
Problem: Digital scams are becoming increasingly convincing, using urgency, impersonation, fake offers, suspicious links, payment requests, and social engineering to pressure people into making quick decisions. Many users can recognize obvious scams but struggle to determine whether a realistic-looking message, job offer, payment request, QR code, or website is trustworthy. Existing approaches often reduce the problem to a simple “scam/not scam” classification, which does not teach users what to look for or what to do next. Solution: ScamLens is an AI-powered “second pair of eyes” for everyday digital interactions. Users can paste a message, upload a screenshot, check a link, or provide other suspicious digital content. ScamLens analyzes the content for multiple risk signals such as urgency, impersonation, suspicious domains, credential requests, payment requests, emotional pressure, unrealistic offers, and unusual instructions. Instead of simply declaring something a scam, ScamLens provides an understandable risk assessment and explains exactly why specific signals were detected. It then provides three practical steps: STOP – what the user should avoid doing; VERIFY – how the claim can be independently checked; and PROTECT – the safest next action. Example: If a user receives a message claiming that their bank account will be blocked unless they click a link, ScamLens can identify urgency, potential impersonation, suspicious-domain characteristics, and credential requests. It can then recommend accessing the bank through its official application or independently verified contact channel instead of following the message's link. Target Users: ScamLens is designed for everyday digital users, including students, working professionals, parents, senior citizens, online shoppers, and people who may not have cybersecurity expertise. Multilingual explanations can make the system more accessible to users who are more comfortable in regional languages. Innovation: ScamLens focuses on explainable protection rather than black-box classification. Its core experience is “Give this a Second Look”: analyze the content, identify warning signals, explain them in simple language, and provide safe verification steps. This turns AI from a passive answer generator into a proactive decision-support layer for everyday digital safety. Efficiency: The prototype is designed around a focused pipeline: input capture, text/image understanding, risk-signal extraction, AI reasoning, explainable assessment, and recommended safety actions. The modular architecture allows future expansion into real-time browser protection, email analysis, QR-code analysis, voice-call transcription, and multilingual assistance. ScamLens does not claim that an AI assessment is definitive proof of fraud. Instead, it helps users recognize potential warning signs and encourages independent verification before sensitive actions such as clicking, paying, sharing credentials, or transferring money.
27 Sep 2026