VHub - An API that permits uploading of vulnerability datasets and return of the serialized data

Related tags

Data Analysisvhub
Overview

VHub

VHub is an API that permits uploading of vulnerability datasets based on the following pattern of columns:

ASSET - HOSTNAME ASSET - IP_ADDRESS VULNERABILITY - TITLE VULNERABILITY - SEVERITY VULNERABILITY - CVSS VULNERABILITY - PUBLICATION_DATE

The data are provided by endpoints to handle it and possibly to generate tables and chats to get insights about the vulnerability data.


Pre-requisites


Installation

To install the package, clone the repository on github and run the following command:

poetry install

Next, enter the virtualenv to be able getting access to django, with:

poetry shell

Setting up environment variables

Before continue, you need to generate the SECRET_KEY. To do this, rename the file .env.example to .env, generate the token and put it as value to SECRET_KEY.

Setting up the database

To setup the databse run:

python manage.py migrate

Running the API

Finally, run the Vhub API with:

python manage.py runserver

Now, access http://127.0.0.1:8000/api/swagger/ to see the Swagger documentation.

You might also like...
Udacity-api-reporting-pipeline - Udacity api reporting pipeline

udacity-api-reporting-pipeline In this exercise, you'll use portions of each of

 🧪 Panel-Chemistry - exploratory data analysis and build powerful data and viz tools within the domain of Chemistry using Python and HoloViz Panel.
🧪 Panel-Chemistry - exploratory data analysis and build powerful data and viz tools within the domain of Chemistry using Python and HoloViz Panel.

🧪📈 🐍. The purpose of the panel-chemistry project is to make it really easy for you to do DATA ANALYSIS and build powerful DATA AND VIZ APPLICATIONS within the domain of Chemistry using using Python and HoloViz Panel.

Reading streams of Twitter data, save them to Kafka, then process with Kafka Stream API and Spark Streaming
Reading streams of Twitter data, save them to Kafka, then process with Kafka Stream API and Spark Streaming

Using Streaming Twitter Data with Kafka and Spark Reading streams of Twitter data, publishing them to Kafka topic, process message using Kafka Stream

PrimaryBid - Transform application Lifecycle Data and Design and ETL pipeline architecture for ingesting data from multiple sources to redshift
PrimaryBid - Transform application Lifecycle Data and Design and ETL pipeline architecture for ingesting data from multiple sources to redshift

Transform application Lifecycle Data and Design and ETL pipeline architecture for ingesting data from multiple sources to redshift This project is composed of two parts: Part1 and Part2

Minimal working example of data acquisition with nidaqmx python API

Data Aquisition using NI-DAQmx python API Based on this project It is a minimal working example for data acquisition using the NI-DAQmx python API. It

API>local_db>AWS_RDS - Disclaimer! All data used is for educational purposes only.
APIlocal_dbAWS_RDS - Disclaimer! All data used is for educational purposes only.

APIlocal_dbAWS_RDS Disclaimer! All data used is for educational purposes only. ETL pipeline diagram. Aim of project By creating a fully working pipe

Demonstrate a Dataflow pipeline that saves data from an API into BigQuery table

Overview dataflow-mvp provides a basic example pipeline that pulls data from an API and writes it to a BigQuery table using GCP's Dataflow (i.e., Apac

fds is a tool for Data Scientists made by DAGsHub to version control data and code at once.
fds is a tool for Data Scientists made by DAGsHub to version control data and code at once.

Fast Data Science, AKA fds, is a CLI for Data Scientists to version control data and code at once, by conveniently wrapping git and dvc

Python data processing, analysis, visualization, and data operations

Python This is a Python data processing, analysis, visualization and data operations of the source code warehouse, book ISBN: 9787115527592 Descriptio

Releases(v0.1.1)
Owner
André Rodrigues
Python Developer. Computer Engineering.
André Rodrigues
This is an example of how to automate Ridit Analysis for a dataset with large amount of questions and many item attributes

This is an example of how to automate Ridit Analysis for a dataset with large amount of questions and many item attributes

Ishan Hegde 1 Nov 17, 2021
BIGDATA SIMULATION ONE PIECE WORLD CENSUS

ONE PIECE is a Japanese manga of great international success. The story turns inhabited in a fictional world, tells the adventures of a young man whose body gained rubber properties after accidentall

Maycon Cypriano 3 Jun 30, 2022
Exploring the Top ML and DL GitHub Repositories

This repository contains my work related to my project where I scraped data on the most popular machine learning and deep learning GitHub repositories in order to further visualize and analyze it.

