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Give and Take: An End-To-End Investigation of Giveaway Scam Conversion Rates

Enze Liu, George Kappos, Eric Mugnier, Luca Invernizzi, Stefan Savage, David Tao, Kurt Thomas, Geoffrey M. Voelker, Sarah Meiklejohn

TL;DR

It is found that 1 in 1000 scam tweets, and 4 in 100,000 livestream views, net a victim, and that scammers managed to extract nearly $4.62 million from just hundreds of victims during the measurement window.

Abstract

Scams -- fraudulent schemes designed to swindle money from victims -- have existed for as long as recorded history. However, the Internet's combination of low communication cost, global reach, and functional anonymity has allowed scam volumes to reach new heights. Designing effective interventions requires first understanding the context: how scammers reach potential victims, the earnings they make, and any potential bottlenecks for durable interventions. In this short paper, we focus on these questions in the context of cryptocurrency giveaway scams, where victims are tricked into irreversibly transferring funds to scammers under the pretense of even greater returns. Combining data from Twitter, YouTube and Twitch livestreams, landing pages, and cryptocurrency blockchains, we measure how giveaway scams operate at scale. We find that 1 in 1000 scam tweets, and 4 in 100,000 livestream views, net a victim, and that scammers managed to extract nearly \$4.62 million from just hundreds of victims during our measurement window.

Give and Take: An End-To-End Investigation of Giveaway Scam Conversion Rates

TL;DR

It is found that 1 in 1000 scam tweets, and 4 in 100,000 livestream views, net a victim, and that scammers managed to extract nearly $4.62 million from just hundreds of victims during the measurement window.

Abstract

Scams -- fraudulent schemes designed to swindle money from victims -- have existed for as long as recorded history. However, the Internet's combination of low communication cost, global reach, and functional anonymity has allowed scam volumes to reach new heights. Designing effective interventions requires first understanding the context: how scammers reach potential victims, the earnings they make, and any potential bottlenecks for durable interventions. In this short paper, we focus on these questions in the context of cryptocurrency giveaway scams, where victims are tricked into irreversibly transferring funds to scammers under the pretense of even greater returns. Combining data from Twitter, YouTube and Twitch livestreams, landing pages, and cryptocurrency blockchains, we measure how giveaway scams operate at scale. We find that 1 in 1000 scam tweets, and 4 in 100,000 livestream views, net a victim, and that scammers managed to extract nearly \$4.62 million from just hundreds of victims during our measurement window.
Paper Structure (39 sections, 5 figures, 3 tables)

This paper contains 39 sections, 5 figures, 3 tables.

Figures (5)

  • Figure 1: Example giveaway scam landing pages promoted via Twitter. Scammers impersonate popular personalities including Brad Garlinghouse (the Ripple CEO) and Elon Musk.
  • Figure 2: Example livestream containing a giveaway scam. The video playing is of Brad Garlinghouse and the scam website is linked to in both the chat and the embedded QR code.
  • Figure 3: The volume of giveaway scam tweets on a given week, between January 1, 2022 and July 7, 2022.
  • Figure 4: The volume of giveaway scam streams and views per week, between July 24, 2023 and January 21, 2024.
  • Figure 5: Effectiveness of keywords