Browser-based visualization tool that uses JSON and an interactive enclosure diagram to visualize networks.

What is on your network? For mid-sized to large enterprises, visualizing all the assets on one screen can prove to be a hairball of a challenge.

CRviz is our first attempt at visualizing networks differently, utilizing circle-packing techniques to easily visualize some 10k nodes (and then some). It is still an early prototype and is actively under development, but we want to share this tool in its formative stage because we think that our approach has the potential to improve the scalability and legibility of network data, and also because we want feedback. Check out our demo (or deploy it for yourself, using our sample data sets or your own JSON file) and send us your suggestions and comments!

A Python-based application that leverages software defined networks (SDN) to acquire and then feed network traffic to a number of learning techniques. Poseidon’s goal is to have machine learning algorithms that predict both the type of device and if it acts normally or abnormally.

We believe that the widespread adoption of Software-Defined Networks (SDN) is inevitable. However, most SDN offerings lack security emphasis, much less methods to enhance operational security, without situational awareness and context, defending a difficult proposition. SDN has the potential to provide network defenders with powerful new capabilities, as well as augment defensive action.

This project utilizes both SDN and machine learning techniques to answer two questions:

1. What is on the network; and
2. What is it doing?

This project is a joint effort between two IQT Labs: Lab41 and Cyber Reboot.