Nico Van den Hooff 17 Aug 21, 2022
NumPy and Pandas interface to Big Data

Blaze translates a subset of modified NumPy and Pandas-like syntax to databases and other computing systems. Blaze allows Python users a familiar inte

Blaze 3.1k Jan 05, 2023
Analyse the limit order book in seconds. Zoom to tick level or get yourself an overview of the trading day.

Analyse the limit order book in seconds. Zoom to tick level or get yourself an overview of the trading day. Correlate the market activity with the Apple Keynote presentations.

2 Jan 04, 2022
fds is a tool for Data Scientists made by DAGsHub to version control data and code at once.

Fast Data Science, AKA fds, is a CLI for Data Scientists to version control data and code at once, by conveniently wrapping git and dvc

DAGsHub 359 Dec 22, 2022
The official pytorch implementation of ViTAE: Vision Transformer Advanced by Exploring Intrinsic Inductive Bias

ViTAE: Vision Transformer Advanced by Exploring Intrinsic Inductive Bias Introduction | Updates | Usage | Results&Pretrained Models | Statement | Intr

104 Nov 27, 2022
Fancy data functions that will make your life as a data scientist easier.

WhiteBox Utilities Toolkit: Tools to make your life easier Fancy data functions that will make your life as a data scientist easier. Installing To ins

WhiteBox 3 Oct 03, 2022
The micro-framework to create dataframes from functions.

The micro-framework to create dataframes from functions.

Stitch Fix Technology 762 Jan 07, 2023
PyStan, a Python interface to Stan, a platform for statistical modeling. Documentation: https://pystan.readthedocs.io

PyStan PyStan is a Python interface to Stan, a package for Bayesian inference. Stan® is a state-of-the-art platform for statistical modeling and high-

Stan 229 Dec 29, 2022
Flood modeling by 2D shallow water equation

hydraulicmodel Flood modeling by 2D shallow water equation. Refer to Hunter et al (2005), Bates et al. (2010). Diffusive wave approximation Local iner

6 Nov 30, 2022
Package for decomposing EMG signals into motor unit firings, as used in Formento et al 2021.

EMGDecomp Package for decomposing EMG signals into motor unit firings, created for Formento et al 2021. Based heavily on Negro et al, 2016. Supports G

13 Nov 01, 2022
MIR Cheatsheet - Survival Guidebook for MIR Researchers in the Lab

MIR Cheatsheet - Survival Guidebook for MIR Researchers in the Lab

SeungHeonDoh 3 Jul 02, 2022
A real data analysis and modeling project - restaurant inspections

A real data analysis and modeling project - restaurant inspections Jafar Pourbemany 9/27/2021 This project represents data analysis and modeling of re

Jafar Pourbemany 2 Aug 21, 2022
A model checker for verifying properties in epistemic models

Epistemic Model Checker This is a model checker for verifying properties in epistemic models. The goal of the model checker is to check for Pluralisti

Thomas Träff 2 Dec 22, 2021
Big Data & Cloud Computing for Oceanography

DS2 Class 2022, Big Data & Cloud Computing for Oceanography Home of the 2022 ISblue Big Data & Cloud Computing for Oceanography class (IMT-A, ENSTA, I

Ocean's Big Data Mining 5 Mar 19, 2022
pipeline for migrating lichess data into postgresql

How Long Does It Take Ordinary People To "Get Good" At Chess? TL;DR: According to 5.5 years of data from 2.3 million players and 450 million games, mo

Joseph Wong 182 Nov 11, 2022
pyhsmm MITpyhsmm - Bayesian inference in HSMMs and HMMs. MIT

Bayesian inference in HSMMs and HMMs This is a Python library for approximate unsupervised inference in Bayesian Hidden Markov Models (HMMs) and expli

Matthew Johnson 527 Dec 04, 2022
Tools for analyzing data collected with a custom unity-based VR for insects.

unityvr Tools for analyzing data collected with a custom unity-based VR for insects. Organization: The unityvr package contains the following submodul

Hannah Haberkern 1 Dec 14, 2022
VevestaX is an open source Python package for ML Engineers and Data Scientists.

VevestaX Track failed and successful experiments as well as features. VevestaX is an open source Python package for ML Engineers and Data Scientists.

Vevesta 24 Dec 14, 2022