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risk-explorer-for-machine-learning's Introduction

Risk Explorer for Software Supply Chains

License REUSE status

About this project

This project offers a tool to explore a taxonomy of attack vectors targeting open-source software supply chains. This information has been compiled on the basis of numerous real-world incidents, i.e. actual attacks and vulnerabilities, as well as plausible proof-of-concepts and scientific literature. You can find more about this work in our paper.

The project can be used as learning material for awareness campaigns or trainings, but also for purposes such as threat modeling, risk-assessments or pentest scoping.

In more detail, project and tool provide the following information:

  • Attack Tree: a hierarchical organization of 100+ attack vectors and techniques comprised in the taxonomy, starting from the abstract, top-level goal down to alternative and more concrete attack techniques
  • Attack Vectors: a tabular view of all the attack vectors, along with the description, references, real-world examples and mapped safeguards
  • Safeguards: a tabular view of countermeasures that fully or partially mitigate the above-mentioned attacks
  • References: 300+ resources in some or another way related to supply chain security, both scientific and gray literature, all tagged and linked to attack vectors/safeguards

Requirements and Setup

Simply access the tool online using your favorite browser. Make sure to enable JavaScript and use a desktop environment for a better experience.

If you want to run a local version of the code you need to install Node.js, then from inside the project directory (where package.json is located):

  1. Install the required dependencies via npm install
  2. Run the project via npm start

Support, Feedback, Contributing

This project is open to feature requests/suggestions, bug reports etc. via GitHub issues. Contribution and feedback are encouraged and always welcome. For more information about how to contribute, the project structure, as well as additional contribution information, see our Contribution Guidelines.

Code of Conduct

We as members, contributors, and leaders pledge to make participation in our community a harassment-free experience for everyone. By participating in this project, you agree to abide by its Code of Conduct at all times.

Licensing

Copyright 2022 SAP SE or an SAP affiliate company and Risk Explorer for Software Supply Chains contributors. Please see our LICENSE for copyright and license information. Detailed information including third-party components and their licensing/copyright information is available via the REUSE tool.

risk-explorer-for-machine-learning's People

Contributors

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Forkers

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