Pawgoni

Process Actuarial Worker for Authentication Incidence

Artificial intelligence is critical for cybersecurity and web development. This project will consider defending against botnets, specifically XOR. Combating this threat must automate the monitoring of infected addresses and take measures to notify the compromised machine’s internet access provider with solutions for resolution. To do so, a process actuarial monitoring system for sshd authentication Intent (PAWGONI) that employs machine learning to track and automate threat response will be developed.

Read the whitepaper for the conceptual basis of this project.

Up and running

Get the repo:

git clone http://github.com/xhad/pawgoni.git
cd pawgoni

Next, install dependencies. The back-end is a simple Flask API, so you'll probably want to set up a virtual environment as well. These commands assume that you have Python3 and Node.js (with npm) installed.

sudo apt-get install python3-venv
pyvenv env
source env/bin/activate
pip install -r requirements.txt
npm install

Server Database

Next, build the MongoDB docker image. Here is a link for more information on how to build docker images:

sudo apt install docker docker-compose
sudo gpasswd -a ${USER} docker
cd db
./build-db.sh

To run the database as a daemon:

docker-compose up -d

To copy a csv file from the host to the container and import the longon.csv file to the MongoDB running on the container:

docker cp ./seed-data  db_mongodb_1:/root/seed-data
docker exec -it db_mongodb_1 bash
mongoimport  --db pawgoni --collection logons  --type csv --headerline --file /root/seed-data/logons.csv

NOTES

docker exec -it db_mongodb_1 bash

Clean up and erase all docker containers:

docker stop $(docker ps -a -q)
docker rm $(docker ps -a -q)

Client Database

To more effectively manage data, this project uses RxDB on the client.

Websocket Data Server

Socket.io server with nodejs that handles delivery of large data sets This server requires PM2, a node process manager, to be installed globally.

sudo npm install -g pm2

Now that you have everything installed, you can build and run the app.

npm start
npm stop

This will compile the JavaScript modules and Less and start up the Flask API.

Development

To watch the src folder for changes and automatically recompile, run:

npm run watch

React

React: React Routing: React-Router Observables: Rxjs Database: RxDB

Running tests

To run the tests, use the following commands. The first runs the Mocha test-suite for the JavaScript app. The second runs the Python unit tests for the API.

npm run test
python api.py

You can also run the JavaScript tests in watch mode by passing an additional flag into the npm run-script command.

npm run test -- -w

Styling and Design

The style and design libraries are from Materialize. Reference React Materialize for designing with this project.

Scrape GeoLocation Data for Logon Source IP

After you have imported logons.csv into MongoDB and started the container, you can run this command and get all geo location data form ip addresses

cd server
pm2 addGeoLoc.js --name addGeo