VulnerVAN: Automating the Generation of Vulnerable Network Scenarios for Cybersecurity Events and Training Exercises
Abstract
In this report, we present VulnerVAN, a toolset for automating the generation of vulnerable network scenarios to support cybersecurity training and exercise. Cyber training is becoming increasingly important. People use cyber ranges for training Cyber Protection Teams. Currently, it takes months to plan training exercises, and the process is largely manual. This is because it is hard to plan complex scenarios with multistage attacks and is both labor-intensive and time-consuming. As a result, we designed and developed VulnerVAN. We describe the architecture of VulnerVAN and how the design of the components enables automated generation of vulnerable network scenarios. We also provide examples and use cases to illustrate the functionalities of VulnerVAN.
Document Details
- Document Type
- Technical Report
- Publication Date
- Feb 08, 2021
- Accession Number
- AD1123194
Entities
People
- Alexander Poylisher
- Blaine Hoffman
- Cho-yu J. Chiang
- E. A. Newcomb
- Gary Walther
- Jason A. Youzwak
- Matthew Witkowski
- Michelle Wolberg
- Norbou Buchler
- Ritu Chadha
- Shridatt Sugrim
- Sridhar Venkatesan