Recently, there has been substantial research in the area of network security. Correlation of intrusion detection sensor alerts, vulnerability analysis, and threat projection are all being studied in hopes to relieve the workload that analysts have in monitoring their networks. Having an automated algorithm that can estimate the impact of cyber attacks on a network is another facet network analysts could use in defending their networks and gaining better overall situational awareness. Impact assessment involves determining the effect of a cyber attack on a network. Impact algorithms may consider items such as machine importance, connectivity, user accounts, known attacker capability, and similar machine configurations. Due to the increasing number of attacks, constantly changing vulnerabilities, and unknown attacker behavior, automating impact assessment is a non-trivial task. This work develops a virtual terrain that contains network and machine characteristics relevant to impact assessment. Once populated, this virtual terrain is used to perform impact assessment algorithms. The goal of this work is to investigate and propose an impact assessment system to assist network analysts in prioritizing attacks and analyzing overall network status. VTAC is tested with several scenarios over a network with a variety of configurations. Insights into the results of the scenarios, including how the network topologies and network asset configurations affect the impact analysis are discussed
