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Automated Elastic Stack Deployment

The files in this repository were used to configure the network depicted below.

Elk-stack-Simulation

These files have been tested and used to generate a live ELK deployment on Azure. They can be used to either recreate the entire deployment pictured above. Alternatively, select portions of the yaml playbook file may be used to install only certain pieces of it, such as Filebeat.

  • filebeat-playbook.yml.

This document contains the following details:

  • Description of the Topology
  • Access Policies
  • ELK Configuration
    • Beats in Use
    • Machines Being Monitored
  • How to Use the Ansible Build

Description of the Topology

The main purpose of this network is to expose a load-balanced and monitored instance of DVWA, the D*mn Vulnerable Web Application.

Load balancing ensures that the application will be highly reliable and available, in addition to restricting any form of destributed denial of service to the network. It does this by shifting attack traffic from the corporate server to a public cloud provider.

A jump box is a secure computer that all admins first connect to before launching any administrative task or use as an origination point to connect to other servers or untrusted environments. It also helps protect unauthorized access to the network by providing a controlled means.

Integrating an ELK server allows users to easily monitor the vulnerable VMs for changes to the files and system configuration.

  • Filebeat is a lightweight shipper for forwarding and centralizing log data. Installed as an agent on your servers, Filebeat monitors the log files or locations that you specify, collects log events, and forwards them either to Elasticsearch or Logstash for indexing.

-Metricbeat is a lightweight shipper that you can install on your servers to periodically collect metrics from the operating system and from services running on the server. Metricbeat takes the metrics and statistics that it collects and ships them to the output that you specify, such as Elasticsearch or Logstash.

The configuration details of each machine may be found below.

Name Function IP Address Operating System
Jump Box Gateway 10.0.0.4 Linux
Web 1 Webserver 10.0.0.5 Linux
Web 2 Webserver 10.0.0.6 Linux
Web 3 Webserver 10.0.0.7 Linux

Access Policies

The machines on the internal network are not exposed to the public Internet.

Only the Provisioning machine machine can accept connections from the Internet. Access to this machine is only allowed from the following IP addresses:

  • 75.87.171.148

Machines within the network can only be accessed by 10.0.0.4 (Jump-Box-Provisioner).

A summary of the access policies in place can be found in the table below.

Name Publicly Accessible Allowed IP Addresses
Jump Box Yes 75.87.171.148
Web1 Yes 10.0.0.5
Web2 Yes 10.0.0.6
Web3 Yes 10.0.0.7
ELK Yes 75.87.171.148

Elk Configuration

Ansible was used to automate configuration of the ELK machine. No configuration was performed manually, which is advantageous because...

  • One of the prominent advantages of Ansible also refers to the language in which it is written. Python is a human-readable language and serves as the basis for Ansible. It provides better facilities for getting up Ansible and running it due to the presence of Python libraries on the majority of Linux distributions by default.

  • Ansible manages all the master-agent communications through Standard SSH or Paramiko module. The Paramiko module is a Python implementation of SSH2 and is crucial for managing nodes. Therefore, Ansible does not require any form of agents installed on remote systems for ensuring management. As a result, maintenance overheads and performance degradations reduce considerably by huge margins with Ansible.

The playbook implements the following tasks:

  • Installs Docker .io
  • Virtual memory increase
  • The managed nodes to target, using a pattern at least one task to execute.
  • Install pip3

The following screenshot displays the result of running docker ps after successfully configuring the ELK instance.

Elk-stack-Simulation

Target Machines & Beats

This ELK server is configured to monitor the following machines: |Web-1 | | 10.0.0.5 | |Web-2 | | 10.0.0.6 | |Web-3 | | 10.0.0.7 |

We have installed the following Beats on these machines:

  • Filebeat
  • Metricbeat

These Beats allow us to collect the following information from each machine:

  • The filebeats collects data of the file system such as log events, and transports them to the monitoring cluster.
  • The metricbeats collects metrics and statistics and transports them to Elasticsearch or Logstash for its output.

Using the Playbook

In order to use the playbook, you will need to have an Ansible control node already configured. Assuming you have such a control node provisioned:

SSH into the control node and follow the steps below:

  • Copy the playbook file to Ansible.
  • Update the host file to include webservers/Elk
  • Run the playbook, and navigate to Kibana to check that the installation worked as expected.
  • Navigate to the URL : http://[ELK IP Address:5061/app/kibana

. To download a playbook, run the following commands.

  • nano ansible.cfg
  • add the machine, its IP, and ansible_python_interpreter=/usr/bin/python3 to the hosts
  • Ctrl + x to exit file
  • in the folder that install-elk.yml is in, run: cp install-elk.yml /etc/ansible
  • nano install-elk.yml /etc/ansible
  • name: installing elk hosts: [your_machine]
  • Ctrl + x to exit file
  • ansible-playbook install-elk.yml

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