• Ms. Meetali Gajanan Rane
• Ms. Nikita Ishwar Patil
• Ms. Priyanka Chanvir
• Mrs. Sushiladevi Vantamuri

In a world where cyber- attacks are becoming more sophisticated and more common, active detection systems are critical to protect digital infrastructure. This paper introduces a full-fledged cybersecurity monitoring system that utilizes email address analysis, IP monitoring, file preview, and spam phone number detection. Developed on the Flask web framework, the system incorporates machine learning, threat intelligence APIs, and user-agent analytics in order to evaluate and visualize web traffic risks. Suspicious domains, IP anomalies, or known attack patterns trigger alerts and logging, and users have access to an easy-to-use interface to view activity trends and timely notifications. The platform also features domain mirror detection to enhance its threat assessment functionality. Built to be lightweight, extensible, and easy to use, the system enables individuals and organizations to improve their cybersecurity stance with early threat detection, and thus it is an excellent resource for research, education, and operational security.

Cybersecurity, IP Analysis, Domain Monitoring, Flask Web Application, Mirror website Detection, Machine Learning.

"OBLIVION SENTINEL: THREAT INTELLIGENCE MONITOR USING CYBER SECURITY", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 5, page no.d849-d855, May-2025, Available :http://www.jetir.org/papers/JETIR2505444.pdf

"OBLIVION SENTINEL: THREAT INTELLIGENCE MONITOR USING CYBER SECURITY", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 5, page no. ppd849-d855, May-2025, Available at : http://www.jetir.org/papers/JETIR2505444.pdf