Student Team
Mishika Malik
AI Scam Detector Team · Grade 11 · New Delhi
Divyanshi Singh
AI Scam Detector Team · Grade 11 · Kanpur
A real-time AI protection tool that scans links, messages, files, and suspicious scam patterns, then gives users a risk score, alert, and simple report before fraud can happen.
Online scams are increasing rapidly across social media, websites, email, and messaging platforms.
Many users cannot identify scam attempts early enough and become victims of fraud.
Fraud can steal passwords, money, savings, and private information from individuals and businesses.
The project frames online fraud as a fast-growing safety problem where simple, instant checks can prevent major harm.
Large-scale losses show why early scam detection matters.
Scam attempts have multiplied in recent years.
Many users face scam attempts every month.
Fake emails trick users, steal passwords or money, and can install malware.
Scammers promise big returns, then victims lose their savings.
Scammers pressure people into sharing private information or taking risky action.
The system checks user-submitted content, compares it with known scam patterns, and warns the user with a clear risk score.
Users share a link, message, file, or suspicious content.
The system checks for warning signs in the content.
It compares the input against known scams and risky patterns.
The user receives a risk score and warning.
Reads messages and links to find signs of fraud.
Learns from known scams and improves over time.
Finds hidden patterns in tricky scams.
Flags unusual behavior that may indicate fraud.
Checks data immediately and sends instant alerts.
Shows danger from 0 to 100 so users can decide quickly.
Flags unsafe links and explains why they look risky.
Generates simple reports that can support complaints.
Feedback helps improve future scam detection.
AI Scam Detector helps protect people online, teaches warning signs, reduces financial losses, and can provide useful clues for reporting fraud.
Helps new and experienced users spot suspicious activity before they act.
Early warnings can prevent scam losses and stolen savings.
Simple reports can help users document suspicious activity.