Inspiration
Financial scams are no longer targeting only adults. Teenagers are increasingly exposed to fake giveaways, phishing messages, impersonation scams, and online job fraud through SMS, emails, and social media platforms. Many young people fall victim simply because they don’t know what red flags to look out for. ScamGuard was inspired by the need to protect teenagers early by giving them the knowledge and tools to recognize scams before financial or emotional damage occurs.
What it does
ScamGuard is a web based Financial Scam Awareness tool designed for teenagers aged 13 to 18. Users can paste suspicious messages such as SMS, emails, or social media DMs into the system and ScamGuard analyzes the content to determine whether it is Low Risk, Suspicious, or Likely a Scam. The platform clearly explains the red flags detected and educates users through a Scam Education Hub that covers common scam types, examples, and prevention tips. ScamGuard focuses on prevention, awareness and learning rather than fear or complex automation.
How I built it
ScamGuard was built using a simple, transparent, and explainable approach: Frontend: HTML, CSS, and JavaScript were used to create a clean, teen friendly and responsive interface. Backend: PHP handles server side logic and scam analysis. Database: MySQL stores scam patterns, scam categories, and user reports. The detection engine uses a rule based system that scans messages for known scam keywords, urgency indicators and suspicious patterns. Each detected red flag contributes to a weighted score, which determines the final risk classification and explanation shown to the user.
Challenges I ran into
One major challenge was balancing accuracy with simplicity. I wanted ScamGuard to be effective without making unrealistic AI claims or overcomplicating the system. Another challenge was designing explanations that were clear and educational for teenagers while still being informative. Ensuring a clean user experience and meaningful feedback within a limited development timeframe also required careful prioritization.
Accomplishments that I'm proud of
Building a fully functional MVP within a short timeframe Creating a transparent scam detection system that clearly explains its decisions Designing a teen-friendly interface focused on education and prevention Successfully combining detection and learning into one simple platform
What I learned
Through this project, I learned the importance of building explainable and responsible financial technology, especially for young users. I also gained hands-on experience designing rule based detection systems, structuring backend logic securely with PHP and MySQL, and translating complex financial risks into simple, understandable insights for non technical users.
What's next for ScamGuard
Future improvements for ScamGuard include expanding scam pattern datasets, adding multi-language support, introducing parent and educator dashboards and eventually integrating more advanced analysis techniques using anonymized data. Long term, ScamGuard could evolve into a browser extension or mobile app and be adopted by schools, NGOs, and financial literacy programs to help protect young people globally.
Log in or sign up for Devpost to join the conversation.