GithubHelp home page GithubHelp logo

yuning-j / nvdfeatureanalysis Goto Github PK

View Code? Open in Web Editor NEW
10.0 1.0 3.0 65.18 MB

Correlate NVD datasets wIth CWE/CAPEC/CVSS labels for customised usage. Plus static analysis and data visualisation.

License: GNU Affero General Public License v3.0

Python 2.92% Jupyter Notebook 97.08%
nvd text-mining cvss cwe capec cvedetails json xml data-visualization csv-export

nvdfeatureanalysis's Introduction

NVD Feature Analysis



GitHub repo size GitHub last commit License

NVD Feature Analysis

Analyse the features of NVD vulnerability reports in terms of CWE, CAPEC, threat and CVSS V2/V3.

Table of Contents

About the Tool

Some static analysis and visualisation for vulnerability instances disclosed in NVD. This tool also generates several datasets with various labels (CWE labels, CAPEC labels, CVSS labels, cvedetails labels) that can be used for further text-mining usage. You can directly employ the generated dataset, or apply this tool to get your own.

Some data samples are illustrated below.

  • Report with CWE and CAPEC labels:

System

  • Report with Threat labels:

System

  • Report with CVSS Version 2 labels:

System

  • Report with CVSS Version 3 labels:

System

Generate your own data

Play with vulnerability reports as you want.

  • Step 1: Clone the repo using the following command:
git clone https://github.com/Yuni0217/NVDdata-analysis-and-visualisation.git 
  • Step 2: Create a virtual environment, also change the absolute path in the config.py file.

  • Step 3: Install requirements using pip:

pip install -r requirements.txt
  • Step 4: Download datasets from NVD feeds and assign CWE/CVSS/threat labels.
python src/getNVDdata.py that downlads datasets from NVD feeds.
python src/assignThreatLabels.py that assigns threat labels to NVD vulnerabilities.
python src/assignCWECAPECLabels.py that assigns CWE and CAPEC labels to NVD vulnerabilities.
python src/assignCVSSLabels.py that assigns threat labels to NVD vulnerabilities.

Directly use historical datasets

Note that these datasets are compressed due to large sizes.

Some data visualisation

Check some of the visualisation documentations in the Notebooks. Or create your own awesomes. Below are some of the examples:

  • Vulnerability distribution in terms of access vector:

System

  • Threat distribution:

System

Cite

If you use this tool in your academic work you can cite it using

@Misc{nvdfeatureanalysis,
  author       = {Yuning Jiang},
  howpublished = {GitHub},
  month        = jan,
  title        = {{NVD Feature Analysis}},
  year         = {2022},
  url          = {https://github.com/Yuning-J/NVDFeatureAnalysis},
}

nvdfeatureanalysis's People

Contributors

yuning-j avatar

Stargazers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

Watchers

 avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.