Abstract

Every day, sensitive personal information sits hidden inside thousands of digital documents, often without anyone realizing the risk. PIIE is a desktop application developed to help users identify sensitive personal information within large collections of files. The application scans text, Word, and PDF documents to locate personally identifiable information allowing users to better understand potential data exposure. All processing occurs locally to preserve data privacy and security. The system uses a modular architecture consisting of a Python-based backend, a PyQt graphical interface, and automated packaging into executable programs. The machine learning model used for detection was created and trained locally to meet project-specific requirements. Results are produced in structured log files designed to scale beyond individual use and support integration with enterprise security tools, such as SIEM platforms. By combining accessibility, security, and scalability, this project demonstrates a practical and enterprise-ready approach to strengthening data privacy and information security awareness.