- DoubleVerify (DV, Financial) uncovers a $2.5 million fraud scheme involving 35 million spoofed mobile devices.
- ShadowBot targeted mobile and connected TV environments using rudimentary automation techniques.
- DV's AI-powered Fraud Lab successfully detected the amateur-level mistakes of ShadowBot.
DoubleVerify (DV) (DV), a premier software firm specializing in verifying media quality and optimizing ad performance, has exposed a widespread fraud scheme, termed ShadowBot. The fraudulent operation, active since the beginning of 2025, has lured an estimated $2.5 million from unprotected advertisers, involving over 35 million spoofed mobile devices in just the first quarter of 2025.
The ShadowBot operation was particularly focused on mobile and Connected TV (CTV) sectors. The DV Fraud Lab uncovered this scheme by identifying several key red flags. These included the use of outdated screen resolutions by emulators, overly aggressive traffic generation patterns, suspicious IP activity through anonymizing proxies, a lack of behavioral diversity in device activity, and improbable engagement patterns, such as devices opening ten spoofed apps in just nine minutes.
Gilit Saporta, VP Product, Fraud & Quality at DV, highlighted the implications of the scheme, stating, "ShadowBot shows that fraud doesn’t need to be sophisticated to be costly." Despite these challenges, DV clients remained protected due to the firm's advanced fraud detection capabilities. Lisa Toledano of DV emphasized the susceptibility of emerging media environments to such fraud due to their rapid growth and limited visibility.
Wayne Tassie, Group Director at DoubleVerify, underlined the importance of transparency and accountability in combating fraud, stating that safeguarding advertisers' investments not only preserves brand equity but also maintains trust and investment integrity in the digital advertising ecosystem. DV's ongoing efforts in monitoring and overcoming fraud schemes ensure that brands can safeguard their media investments with confidence.
