AI Security Exposure Detector Earns a 13 Proof of Usefulness Score Building an AI-Powered Data Leak Identification Tool

In this interview, we catch up with Nishant Kumar to discuss AI Security Exposure Detector, a web-based tool designed to help organizations identify publicly exposed cloud files and sensitive data leaks. We look at how they are using AI-powered classification and risk scoring to prevent data breaches.

What does AI Security Exposure Detector do? And why is now the time for it to exist?

AI Security Exposure Detector is a web-based tool that helps organizations identify publicly exposed cloud files and sensitive data leaks using AI-powered classification and risk scoring. It enables users to quickly scan links, assess exposure risks, and generate actionable security reports to prevent data breaches. Now’s a good time for AI Security Exposure Detector to exist because cloud storage misconfigurations are increasingly common, and organizations need automated ways to classify and secure sensitive data before malicious actors find it.

What is your traction to date? How many people does AI Security Exposure Detector reach?

The project is currently reaching early adopters including developers, security enthusiasts, and small teams who are testing the tool and providing real-world feedback. Audience reach is expected to grow through community sharing, social platforms, and targeted outreach to users who benefit from automated risk detection and AI-powered insights.

Who does your project serve? What’s exciting about your users and customers?

This project is for indie developers, startup founders, and product teams who want to measure real user adoption, validate product impact, and prove that their product delivers real-world value beyond demos.

What technologies were used in the making of the AI Security Exposure Detector? And why did you choose ones most essential to your tech stack?

The platform leverages a custom AI stack designed specifically to handle classification and risk scoring tasks efficiently. Additionally, it integrates with Bright Data to facilitate robust web scraping and the discovery of exposed data across the web.

What is the traction to date for the AI Security Exposure Detector? Around the web, who’s been noticing?

Currently, the product operates in beta, working closely with pilot users to validate core functionality. These early interactions are generating real usage data that directly informs feature refinement and ensures the tool addresses practical security needs.

What excites you about this project's potential usefulness?

What excites me most about this project’s potential usefulness is that it focuses on solving a real, practical problem with measurable impact rather than being just a conceptual demo. The project is designed to deliver tangible value by helping users make better, faster, and safer decisions through AI-powered insights, real usage tracking, and actionable outputs. Its emphasis on real-world adoption, continuous improvement based on user feedback, and proof of actual utility gives it the potential to become a genuinely helpful tool that people rely on in meaningful, everyday scenarios.