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Project KB

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Description

The goal of Project KB is to enable the creation, management and aggregation of a distributed, collaborative knowledge base of vulnerabilities affecting open-source software.

Project KB consists of vulnerability data vulnerability knowledge-base as well as set of tools to support the mining, curation and management of such data.

Motivations

In order to feed Eclipse Steady with fresh data, we have spent a considerable amount of time, in the past few years, mining and curating a knowledge base of vulnerabilities that affect open-source components. We know that other parties have been doing the same, in academia as well as in the industry. From this experience, we have learnt that with the growing size of open source ecosystems and the pace at which new vulnerabilities are discovered, the old approach cannot scale. We are also more and more convinced that vulnerability knowledge-bases about open-source should be open-source themselves and adopt the same community-oriented model that governs the rest of the open-source ecosystem.

These considerations have pushed us to release our vulnerability knowledge base in early 2019. In June 2020, we made a further step releasing the kaybee tool support to make the creation, aggregation, and consumption of vulnerability data much easier. In late 2020, we also released, as a proof-of-concept, the prototype prospector, whose goal is to automate the mapping of vulnerability advisories onto their fix-commits.

We hope this will encourage more contributors to join our efforts to build a collaborative, comprehensive knowledge base where each party remains in control of the data they produce and of how they aggregate and consume data from the other sources.

Kaybee

Kaybee is a vulnerability data management tool, it makes possible to fetch the vulnerability statements from this repository (or from any other repository) and export them to a number of formats, including a script to import them to a Steady backend.

For details and usage instructions check out the kaybee README.

Prospector

Prospector is a vulnerability data mining tool that aims at reducing the effort needed to find security fixes for known vulnerabilities in open source software repositories. The tool takes a vulnerability description (in natural language) as input and produces a ranked list of commits, in decreasing order of relevance.

For details and usage instructions check out the prospector README.

Vulnerability data

The vulnerability data of Project KB are stored in textual form as a set of YAML files, in the vulnerability-data branch.

Publications

In early 2019, a snapshot of the knowlege base from project "KB" was described in:

If you use the dataset for your research work, please cite it as:

@inproceedings{ponta2019msr,
    author={Serena E. Ponta and Henrik Plate and Antonino Sabetta and Michele Bezzi and
    C´edric Dangremont},
    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,
}

MSR 2019 DATA SHOWCASE SUBMISSION: please find here the data and the scripts described in that paper

If you wrote a paper that uses the data or the tools from this repository, please let us know (through an issue) and we'll add it to this list.

Star History

Star History Chart

Credits

EU-funded research projects

The development of Project KB is partially supported by the following projects:

Vulnerability data sources

Vulnerability information from NVD and MITRE might have been used as input for building parts of this knowledge base. See MITRE's CVE Usage license for more information.

Limitations and Known Issues

This project is work-in-progress, you can find the list of known issues here.

Currently the vulnerability knowledge base only contains information about vulnerabilities in Java and Python open source components.

Support

For the time being, please use GitHub issues to report bugs, request new features and ask for support.

Contributing

See How to contribute.

Packages

No packages published

Languages

  • Python 59.6%
  • Go 26.7%
  • Jupyter Notebook 5.9%
  • HTML 4.7%
  • Makefile 1.0%
  • Dockerfile 0.9%
  • Other 1.2%