Security dashboards often show alerts without making it obvious why an event was flagged.

I started building SentinelGraph AI to explore more transparent security-event investigations.

Project design

The prototype is designed around:

  • Synthetic authentication events
  • Explainable detection rules
  • Risk scoring and severity levels
  • Interactive security dashboards
  • Relationships between users, devices, and IP addresses
  • CSV export for investigations

Technology

Python, Streamlit, Pandas, Plotly, NetworkX, and Docker.

Current development status

This project is still incomplete.

The Streamlit dashboard code is available, but the core sentinelgraph/ Python package and automated tests still need to be uploaded.

The animated preview is a concept illustration, not a recording of a working application.

Future work includes restoring the missing source code, adding tests, validating the application, and developing machine-learning detection capabilities.

GitHub repository: https://github.com/tasnem-tech/sentinelgraph-ai

I'm sharing this as a work-in-progress project and welcome constructive feedback.