security-ownership-map

You can identify orphaned sensitive code and bus factor risks by analyzing git history to build a security ownership topology. This maps people to the files they touch, surfacing ownership clusters and governance gaps for targeted risk assessment.

CODEOWNERS drift occurs when actual file ownership from commit history diverges from defined CODEOWNERS rules. You detect it by analyzing git history to map real file contributions, then comparing these ownership clusters against the declared governance file.

Yes, you can export git commit ownership graphs to Neo4j or Gephi. The analysis generates CSV and JSON artifacts containing people-to-file bipartite graphs, which can be imported into graph databases or visualization tools for governance insights.

Yes, you need Python 3 to run the ownership topology analysis. The networkx library is required for community detection and GraphML output, while core graph generation and risk metric summaries function without it.

You compute sensitive-touches and ownership risk metrics by running an analysis script against your repository root. It evaluates commit history over a specified time window, linking contributors to sensitive files and outputting risk summaries.

The best way to map code ownership clusters is to build a bipartite graph from commit history linking developers to touched files. This approach reveals ownership concentration, highlights orphaned code, and exports structured graph data for visualization.