Cyber Sheild – An Intelligent Browser Activity Monitoring and Threat Analyzer

Routine web browsing regularly exposes users to phishing domains, deceptive redirects, and other malicious web entities, yet stored browser histories give no indication of the risk those visits carried. This paper presents Cyber Shield, a browser activity monitoring and threat analysis suite that audits historical Google Chrome browsing records and assigns each visited URL a risk estimate. The system pairs a React and Vite front end with a Django REST Framework backend and keeps session logs and analysis results in SQLite. On explicit administrative request, a collector extracts URL history from the local Chrome profile database. Each link is evaluated by a rule-based scoring engine that flags unencrypted HTTP, suspicious keywords, raw IP hostnames, irregular domain formatting, and excessive URL length. A supervised classifier built on character-level TF-IDF vectorization and logistic regression adds a complementary phishing prediction, and, when API credentials are supplied, Virus Total reputation data is retrieved. The web dashboard presents aggregate statistics, risk classifications, and recent activity, and the platform supports credential management, log filtering, persistent threat records, and PDF audit reports. The implemented capabilities are demonstrated through interface snapshots and a sample report of 35 records. The outputs are probabilistic risk estimates and not guarantees of safety, and the machine learning component has not yet been benchmarked because the supplied training dataset is too small.