Publication Type
Journal Article
Version
acceptedVersion
Publication Date
7-2019
Abstract
A container is a group of processes isolated from other groups via distinct kernel namespaces and resource allocation quota. Attacks against containers often leverage kernel exploits through the system call interface. In this paper, we present an approach that mines sandboxes and enables fine-grained sandbox enforcement for containers. We first explore the behavior of a container by running test cases and monitor the accessed system calls including types and arguments during testing. We then characterize the types and arguments of system call invocations and translate them into sandbox rules for the container. The mined sandbox restricts the container’s access to system calls which are not seen during testing and thus reduces the attack surface. In the experiment, our approach requires less than eleven minutes to mine a sandbox for each of the containers. The estimation of system call coverage of sandbox mining ranges from 96.4% to 99.8% across the containers under the limiting assumptions that the test cases are complete and only static system/application paths are used. The enforcement of mined sandboxes incurs low performance overhead. The mined sandboxes effectively reduce the attack surface of containers and can prevent the containers from security breaches in reality
Keywords
Container, System call, Sandbox, Testing, Monitoring, Cloud computing, Docker, Seccomp
Discipline
Programming Languages and Compilers | Software Engineering
Research Areas
Software and Cyber-Physical Systems
Publication
Empirical Software Engineering
Volume
24
First Page
4034
Last Page
4070
ISSN
1382-3256
Identifier
10.1007/s10664-019-09737-2
Publisher
Springer Verlag (Germany)
Citation
WAN, Zhiyuan; LO, David; XIA, Xin; and CAI, Liang.
Practical and effective sandboxing for Linux containers. (2019). Empirical Software Engineering. 24, 4034-4070.
Available at: https://ink.library.smu.edu.sg/sis_research/4502
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1007/s10664-019-09737-2