IMap: Fast and Scalable In-Network Scanning with Programmable Switches

Authors: 

Guanyu Li, Tsinghua University; Menghao Zhang, Tsinghua University; Kuaishou Technology; Cheng Guo, Han Bao, and Mingwei Xu, Tsinghua University; Hongxin Hu, University at Buffalo, SUNY; Fenghua Li, Tsinghua University

Abstract: 

Network scanning has been a standard measurement technique to understand a network’s security situations, e.g., revealing security vulnerabilities, monitoring service deployments. However, probing a large-scale scanning space with existing network scanners is both difficult and slow, since they are all implemented on commodity servers and deployed at the network edge. To address this, we introduce IMap, a fast and scalable in-network scanner based on programmable switches. In designing IMap, we overcome key restrictions posed by computation models and memory resources of programmable switches, and devise numerous techniques and optimizations, including an address-random and rate-adaptive probe packet generation mechanism, and a correct and efficient response packet processing scheme, to turn a switch into a practical high-speed network scanner. We implement an open-source prototype of IMap, and evaluate it with extensive testbed experiments and real-world deployments in our campus network. Evaluation results show that even with one switch port enabled, IMap can survey all ports of our campus network (i.e., a total of up to 25 billion scanning space) in 8 minutes. This demonstrates a nearly 4 times faster scanning speed and 1.5 times higher scanning accuracy than the state of the art, which shows that IMap has great potentials to be the next-generation terabit network scanner with all switch ports enabled. Leveraging IMap, we also discover several potential security threats in our campus network, and report them to our network administrators responsibly.

NSDI '22 Open Access Sponsored by
King Abdullah University of Science and Technology (KAUST)

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BibTeX
@inproceedings {278328,
author = {Guanyu Li and Menghao Zhang and Cheng Guo and Han Bao and Mingwei Xu and Hongxin Hu and Fenghua Li},
title = {{IMap}: Fast and Scalable {In-Network} Scanning with Programmable Switches},
booktitle = {19th USENIX Symposium on Networked Systems Design and Implementation (NSDI 22)},
year = {2022},
isbn = {978-1-939133-27-4},
address = {Renton, WA},
pages = {667--681},
url = {https://www.usenix.org/conference/nsdi22/presentation/li-guanyu},
publisher = {USENIX Association},
month = apr
}

Presentation Video