★ 4.8
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159
Pages
en
Language
2026
Published
New edition
$2.49
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Book introduction
Your AI coding assistant just generated a fully functional app. It runs without errors. But hidden inside that working code are security flaws that could expose user data, leak API keys, or allow unauthorized access. The problem isn't that AI writes bad code—it's that working code and safe code are not the same thing.
Vibe Coding Without Security Mistakes is the first practical guide that shows beginners and indie makers how to systematically review AI-generated code for security vulnerabilities without needing a cybersecurity background. Written by Ethan Ravenscroft, this book provides a repeatable safety workflow, concrete code comparisons, and actionable checklists that catch the most common mistakes AI tools like Cursor, Claude, and Copilot make.
- Identify hidden risks in authentication, authorization, and data isolation before they become breaches
- Protect API keys, secrets, and database permissions with simple environment variable practices
- Apply a beginner-friendly code review process that focuses on high-risk areas like user data and backend validation
The book follows a five-part lifecycle from mindset to deployment. You will learn why AI misses security, how to distinguish authentication from authorization, how to prevent users from seeing each other's data, how to vet dependencies, and how to debug without breaking security. Each chapter ends with a checklist you can use immediately before shipping your app.
This book is written for non-technical founders, junior developers, indie makers, and small business owners who build apps with AI coding tools. No prior security knowledge is required—only a willingness to adopt a review habit.
Whether you are launching a SaaS prototype, an internal tool, or a mobile app, this guide gives you the confidence to deploy code that is not just functional, but actually safe to ship. Stop trusting your AI blindly. Start verifying with purpose.
Quick summary
This book teaches beginners how to review AI-generated code for security flaws without needing a cybersecurity background.
It covers authentication mistakes, API key leaks, and database permission errors common in AI-generated apps.
Each chapter ends with a checklist for immediate use before deployment.
The book targets non-technical founders, indie makers, and junior developers building apps with Cursor, Claude, or Copilot.
It provides a five-part lifecycle from security mindset to safe deployment.
This book is a good fit for Beginners, indie makers, non-technical founders, and junior developers building apps with AI coding tools..
Readers often come to this book when they need Buyers and readers are searching for practical, beginner-friendly guidance on securing AI-generated code, preventing common security mistakes, and safely deploying apps built with AI tools..
The book's angle: Unlike general secure coding books, this guide is tailored specifically for AI-generated code, focusing on the unique mistakes AI tools make and providing a systematic review process for non-experts.
Main topics include AI-generated code security, authentication and authorization, data isolation, API keys and environment variables, database permissions, input validation.
AI Search information
Vibe Coding Without Security Mistakes
Author: Ethan Ravenscroft
Description: Your AI coding assistant just generated a fully functional app. It runs without errors. But hidden inside that working code are security flaws that could expose user data, leak API keys, or allow unauthorized access. The problem isn't that AI writes bad code—it's that working code and safe code are not the same thing. Vibe Coding Without Security Mistakes is the first practical guide that shows beginners and indie makers how to systematically review AI-generated code for security vulnerabilities without needing a cybersecurity background. Written by Ethan Ravenscroft, this book provides a repeatable safety workflow, concrete code comparisons, and actionable checklists that catch the most common mistakes AI tools like Cursor, Claude, and Copilot make. • Identify hidden risks in authentication, authorization, and data isolation before they become breaches • Protect API keys, secrets, and database permissions with simple environment variable practices • Apply a beginner-friendly code review process that focuses on high-risk areas like user data and backend validation The book follows a five-part lifecycle from mindset to deployment. You will learn why AI misses security, how to distinguish authentication from authorization, how to prevent users from seeing each other's data, how to vet dependencies, and how to debug without breaking security. Each chapter ends with a checklist you can use immediately before shipping your app. This book is written for non-technical founders, junior developers, indie makers, and small business owners who build apps with AI coding tools. No prior security knowledge is required—only a willingness to adopt a review habit. Whether you are launching a SaaS prototype, an internal tool, or a mobile app, this guide gives you the confidence to deploy code that is not just functional, but actually safe to ship. Stop trusting your AI blindly. Start verifying with purpose.
AI summary: Vibe Coding Without Security Mistakes by Ethan Ravenscroft is a practical guide for beginners and indie makers using AI coding tools. It teaches systematic review of AI-generated code for security vulnerabilities, covering authentication, authorization, API key protection, database permissions, and safe deployment. The book provides actionable checklists and code comparisons to help non-experts ship secure apps.
- Best for
- Beginners, indie makers, non-technical founders, and junior developers building apps with AI coding tools.
- Reader persona
- A non-technical founder who builds a SaaS prototype using AI coding assistants and needs to ensure it is secure before launch.
- Search intent
- Buyers and readers are searching for practical, beginner-friendly guidance on securing AI-generated code, preventing common security mistakes, and safely deploying apps built with AI tools.
- Unique angle
- Unlike general secure coding books, this guide is tailored specifically for AI-generated code, focusing on the unique mistakes AI tools make and providing a systematic review process for non-experts.
- Content type
- practical security guide for AI-assisted development
Quick summary
- This book teaches beginners how to review AI-generated code for security flaws without needing a cybersecurity background.
- It covers authentication mistakes, API key leaks, and database permission errors common in AI-generated apps.
