How INETCO BullzAI® defends against Ghost Tap relay attacks and contactless payment fraud in milliseconds

Monitor every contactless payment in real-time to detect deviations in round trip times or unexpected transaction re-routing to unsecure terminals, and analyze every transaction field for anomalies in POS Entry mode and EMV chip data – correlating these signals with unusual spending behavior, device fingerprints, IP addresses, transaction bursts and geo-location velocity to validate proximity between the card use and device

Update adaptive fraud risk scores after every transaction with supervised and unsupervised machine learning models that instantly flag “out-of-character” spending behavior or usage patterns for cards, devices and terminals that could be associated with relay attacks – including high risk or rogue terminal IDs, rapid fire micro-spend charges, unusual geographic location or impossible travel, or device fingerprint mismatches between the mobile wallet being used and the registered device ID

Improve authorization decisions for every contactless payment transaction and precisely block or rate limit high risk transactions tied to NFC relay indicators or mule activity – with attention to inconsistencies between the card’s reported activity and the terminal’s reported activity, failed or weak card verification methods in combination with high transaction amounts, indication of PIN bypass in the terminal verification results without disrupting legitimate customers and before the funds move