Security Ownership Map

Security Ownership Map is an official curated OpenAI skill for security-oriented analysis of Git repositories. According to the provider, the workflow builds a bipartite graph of people and files from Git history. It then surfaces who has changed security-relevant files, how widely knowledge is distributed, and where a low bus factor may indicate an operational risk. The skill is published in the official openai/skills repository under the curated security-ownership-map path. The skill directory identifies Apache-2.0 as its license. That provenance makes the catalog record traceable, but it does not replace an independent review of the current source, license obligations, or fitness for a particular privacy and security environment.

Purpose and Professional Use

The defined use case is a security analysis grounded in commit history. The skill should not be triggered for a general maintainer directory or a non-security ownership question. Appropriate questions include orphaned sensitive code, hidden security owners, sensitive hotspots with a low bus factor, ownership clusters, and checks of whether CODEOWNERS reflects the people who actually work on a code area. The analysis can help teams plan review coverage, handovers, and deliberate distribution of security knowledge. A low bus factor is a warning about dependency on a small number of contributors; it is not proof of a vulnerability, poor engineering, or an absent security process.

Git and Graph Method

According to the provider, the workflow first scopes the repository and optional time window. The analysis can switch between author and committer identity and can use a selected date field. Merge commits and certain automated contributions are excluded by default so that integration noise does not dominate the result. The workflow also builds a file co-change graph. Jaccard similarity groups files that move together in shared commits. Large supernode commits and common glue files can be excluded so communities represent meaningful code movement rather than shared infrastructure edits.

Sensitive Paths and Artifacts

The default rules flag common authentication, cryptography, and secret-related paths according to the provider. Teams can supply their own patterns, tags, and weights through a CSV sensitivity configuration. Outputs include people, files, and edge data, a summary of findings, optional commit records, and JSON or GraphML artifacts. These outputs can support bounded queries, visualization, or later graph-database import. A responsible report should record the repository scope, time window, identity choice, excluded authors, co-change exclusions, and sensitivity rules so that future comparisons remain interpretable.

Security, Privacy, and Limits

Git history may contain names, email addresses, internal paths, and clues about confidential structures. It should therefore be analyzed in a controlled working copy and should not be casually copied into external models, tickets, or public reports. The skill analyzes historical activity; it does not prove organizational ownership, current availability, expertise, or the validity of CODEOWNERS. Bot filtering, the selected time range, and author-versus-committer attribution can materially change the picture. According to the provider, teams should reconcile the findings with responsible engineers, real access controls, and current operational knowledge. Graph databases and visualization files must be reviewed for personal and security-sensitive data before sharing.

Positioning for Teams

Security Ownership Map is useful as a reproducible baseline for AppSec reviews, handover planning, and prioritizing security knowledge distribution. It does not replace independent assessment, incident investigation, or a binding organizational decision. Its value depends on a defensible scope, reliable history, documented parameters, and human validation. The Codex relationship in this catalog entry reflects documented compatibility; actual runtime and privacy conditions depend on the selected agent and its model and integration path.