Face Search 1:N: Finding Every Account One Person Controls
Blog post from Didit
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Didit’s Face Search 1:N feature is presented as a biometric tool for identifying multiple accounts associated with the same person by comparing a submitted selfie against faces previously enrolled by a single application, rather than a shared cross-customer database. Available through the POST /v3/face-search endpoint or automatically during liveness checks, it supports duplicate-account detection through a most_similar mode and blocklist screening through a blocklisted_or_approved mode, returning account-linked vendor data, similarity scores, verification dates, session identifiers, and relevant warnings. A duplicate face match remains “Approved” with a DUPLICATED_FACE warning so that customers can apply their own policies, while confirmed blocklist matches return “Declined”; borderline matches are intended for review. The feature can help platforms investigate coordinated account abuse, repeat registrations, marketplace bans, gaming self-exclusion, and identity-fraud networks by linking face matches with device, network, and timeline data, though it does not analyze API traffic or independently detect model extraction. Enrollment and retention depend on the customer’s use of save_api_request and applicable biometric-data privacy obligations, while standalone search thresholds are fixed internally and application logic must determine how to treat similarity results.
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