📰 Originally published on Securityelites — AI Red Team Education — the canonical, fully-updated version of this article.
💻 MASTERING CODING WITH AI FREE
Day 5 of 5 · 🎉 100% complete!
Here’s a situation I’ve seen play out more times than I’d like: a non-technical founder uses AI to build a customer-facing tool in a weekend. The tool works. Users start signing up. Three months later, someone finds a simple SQL injection vulnerability that exposes every user’s email address. The tool worked. The tool was not safe.
The goal of Day 5 isn’t to scare you out of building things. It’s to give you the specific security checks that catch the most common AI code vulnerabilities — checks you can run entirely by asking AI the right questions, with no coding knowledge required. I’ve distilled five years of reviewing AI-generated code into the patterns that appear most often, and the audit questions that reliably surface them.
By the end of today you’ll have a personal security checklist that you run on every tool before sharing it with anyone who matters. You’ll know when you can ship confidently and when to get a human reviewer. And you’ll understand exactly where this course leads next.
🎯 What You’ll Master in Day 5
The five most common security issues in AI-generated code
The AI audit loop — using AI to review its own code for security problems
Dependency risk — what it is and how to protect against it
The shipping decision — when to ship, when to pause, when to get help
Your complete personal AI coding checklist for every future project
⏱ 25 min read · 3 exercises · Browser needed 📋 Full Course Foundation
- Day 1: Mental model, IPO, architect vs builder, specificity
- Day 2: Five-component prompts, iterative prompting, constraints
- Day 3: Structural reading, five mistakes, debug loop, behavioural testing
- Day 4: Six-stage build process, deployment, real user feedback
Secure AI Generated Code — Day 5 of 5
- The Five Most Common AI Code Security Issues
- The AI Audit Loop — Using AI to Security-Review Its Own Code
- Dependency Risk — The Invisible Attack Surface
- The Shipping Decision — When to Ship, When to Pause
- Your Personal AI Coding Security Checklist
- Where to Go Next — Your Learning Path
- Questions and Answers
Day 5 is the security practitioner’s perspective on everything you’ve built this week. The vibe coding security risks article covers the broader landscape of what goes wrong when AI-generated code gets shipped without review. Our phishing URL scanner demonstrates what security-conscious tool building looks like in production — client-side only, no data storage, clear about what it can and can’t do. That’s the standard to aim for.
The Five Most Common AI Code Security Issues
I’ve reviewed hundreds of AI-generated tools and the same security issues appear repeatedly. Not randomly — they appear because they’re the things that require explicit specification to include, and most prompts don’t include them. Here’s the list, with what to check and how to fix each one.
Issue 1 — Unescaped output (XSS). If your tool takes user input and displays it on screen without “escaping” HTML special characters, an attacker can inject <script> tags that run malicious code in other users’ browsers. This is the most common and most immediately exploitable vulnerability in AI-generated web tools.
Check: type <script>alert(‘xss’)</script> in any input field. If a popup appears, you’re vulnerable. Fix: “Update this code to escape all HTML special characters in any user input before displaying it. Use the browser’s built-in textContent property instead of innerHTML for displaying user input.”
Issue 2 — Plain text data storage. If your tool stores passwords, API keys, or sensitive personal information without encryption or hashing, anyone who gains access to the storage sees everything. For browser-based tools: avoid storing sensitive data at all. For server-side tools: passwords must always be hashed with bcrypt or argon2, never stored in plain text.
Check: ask AI “does this code store any passwords, tokens, or sensitive information? If so, how are they stored?” Fix: “Update the password storage to use bcrypt hashing. Never store the plain text password.” Or, for browser tools: “Remove any storage of the password — it should only be evaluated, never saved.”
Issue 3 — No rate limiting on forms. A form without rate limiting can be hammered by an automated script thousands of times per second — to brute-force passwords, submit spam, or overwhelm a server. For simple browser-only tools this matters less (there’s no server to overwhelm). For any form that calls a backend: rate limiting is essential.
Check: ask AI “does this code have any rate limiting on form submissions or API calls?” Fix: “Add rate limiting — allow a maximum of 5 submissions per IP address per minute. Return a friendly error message if exceeded.”
Issue 4 — Sensitive data in client-side code. API keys, database passwords, internal server URLs, and business logic embedded in JavaScript that runs in the browser can be viewed by anyone who looks at the page source. Browser-side code is public by definition.
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This article was originally written and published by the Securityelites — AI Red Team Education team. For more cybersecurity tutorials, ethical hacking guides, and CTF walk-throughs, visit Securityelites — AI Red Team Education.
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