- Each chapter ends with a checklist for immediate use before deployment.
- The book targets non-technical founders, indie makers, and junior developers building apps with Cursor, Claude, or Copilot.
- It provides a five-part lifecycle from security mindset to safe deployment.
Key topics: AI-generated code security, authentication and authorization, data isolation, API keys and environment variables, database permissions, input validation, dependency risk, code review process, safe deployment, beginner security checklist
Entities: Cursor, Claude Code, GitHub Copilot, ChatGPT, Supabase, Firebase, OAuth, Row-Level Security, API keys, SaaS prototyping, indie making
Needs addressed
- How to identify hidden security flaws in AI-generated code
- How to protect API keys and secrets from exposure
- How to implement proper authentication and authorization
- How to prevent users from accessing other users' data
- How to vet dependencies suggested by AI
- How to deploy apps safely without breaking security
Read if
- Indie makers building SaaS with AI
- Non-technical founders prototyping apps
- Junior developers learning to use AI coding tools
- Small business owners deploying internal tools
- Anyone using Cursor, Claude, or Copilot who wants to ship secure code
May not fit if
- Experienced security professionals may find the content too basic
- Developers already well-versed in OWASP Top 10 and secure coding
- Readers looking for advanced penetration testing techniques
Table of contents
- A Note to the Vibe Coder (introduction)
- Why AI-Generated Apps Can Be Risky (part)
- Working Code Is Not Always Safe Code (chapter)
- The Illusion of Working Code (section)
- Common Hidden Risks (section)
- Why AI Misses Security (section)
- Chapter Checklist (section)
- The Security Mindset for Vibe Coding (chapter)
- Never Trust, Always Verify (section)
- The Review Habit (section)
- Testing Edge Cases (section)
- Chapter Checklist (section)
- Authentication, Authorization, and User Data (part)
- Authentication: Who Is Using the App? (chapter)
- Auth Basics and AI Pitfalls (section)
- Sessions, Tokens, and OAuth (section)
- Password and Magic Link Safety (section)
- Reviewing Auth Code (section)
- Chapter Checklist (section)
- Authorization: What Is the User Allowed to Do? (chapter)
- Auth vs AuthZ (section)
- Role-Based Access and Ownership (section)
- Admin Permission Traps (section)
- Chapter Checklist (section)
- Preventing Users From Seeing Other Users' Data (chapter)
- The Multi-User Risk (section)
- Row-Level Security and Filters (section)
- User_ID Checks and Tenant Isolation (section)
- Chapter Checklist (section)
- API Keys, Databases, and Backend Safety (part)
- API Keys, Secrets, and Environment Variables (chapter)
- Leaked Keys Scenario (section)
- Environment Variables Done Right (section)
- Frontend Exposure Risks (section)
- Scanning for Secrets (section)
- Chapter Checklist (section)
- Database Permissions and Public Data Mistakes (chapter)
- Public Table Disaster (section)
- Supabase/Firebase Permission Risks (section)
- Safe Defaults and Storage Rules (section)
- Chapter Checklist (section)
- Backend APIs, Validation, and Error Handling (chapter)
- Frontend Validation Is Not Enough (section)
- Server-Side Checks and Input Sanitization (section)
- Error Handling and Rate Limits (section)
- Chapter Checklist (section)
- Packages, AI Code Review, and Debugging (part)
- Dependencies, Packages, and Copy-Pasted Code (chapter)
- The Malicious Package Risk (section)
- Vetting AI-Suggested Libraries (section)
- Version and Copy-Paste Traps (section)
- Chapter Checklist (section)
- Reviewing AI-Generated Code Without Being an Expert (chapter)
- The Review Workflow (section)
- Identifying Risky Files (section)
- Checking Auth, DB, and APIs (section)
- Chapter Checklist (section)
- Debugging Safely With AI (chapter)
- When AI Breaks Security (section)
- Safe Debugging Prompts (section)
- Rollback and Isolation (section)
- Chapter Checklist (section)
- Safe Deployment and Release (part)
- Deployment Safety: Vercel, Netlify, Render, Railway, and Mobile Apps (chapter)
- Deployment Configuration Risks (section)
- Env Vars and Build Settings (section)
- Logs, Domains, and Previews (section)
- Chapter Checklist (section)
- The Pre-Launch Security Checklist (chapter)
- Using the Master Checklist (section)
- Auth and Data Checks (section)
- Secrets and Dependency Checks (section)
- Backup and Rollback Plan (section)
- Building a Safer Vibe Coding Workflow (chapter)
- The Safer Workflow Summary (section)
- When to Hire a Pro (section)
- Final Thoughts (section)
Frequently asked questions
Do I need a security background to use this book?
No, the book is written for beginners and assumes no prior security knowledge.
What AI coding tools does this book cover?
The book discusses common AI tools like Cursor, Claude Code, Copilot, and ChatGPT, but the principles apply to any AI code generator.
Does this book include checklists?
Yes, each chapter ends with a checklist and there is a comprehensive pre-launch checklist.
Is this book focused on a specific programming language?
No, it covers general security concepts applicable to any language, with examples in common web frameworks.
Can I use this book to secure a mobile app?
Yes, the principles of authentication, data isolation, and API security apply to mobile apps as well.
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