environment Setup
    • 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.
  • Introduction to Secure Vibe Coding
    • 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.
  • Planning a Project With AI
    • 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.
  • Security Foundations for Vibe Coders
    • 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.
  • Access Control Review and Hardening
    • 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.
  • Secure Input Handling, Filtering, and Search
    • 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.
  • Authentication, Authorization, and Insecure Defaults
    • 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.
  • Secrets, Dependencies, and AI-Assisted Supply Chain Risk
    • 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.
  • Security-Focused Tests and Automated Checks
    • 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.
  • Secure Shipping Checklists and AI Security Reviews
    • 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.
  • Course Wrap-Up
    • 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.

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