Read This Paper to Get $50 Million:* An Analysis of Mobile Messaging Scams Using Reddit Data

2026-05-15

AI Summary

This study addresses the escalating and evolving threat of mobile messaging scams, which increasingly evade existing detection tools. Leveraging a dataset of 175,430 user-reported scam messages from Reddit spanning June 2020 to December 2025, the authors systematically analyze usage patterns of phone numbers, URLs, and textual content in fraudulent communications. The work reveals, for the first time at scale, the rapid rise of “reply-based scams,” which exhibit a compound annual growth rate of 99.98%—significantly outpacing the 57.29% growth of click-based scams. Through web scraping, content analysis, statistical modeling, and empirical evaluation of leading commercial and open-source detection systems, the study demonstrates that current methods perform worst against reply-based scams, highlighting their evasion capabilities and exposing critical limitations in contemporary detection technologies. These findings underscore the urgent need for more sophisticated and accurate scam detection mechanisms.

Abstract

Mobile messaging scams--fraudulent messages delivered over SMS and other mobile applications--have become a persistent and evolving security threat, yet the attributes underlying these campaigns remain unclear. This study seeks to address this gap by examining trends in mobile messaging scams and testing the effectiveness of commercial and open-source off-the-shelf detection tools. We characterize mobile messaging scam operations, focusing on how phone numbers, URLs, and text content are used across campaigns. To achieve this objective, we collect and measure a dataset of 175,430 user-reported mobile messaging scams from Reddit between June 2020 and December 2025. While reply-based scams constitute only 50% of our dataset, their compound annual growth rate (99.98%) is nearly twice that of click-based scams (57.29%). Critically, reply-based scams also show the lowest detector performance--despite identifiable similarities in text content and phone number origin within categories--indicating that current off-the-shelf tools are ineffective. These results suggest that further development of detectors is necessary to defend against this rapidly changing ecosystem. By examining a range of message attributes, this work provides new insights into mobile messaging scams, informing the design of more targeted and robust detection methods.

Problem

• mobile messaging scams
• SMS fraud
• scam detection
• reply-based scams
• cybersecurity

Innovation

• mobile messaging scams
• reply-based scams
• scam detection
• Reddit dataset
• off-the-shelf tools