IPvSeeYou: Exploiting Leaked Identifiers in IPv6 for Street-Level Geolocation
August 14, 2022 ยท Declared Dead ยท ๐ IEEE Symposium on Security and Privacy
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Erik Rye, Robert Beverly
arXiv ID
2208.06767
Category
cs.NI: Networking & Internet
Cross-listed
cs.CR
Citations
27
Venue
IEEE Symposium on Security and Privacy
Last Checked
3 months ago
Abstract
We present IPvSeeYou, a privacy attack that permits a remote and unprivileged adversary to physically geolocate many residential IPv6 hosts and networks with street-level precision. The crux of our method involves: 1) remotely discovering wide area (WAN) hardware MAC addresses from home routers; 2) correlating these MAC addresses with their WiFi BSSID counterparts of known location; and 3) extending coverage by associating devices connected to a common penultimate provider router. We first obtain a large corpus of MACs embedded in IPv6 addresses via high-speed network probing. These MAC addresses are effectively leaked up the protocol stack and largely represent WAN interfaces of residential routers, many of which are all-in-one devices that also provide WiFi. We develop a technique to statistically infer the mapping between a router's WAN and WiFi MAC addresses across manufacturers and devices, and mount a large-scale data fusion attack that correlates WAN MACs with WiFi BSSIDs available in wardriving (geolocation) databases. Using these correlations, we geolocate the IPv6 prefixes of $>$12M routers in the wild across 146 countries and territories. Selected validation confirms a median geolocation error of 39 meters. We then exploit technology and deployment constraints to extend the attack to a larger set of IPv6 residential routers by clustering and associating devices with a common penultimate provider router. While we responsibly disclosed our results to several manufacturers and providers, the ossified ecosystem of deployed residential cable and DSL routers suggests that our attack will remain a privacy threat into the foreseeable future.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
๐ Similar Papers
In the same crypt โ Networking & Internet
R.I.P.
๐ป
Ghosted
R.I.P.
๐ป
Ghosted
Federated Learning in Mobile Edge Networks: A Comprehensive Survey
R.I.P.
๐ป
Ghosted
A Survey of Indoor Localization Systems and Technologies
R.I.P.
๐ป
Ghosted
Survey of Important Issues in UAV Communication Networks
R.I.P.
๐ป
Ghosted
Network Function Virtualization: State-of-the-art and Research Challenges
R.I.P.
๐ป
Ghosted
Applications of Deep Reinforcement Learning in Communications and Networking: A Survey
Died the same way โ ๐ป Ghosted
R.I.P.
๐ป
Ghosted
Language Models are Few-Shot Learners
R.I.P.
๐ป
Ghosted
PyTorch: An Imperative Style, High-Performance Deep Learning Library
R.I.P.
๐ป
Ghosted
XGBoost: A Scalable Tree Boosting System
R.I.P.
๐ป
Ghosted