Code Ownership in Open-Source AI Software Security

TL;DR

This study investigates how code ownership patterns in open-source AI projects relate to security vulnerabilities, introducing new time-based metrics and a tool to help improve project security and developer engagement.

Contribution

It provides empirical evidence linking code ownership characteristics to vulnerabilities and introduces innovative time metrics and a benchmarking tool for open-source AI security.

Findings

High ownership correlates with fewer vulnerabilities.

Time metrics effectively categorize project phases and vulnerability levels.

Developed a Python tool for security assessment and benchmarking.

Abstract

As open-source AI software projects become an integral component in the AI software development, it is critical to develop a novel methods to ensure and measure the security of the open-source projects for developers. Code ownership, pivotal in the evolution of such projects, offers insights into developer engagement and potential vulnerabilities. In this paper, we leverage the code ownership metrics to empirically investigate the correlation with the latent vulnerabilities across five prominent open-source AI software projects. The findings from the large-scale empirical study suggest a positive relationship between high-level ownership (characterised by a limited number of minor contributors) and a decrease in vulnerabilities. Furthermore, we innovatively introduce the time metrics, anchored on the project's duration, individual source code file timelines, and the count of impacted releases. These metrics adeptly categorise distinct phases of open-source AI software projects and their respective vulnerability intensities. With these novel code ownership metrics, we have implemented a Python-based command-line application to aid project curators and quality assurance professionals in evaluating and benchmarking their on-site projects. We anticipate this work will embark a continuous research development for securing and measuring open-source AI project security.