Authors - Kaushal Kotkar, Samiran Deore, Riddhi Tak, Tejal Deshmukh, Rupali Vairagade, Nilakshi Jain Abstract - Traditional CAPTCHAs often hinder users more than they stop bots. This project proposes a passive, user-friendly alternative that monitors behavior—like mouse movement, typing speed, and clicks—to distinguish humans from bots. Built with Python, FastAPI, MongoDB, and XGBoost, the system defends against threats like DoS/DDoS attacks while remaining seamless. It adapts over time through model updates and achieved 95.3% accuracy with minimal false positives. With response times under a second, it outperforms conventional CAPTCHAs in both speed and usability.
