This content originally appeared on DEV Community and was authored by Jaideep Parashar
As developers, we often focus on building features fast. But here’s the truth:
A single security flaw can undo months of hard work.
That’s why I’ve started using AI not just to write and debug code, but also to spot vulnerabilities early. It’s like having a security reviewer on call 24/7.
Here are some ways AI helps me code more securely.
1️⃣ Input Validation
Many bugs and exploits come from unvalidated input. AI can flag missing checks.
💡 Prompt Example:
“Review this function for input validation vulnerabilities. Suggest fixes for injection or invalid inputs.”
Why: Protects against SQL injection, XSS, and other common attacks.
2️⃣ Authentication Flaws
Implementing login and token systems can be tricky. AI helps generate secure patterns.
💡 Prompt Example:
“Write secure JWT authentication code in Node.js. Include token expiration, refresh, and error handling.”
Why: Avoids unsafe shortcuts like hardcoded keys or weak tokens.
3️⃣ Dependency Risks
Outdated libraries = hidden vulnerabilities. AI can scan and recommend updates.
💡 Prompt Example:
“Review this requirements.txt file and flag outdated or insecure Python dependencies.”
Why: Keeps your stack clean and patched.
4️⃣ Secure API Practices
APIs are prime targets. AI helps enforce best practices like rate limiting and error handling.
💡 Prompt Example:
“Review this API endpoint for potential security issues. Suggest improvements for rate limiting, error handling, and token validation.”
Why: Ensures your API can’t be abused easily.
5️⃣ Secure Configurations
Config mistakes (open ports, exposed secrets) are common. AI can generate safe templates.
💡 Prompt Example:
“Generate a secure Dockerfile for a Flask app. Include environment variables, least-privilege practices, and secure defaults.”
Why: Security is built in, not bolted on.
📌 Here is my complete Coding Prompts Collection:
As part of community support, the Kindle edition of the book is available free on Amazon for two days from Monday, Sept 29 – Tuesday, Sept 30, 2025 (PDT)
In ChatGPT Prompts for Coding, I’ve compiled 630 actionable prompts covering debugging, testing, integration, and deployment.
This way, you don’t just read about workflows here — you’ll have a full playbook to apply them immediately.
Final Thought:
Faster coding is great. But faster + secure coding is unbeatable.
AI won’t replace security experts — but it helps every developer write code that’s safer by default.
Next Post: “My AI Workflow for Writing Cleaner, Readable Code” — how AI helps me enforce coding standards consistently.
This content originally appeared on DEV Community and was authored by Jaideep Parashar
Jaideep Parashar | Sciencx (2025-09-29T04:12:44+00:00) Using AI for Secure Coding: Avoiding Common Vulnerabilities. Retrieved from https://www.scien.cx/2025/09/29/using-ai-for-secure-coding-avoiding-common-vulnerabilities/
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