Live Lesson: Labtainers: A Docker-based Framework for Cybersecurity Labs


Cynthia E. Irvine, Michael F. Thompson, Michael McCarrin, and Jean Khosalim, Naval Postgraduate School


Successful lab designs are a valuable resource that should be re-used and shared among educators and between institutions. A collaborative, community-sourced design effort maximizes the benefit of the effort and expertise required to build and test an effective lab exercise. Unfortunately, infrastructure requirements, heterogeneous operating environments, and the desire to incentivize individual student work pose significant challenges that necessitate frequent updating, redesigning and retesting of assignments, creating a significant maintenance burden. To address these challenges, we present Labtainers: a container-based framework for the development, deployment and assessment of Linux-based cyber security lab exercises. Docker containers present a consistent environment that reduces the need for frequent updates, but with considerably less overhead than VMbased approaches. This enables a modest laptop to host labs consisting of multiple networked components. As such, the Labtainers framework is able to simulate a variety of security-relevant scenarios on a standalone student machine, without the need for elaborate infrastructure. Moreover, Labtainers’ scripting support allows exercises to be customized on a per-student basis, then collected and evaluated automatically on the instructor machine. This capability enables the instructor to assign exercises where each solution is unique to the student with little or no increase in complexity of lab setup or assessment.

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@inproceedings {205233,
author = {Cynthia E. Irvine and Michael F. Thompson and Michael McCarrin and Jean Khosalim},
title = {Live Lesson: Labtainers: A Docker-based Framework for Cybersecurity Labs},
booktitle = {2017 USENIX Workshop on Advances in Security Education (ASE 17)},
year = {2017},
address = {Vancouver, BC},
url = {},
publisher = {USENIX Association},
month = aug