MAST Malicious Activity Simulation Tool

MAST – Malicious Activity Simulation Tool – is a DoD sponsored project which aims to support the conduct of network administrator security training on the very network that the administrator is supposed to manage. A key element of MAST is to use malware mimics to simulate malware behavior. Malware mimics look and behave like real malware except for the damage that real malware causes.

The DoD currently employs Red Teams to conduct network infiltration and security training for network administrators. While red teams provide the most effective training, there are several inherent constraints (limited availability, high expense, inconsistent training and feedback) associated with the use of red teams for training network administrators. MAST addresses these shortfalls by providing automated and simulated actions of a red team that are realistic, repeatable, modular, and dynamic. MAST is safe and designed to work on the trainees’ operational network.

MAST is a client-server system and uses malware mimics to enable simulated adversaries (red teams) and trusted agents (blue teams) to leverage their existing skill sets, and conducts training without an increase in risk while operating within the prescribed limits. Malware mimics used in MAST allow for realistic and observable training of Network Administrators on live, operational networks. Malware mimics are programs that are inherently stable and controllable, but when activated, can produce the desired behaviors of a computer-based network threat. Because malware mimics are safe to use, they can be used effectively for training on live computer networks.

MAST Systems Diagram

MAST is currently under development. The following activities are ongoing:

  • Scenario Development and Testing – Develop a library of scenarios and evaluate their interaction with Host-Based Security System (HBSS)
  • Scalability Testing – Determine how MAST uses system and network resources
  • Enhanced Capabilities – Developing dynamic roll-back script that will return the end host to its pre-training state.

For further information, contact: Dr. Gurminder Singh, Professor, Computer Science Department and MOVES Institute, Naval Postgraduate School, Monterey, CA 93943. gsingh<at>nps.edu

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