Detecting Account Farming on AI APIs With Device and Network Signals
Blog post from Didit
Didit's device and network analysis focuses on detecting device-level abuse in account farming by identifying the reuse of a small pool of physical hardware and network paths to create a large number of accounts. By analyzing signals across duplication, integrity, and network categories, the system can distinguish between legitimate and suspicious activities. High-value codes like DEVICE_RECOVERED_HIGH_CONFIDENCE and AUTOMATION_FRAMEWORK_DETECTED indicate potential abuse, while duplication signals require corroboration. The analysis is priced at $0.03 per check or as part of a $0.33 full verification bundle, offering configurable warning actions to manage verification processes effectively. These insights are particularly useful for AI API platforms, marketplaces, and gig platforms to mitigate abuse through emulator farms and unauthorized account creation.
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