Read This Paper to Get $50 Million:* An Analysis of Mobile Messaging Scams Using Reddit Data
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arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2026
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| _version_ | 1866910225553948672 |
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| author | Lu, Allison Medeiros, Bernardo B. P. Butler, Kevin R. B. Traynor, Patrick |
| author_facet | Lu, Allison Medeiros, Bernardo B. P. Butler, Kevin R. B. Traynor, Patrick |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_16656 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Read This Paper to Get $50 Million:* An Analysis of Mobile Messaging Scams Using Reddit Data Lu, Allison Medeiros, Bernardo B. P. Butler, Kevin R. B. Traynor, Patrick Cryptography and Security Computers and Society 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. |
| title | Read This Paper to Get $50 Million:* An Analysis of Mobile Messaging Scams Using Reddit Data |
| topic | Cryptography and Security Computers and Society |
| url | https://arxiv.org/abs/2605.16656 |