edit

Basic Installation

In this page you will be guided through a basic installation of Automatron. If you wish to deploy Automatron within a container, you can skip this guide and follow the Docker deployment instructions.

Basic Installation

Currently, the simplest method of installing Automatron is by either cloning the GitHub Repository or downloading a specific release and installing dependencies.

This guide will walk through cloning the GitHub repository and starting an Automatron instance.

Prerequisites

The below list is a set of base requirements for installing and running an Automatron instance.

  • Python 2.7 or higher
  • Python-dev Package
  • Pip
  • Redis
  • nmap
  • git
  • libffi-dev
  • libssl-dev
  • build-essential

On Ubuntu systems these can be installed with the following command.

$ sudo apt-get install python2.7 python-dev \
                       python-pip redis-server \
                       nmap git libffi-dev \
                       build-essential libssl-dev

Once installed we can proceed to Automatron's installation

Clone from Github

The first installation step is to simply clone the current repository from GitHub using git and change to the newly created directory.

$ git clone https://github.com/madflojo/automatron.git
$ cd automatron

This will place the latest master (production ready) branch into the automatron directory.

Install required python modules

The second installation step is to install the required python modules using the pip command.

$ sudo pip install -r requirements.txt
$ sudo pip install honcho

With the above two steps complete, we can now move to Configuration.

Starting Automatron

In order to start Automatron you can simply execute the command below.

$ honcho start

To shut down Automatron you can use the kill command to send the SIGTERM signal to the running processes.

Dashboard

To view the Automatron dashboard simply open up http://<instance ip>:8080 in your favorite browser. As target nodes are identified and runbooks are executed, events will start to be reflected on the dashboard.