Conference Paper
Sonar: Detecting SS7 Redirection Attacks Via Call Audio-Based Distance Bounding
Christian Peeters, Hadi Abdullah, Nolen Scaife, Jasmine Bowers, Patrick Traynor, Bradley Reaves, and Kevin Butler
Proceedings of the IEEE Symposium on Security and Privacy, 2018
Detects SS7 call redirection attacks by measuring audio round-trip times, catching 100% of real-world redirections in live network tests.
Abstract
The global telephone network is relied upon by billions every day. Central to its operation is the Signaling System 7 (SS7) protocol, which is used for setting up calls, managing mobility, and facilitating many other network services. This protocol was originally built on the assumption that only a small number of trusted parties would be able to directly communicate with its core infrastructure. As a result, SS7 — as a feature — allows all parties with core access to redirect and intercept calls for any subscriber anywhere in the world. Unfortunately, increased interconnectivity with the SS7 network has led to a growing number of illicit call redirection attacks. We address such attacks with Sonar, a system that detects the presence of SS7 redirection attacks by securely measuring call audio round-trip times between telephony devices. This approach works because redirection attacks force calls to travel longer physical distances than usual, thereby creating longer end-to-end delay. We design and implement a distance bounding-inspired protocol that allows us to securely characterize the round-trip time between the two endpoints. We then use custom hardware deployed in 10 locations across the United States and a redirection testbed to characterize how distance affects round trip time in phone networks. We develop a model using this testbed and show Sonar is able to detect 70.9% of redirected calls between call endpoints of varying attacker proximity (300–7100 miles) with low false positive rates (0.3%). Finally, we ethically perform actual SS7 redirection attacks on our own devices with the help of an industry partner to demonstrate that Sonar detects 100% of such redirections in a real network (with no false positives). As such, we demonstrate that telephone users can reliably detect SS7 redirection attacks and protect the integrity of their calls.
Citation (IEEE)
C. Peeters, H. Abdullah, N. Scaife, J. Bowers, P. Traynor, B. Reaves, and K. Butler, “Sonar: Detecting SS7 Redirection Attacks Via Call Audio-Based Distance Bounding,” in Proceedings of the IEEE Symposium on Security and Privacy, 2018.
BibTeX
@inproceedings{pas+18,
author = {Peeters, Christian and Abdullah, Hadi and Scaife, Nolen and Bowers, Jasmine and Traynor, Patrick and {Bradley Reaves} and Butler, Kevin},
booktitle = {Proceedings of the {IEEE} Symposium on Security and Privacy},
date = {2018-05},
title = {Sonar: Detecting {SS7} Redirection Attacks Via Call Audio-Based Distance Bounding},
}