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Inspiration
As digital communication and services are growing, so is the risk of online scams. From phishing texts to fraud calls/ emails every person gets exposed to such deceptive messages which pretend to be real. This inspired me to create this project- FraudAware - a simple interactive tool which teaches people how to identify between real and scam messages and also let them try their custom messages.
What it does
It offers two main features-
- Quiz mode- Users are presented with common messages and must decide whether they’re real or scams. Explanations are given for each answer to improve awareness.
- Custom check mode- Users can input any message they've received, and the tool uses keyword-based logic to evaluate whether it’s suspicious.
How we built it
FRONTEND- HTML and CSS were used to build a clean user interface. BACKEND- The backend is built using Python Flask, which handles routing, form submissions, and database operations. DATABASE-MySQL stores the quiz questions, answers, and explanations, as well as scam/safe keywords. LOGIC-The keyword detection mechanism flags suspicious words in custom messages, while the quiz pulls randomized real-life messages from the database.
Challenges we ran into
There were a number of challenged I faced during the implementation of this project including- Integration of Flask with MySQL for ensuring data consistency Designing intuitive UI while keeping it modern yet simple Ensuring that custom messages gave useful feedback without using advanced ML/NLP methods which was maintained using keyword based weight system Debugging session handling and user flow in quizzes.
Accomplishments that we're proud of
Created a fully working end-to-end web app in a short time frame. Designed a practical solution aligned with real-world scam detection needs. Handled both quiz logic and dynamic user input analysis. Maintained clean code, modular structure, and a user-friendly interface. Participated in a hackathon with a self-built project that I can now confidently add to my resume and GitHub.
What we learned
Building a Full stack Flask application with integrating databases in it Designing better user feedback loops through quizzes and explanations.
What's next for FraudAware
Expanding the dataset of scam and real messages. Adding user authentication and a history log. Eventually integrating a lightweight ML model/ APIs for smarter detection.
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