WhizRT: Simulated Intelligent Cybersecurity Red Team

We propose an innovative solution that includes a novel, automated and intelligent/adaptive red team attacker engine, together with a virtualized playing field testbed (with lifecycle automation, adaptive scoring and more). WhizRT will be able to intelligently choose its actions through an attack behavior tree and execute attack steps across the hands-on playing field. It combines state-of-the-art machine learning with attack tree models and automated attack execution. The playing field is an actual networked IT environment hosted within a virtual machine environment. Using artificial intelligence (AI) techniques (esp. artificial neural networks), the attacker can adapt its choices of attack steps over time by learning from the defenders behaviors, successes/failures etc.The project revolves around two broad areas, the WhizRT intelligent red team system (based on AI, attack behavior trees, and attack step execution), and the training game concept and testbed (based on interconnected VMs with lifecycle management, scoring, education etc.). WhizRT will be developed to be flexible, and in particular to be deployable in other cybersecurity training game platforms. We are highly qualified and positioned to make the proposed effort a success, and have proven to provide exceptional quality and value (incl. several SBIRs).Approved for Public Release | 18-MDA-9710 (6 Jul 18)