Security analysis on InfiniBand protocol implementations
Abstract
The growing popularity of high performance computing has led to a new focus on bypassing or eliminating traditional I/O operations that are usually the bottlenecks for fast processing of large data volumes. One such solution uses a new network communication protocol called InfiniBand (IB) which supports remote direct memory access without making two copies of data (one in user space and the other in kernel space) and thus provides very low latency and very high throughput. To this end, for many industries, IB has now become a promising inter-connect protocol over Ethernet technologies. Ensuring the security of this new protocol is critical since more and more companies are moving towards it. To ensure the security of IB, the first step is to have a thorough understand of the vulnerabilities of its current implementations, which is unfortunately still missing in the literature. In this paper, we aim to fill this gap. In particular, we perform a static code analysis as well as protocol testing in order to examine security features in IB architecture from the implementation perspective. While our extensive penetration testing could not find any significant security loopholes; there are certain aspects in both the design and the implementations that need to be addressed. Our focus is in the implementation perspective. Specifically, we found there is a significant use for a number of vulnerable functions (e.g., memcpy, sprintf, and char) as well as obsolete functions (e.g., memalign) that we believe should be replaced with alternative functions such as memmove, snprintf, getline, and posix memalign. We believe our work will benefit both the protocol developers as well as the users by taking the first step to ensure the security of IB protocol.
Publication Title
2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016
Recommended Citation
Subedi, K., Dasgupta, D., & Chen, B. (2017). Security analysis on InfiniBand protocol implementations. 2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016 https://doi.org/10.1109/SSCI.2016.7849903