It’s that special time of year when the days get shorter, the CPU temps run just a little cooler, and the bits are ripening on the binary search trees. Of course I mean that Hacktoberfest is finally here again.
Network defenders are bombarded with information, and the environments they work in can be incredibly complex. To help better visualize what's on a network, we released two Open Source projects that work together.
Late last year the Cyber Reboot team got the opportunity to run a deployment of our Poseidon project on the high-performance network, SCinet. Read about the changes we made to get it working at high-speed!
Using certificates from python can be a challenging and counterintuitive process, and the default options available to developers are somewhat limited. This blog explores enhance the open source Requests Toolbelt library.
Hacktoberfest — which takes place throughout the month of October — has become an exciting time of the year for open source software. Last year we were happy to report a very successful Hacktoberfest turnout where we contributed to 85 different projects and attracted 33 new contributors to our projects. This year we hope to continue that trend.
Lab41 outlines how Poseidon open source code uses machine learning to classify devices on a network using packet capture data.
This is the third post in a 3-part series about CRviz, a network visualization tool developed by Cyber Reboot.
Cyber Reboot explains how they designed CRviz — an open source tool that uses an interactive “enclosure diagram” to visualize network devices.
Cyber Reboot describes the problems seen with a commonly used network visualization technique, the force-directed graph, and suggests the enclosure diagram as an alternative.
Building a data set to train from is the first step to any machine learning endeavor, and the old adage “garbage in, garbage out” is still true as ever in the cyber domain.
CyberReboot has open-sourced a tool that provides a quick visual snapshot, or thumbnail, of a network packet capture (PCAP file) from the perspective of a single host/device in four distinct areas.
Cyber Reboot explores lateral movement detection for two primary reasons: 1) it is a key component to most computer intrusions, and part of a bigger issue that remains a national security problem, and 2) the application of machine learning and SDN presents new opportunities in detection.