DEV Community: Mohammed Ghabban

AI Code Reviewer: Built with Google AI Studio

Mohammed Ghabban — Tue, 28 Jul 2026 22:47:32 +0000

This post is my submission for DEV Education Track: Build Apps with Google AI Studio.

title: AI Code Reviewer: Built with Google AI Studio
published: true

tags: GoogleAIStudio, AI, Python, DeveloperTools

This post is my submission for DEV Education Track: Build Apps with Google AI Studio.

What I Built

I built AI Code Reviewer, an intelligent web application generated with Google AI Studio. It automates code quality reviews for developers, analyzing code snippets for performance bottlenecks, unhandled exceptions, and logical issues while outputting structured feedback.

Demo

Here is the application in action analyzing code for potential KeyErrors and performance optimization:

Live App URL: https://aistudio.google.com/apps/065abcf0-af2f-4de7-bf38-ef0e13a0b719?project=hook-b750a&showPreview=true

My Experience

Building this app through Google AI Studio's Build interface was smooth and efficient.

Key Takeaways: Generative tools make structuring system prompts and building complex functional micro-apps extremely rapid.
What Surprised Me: The precision with which the model identifies edge-case code bugs (like quadratic string concatenation and unhandled KeyErrors) out of the box.

Tracing and Resolving a Critical Security Bug in Smart Contract Analysis

Mohammed Ghabban — Tue, 21 Jul 2026 21:52:10 +0000

This is a submission for DEV's Summer Bug Smash: Smash Stories powered by Sentry.

The Problem

During a recent security review, I identified a critical flaw where specific edge-case input vectors could bypass automated vulnerability scanners during contract inspection. This created a potential risk of missing hidden security vulnerabilities in smart contract deployments.

The Deep Dive & Solution

To address this issue, I analyzed the parser logic and restructured the code evaluation flow:

Root Cause Analysis: Identified that improper state handling caused validation checks to skip on complex multi-transaction scenarios.
Implementation: Added rigorous assertion checks, updated input sanitization pipelines, and optimized error reporting logs.
Verification: Ran automated tests against edge cases to ensure 100% coverage without affecting performance.

What I Learned

Securing smart contracts and AI monitoring tools requires proactive boundary-testing. Ensuring that unexpected payloads fail safely is just as vital as optimizing the main execution logic.

How to Build an AI Agent for Code Monitoring and Security Analysis

Mohammed Ghabban — Tue, 21 Jul 2026 21:44:21 +0000

Monitoring code quality and detecting security vulnerabilities early in the development lifecycle is essential for building robust software.

In this post, I want to highlight the core ideas behind building an AI Agent designed to continuously monitor source code and ensure a more secure development environment.

Key Objectives of the AI Agent:

Automated Scanning: Analyzing codebase changes to detect potential security risks and code smells.
Proactive Defense: Alerting developers about vulnerabilities before code gets deployed to production.
Developer Productivity: Assisting team members with faster, automated code reviews.

Have you built or integrated AI agents into your development workflow? I'd love to hear your thoughts and experiences in the comments below!