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Sending Out an SMS: Characterizing the Security of the SMS Ecosystem with Public Gateways

Authors: Bradley Reaves; Nolen Scaife; Dave Tian; Logan Blue; Patrick Traynor; Kevin R. B. Butler;

Sending Out an SMS: Characterizing the Security of the SMS Ecosystem with Public Gateways

Abstract

Text messages sent via the Short Message Service (SMS) have revolutionized interpersonal communication. Recent years have also seen this service become a critical component of the security infrastructure, assisting with tasks including identity verification and second-factor authentication. At the same time, this messaging infrastructure has become dramatically more open and connected to public networks than ever before. However, the implications of this openness, the security practices of benign services, and the malicious misuse of this ecosystem are not well understood. In this paper, we provide the first longitudinal study to answer these questions, analyzing nearly 400,000 text messages sent to public online SMS gateways over the course of 14 months. From this data, we are able to identify not only a range of services sending extremely sensitive plaintext data and implementing low entropy solutions for one-use codes, but also offer insights into the prevalence of SMS spam and behaviors indicating that public gateways are primarily used for evading account creation policies that require verified phone numbers. This latter finding has significant implications for research combatting phone-verified account fraud and demonstrates that such evasion will continue to be difficult to detect and prevent.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
32
Top 10%
Top 10%
Top 10%
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