Parasite AI: Real-Time Chat Monitoring and Intelligent Threat Detection Using NLP-Driven Overlay Systems

K. Aravind , K. Ashok Kumar , T. Rajasekhar Reddy , M. Yaswanth Anil , Dr. P. Muthusamy

Real-time chat monitoring Natural language processing Phishing detection Overlay interface Accessibility services Cybersecurity AI

With the rapid proliferation of digital messaging platforms, users face increasing exposure to cyber threats including phishing attacks, fraudulent links, misleading information, and fake product promotions. Traditional security solutions are largely reactive, relying on post-event analysis and basic spam filtering, which proves insufficient against sophisticated real-time threats. This paper presents Parasite AI, an intelligent real-time chat monitoring assistant that leverages Natural Language Processing (NLP) and machine learning techniques to continuously analyze visible chat content and detect potential threats during live conversations. The proposed system employs Android accessibility services to capture on-screen chat data without interrupting user workflows, processes the extracted text through an AI analysis engine incorporating keyword pattern matching, contextual intent recognition, and URL safety verification, and delivers real-time alerts and intelligent suggestions via a non-intrusive overlay interface. The system integrates multiple specialized modules including screen monitoring, text extraction, AI-based threat analysis, link verification, claim detection, and product authentication to provide comprehensive protection. Experimental evaluation across diverse messaging scenarios demonstrates that the system achieves 95.2% threat detection accuracy with a false positive rate of 4.8%, while maintaining sub-second response times. The system's modular architecture supports seamless integration with popular messaging platforms including WhatsApp, Telegram, and social media applications, establishing Parasite AI as a practical and scalable solution for enhancing user safety in digital communication environments

Volume 14 Issue 4, April-2026

Pages : k155-k162