AddrMiner: A Comprehensive Global Active IPv6 Address Discovery System


Guanglei Song, Jiahai Yang, Lin He, Zhiliang Wang, Guo Li, Chenxin Duan, and Yaozhong Liu, Tsinghua University; Zhongxiang Sun, Beijing Jiaotong University


Fast Internet-wide scanning is essential for network situational awareness and asset evaluation. However, the vast IPv6 address space makes brute-force scanning infeasible. Although state-of-the-art techniques have made effective attempts, these methods do not work in seedless regions, while the detection efficiency is low in regions with seeds. Moreover, the constructed hitlists with low coverage cannot truly represent the active IPv6 address landscape of the Internet.

This paper introduces AddrMiner, a global active IPv6 address probing system, making IPv6 active address probing systematic, comprehensive, and economical. We divide the IPv6 address space regions into three kinds according to the number of seed addresses and propose a probing algorithm for each of them. For the regions with no seeds, we propose AddrMiner-N, leveraging an organization association strategy to mine active addresses. It finds active addresses covering 86.4K BGP prefixes, accounting for 81.6\% of the probed BGP prefixes. For the regions with few seeds, we propose AddrMiner-F, utilizing a similarity matching strategy to probe active addresses further. The hit rate of active address probing is improved by 70\%-150\% compared to existing algorithms. For the regions with sufficient seeds, we propose AddrMiner-S to generate target addresses based on reinforcement learning dynamically. It nearly doubles the hit rate compared to the state-of-the-art algorithms. Finally, we deploy AddrMiner and discover 2.1 billion active IPv6 addresses, including 1.7 billion de-aliased active addresses and 0.4 billion aliased addresses, through continuous probing for 13 months. We would like to further open the door of IPv6 measurement studies by publicly releasing AddrMiner and sharing our data.

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@inproceedings {280700,
author = {Guanglei Song and Jiahai Yang and Lin He and Zhiliang Wang and Guo Li and Chenxin Duan and Yaozhong Liu and Zhongxiang Sun},
title = {{AddrMiner}: A Comprehensive Global Active {IPv6} Address Discovery System},
booktitle = {2022 USENIX Annual Technical Conference (USENIX ATC 22)},
year = {2022},
isbn = {978-1-939133-29-19},
address = {Carlsbad, CA},
pages = {309--326},
url = {},
publisher = {USENIX Association},
month = jul

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