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The recently proposed DNS extension, EDNS-Client-Subnet (ECS), has been quickly adopted by major Internet companies such as Google to better assign user requests to their servers and improve end-user experience. In this paper, we show that the adoption of ECS also offers unique, but likely unintended, opportunities to uncover details about these companies' operational practices at almost no cost. A key observation is that ECS allows to resolve domain names of ECS adopters on behalf of any arbitrary IP/prefix in the Internet. In fact, by utilizing only a single residential vantage point and relying solely on publicly available information, we are able to (i) uncover the global footprint of ECS adopters with very little effort, (ii) infer the DNS response cacheability and end-user clustering of ECS adopters for an arbitrary network in the Internet, and (iii) capture snapshots of user to server mappings as practiced by major ECS adopters. While pointing out such new measurement opportunities, our work is also intended to make current and future ECS adopters aware of which operational information gets exposed when utilizing this recent DNS extension. General TermsMeasurement.

No abstract

Researchers and practitioners often face the issue of having to attribute an IP address to an organization. For current data this is comparably easy, using services like whois or other databases. Similarly, for historic data, several entities like the RIPE NCC provide websites that provide access to historic records. For large-scale network measurement work, though, researchers often have to attribute millions of addresses. For current data, Team Cymru provides a bulk whois service which allows bulk address attribution. However, at the time of writing, there is no service available that allows historic bulk attribution of IP addresses. Hence, in this paper, we introduce and evaluate our ‘Back-to-the-Future whois’ service, allowing historic bulk attribution of IP addresses on a daily granularity based on CAIDA Routeviews aggregates. We provide this service to the community for free, and also share our implementation so researchers can run instances themselves.

No abstract