A Manually-Curated Dataset of Fixes to Vulnerabilities of Open-Source Software

A Manually-Curated Dataset of Fixes to Vulnerabilities of Open-Source Software

Abstract

Advancing our understanding of software vulnerabilities, automating their identification, the analysis of their impact, and ultimately their mitigation is necessary to enable the development of software that is more secure. While operating a vulnerability assessment tool that we developed and that is currently used by hundreds of development units at SAP, we manually collected and curated a dataset of vulnerabilities of open-source software and the commits fixing them. The data was obtained both from the National Vulnerability Database (NVD) and from project-specific Web resources that we monitor on a continuous basis. From that data, we extracted a dataset that maps 624 publicly disclosed vulnerabilities affecting 205 distinct open-source Java projects, used in SAP products or internal tools, onto the 1282 commits that fix them. Out of 624 vulnerabilities, 29 do not have a CVE identifier at all and 46, which do have a CVE identifier assigned by a numbering authority, are not available in the NVD yet. The dataset is released under an open-source license, together with supporting scripts that allow researchers to automatically retrieve the actual content of the commits from the corresponding repositories and to augment the attributes available for each instance. Also, these scripts allow to complement the dataset with additional instances that are not security fixes (which is useful, for example, in machine learning applications). Our dataset has been successfully used to train classifiers that could automatically identify security-relevant commits in code repositories. The release of this dataset and the supporting code as open-source will allow future research to be based on data of industrial relevance; also, it represents a concrete step towards making the maintenance of this dataset a shared effort involving open-source communities, academia, and the industry.

Publication
Proceedings of the 16th International Conference on Mining Software Repositories, 2019

The dataset and the related scripts can be downloaded freely from GitHub. If you use the dataset in your own work, please cite our paper as follows:

@inproceedings{ponta2019msr,
    author={Serena E. Ponta and Henrik Plate and Antonino Sabetta and Michele Bezzi and
    C´edric Dangremont},
    url={https://arxiv.org/pdf/1902.02595.pdf},
    title={A Manually-Curated Dataset of Fixes to Vulnerabilities of Open-Source Software},
    booktitle={Proceedings of the 16th International Conference on Mining Software Repositories}, 
    year=2019,
    month=May,
}