Open Arsenal

AI watches. Humans decide.

PHITrack is an open-source platform designed to monitor, analyze, and visualize Protected Health Information (PHI) transmission patterns across healthcare systems using AI-driven analytics and synthetic data. Its primary goal is to improve HIPAA compliance awareness and security posture by making data movement visible, measurable, and understandable in real time. The system is built around a strict safety model where no real PHI is ever used—only synthetic or anonymized datasets are processed throughout the pipeline.

At its core, PHITrack uses an AI analysis layer to classify and track different types of PHI-related events, such as email transmissions, API calls, database access, and file exports. These events are aggregated into statistical models that highlight frequency, severity, and risk trends over time. The platform also includes anomaly detection and predictive risk scoring, allowing systems to identify unusual patterns that may indicate misconfigurations or potential compliance risks before they escalate into incidents.

PHITrack provides a comprehensive visualization and reporting dashboard that turns complex event data into clear insights through charts, heatmaps, and trend analysis. Users can drill down into specific systems or categories to understand where security improvements are needed most. Automated reporting features generate summaries of PHI transmission activity across configurable time periods, making it easier for organizations to support audits and internal compliance reviews.

A key design principle of PHITrack is its human-in-the-loop architecture. While AI continuously monitors and flags potential issues, final validation and decision-making remain with human reviewers. This ensures accountability and reduces the risk of false positives or automated misclassification. Combined with its plugin architecture, synthetic training environments, and extensible AI modules, PHITrack serves as both a compliance tool and an educational framework for strengthening healthcare data security practices.