Compromised Credit Cards for Sale

Sector: Any
Company size: All
Department: Intel Team, CSIRT, Fraud Team, SOC

Criminals steal card data by placing skimmers over card readers at payment points, impersonating ecommerce domains (typosquatting) or infecting devices with malware to record payment information on ecommerce sites. They then sell the information from stolen credit cards on dark web markets for threat actors to commit financial fraud for as little as $5.

Cybersixgill continuously monitors leak sites and marketplaces on the cybercriminal underground in real-time, maintaining our connections to limited access marketplaces and dark web forums. We give security teams a streamlined view of their organizations’ exposure to underground markets exposing identity theft, leaked credentials including usernames and passwords, and typosquatting activity.

Using our threat intelligence, your security team can determine the cause of the data breach and intercept the sale of stolen credit cards to protect your customers. Set up customizable alerts to notify you of credit card data leaked on the deep and dark web from sources including instant messaging apps, IRC chats and limited-access dark web forums and marketplaces.

Cybersixgill instantly collects and categorizes data on compromised credit card data and personal information from the underground so you can receive a breakdown of leaked credit cards by BINs, geography or issuer to implement a root-cause analysis and proactively defend against threats to your organization, assets and customers.

Credit card on a keyboard

Key capabilities delivered by Cybersixgill for this use case:

Immediate detection of compromised credit cards for sale on the dark web

Comprehensive, real-time coverage of dark web, deep web, IM apps and paste sites

OCR image-to-text and multi-language intel extraction

Intuitive search functionality to investigate threats

Understand the origin of stolen credit cards on the dark web

Break down leaked credit cards by issuer, geography or BIN

How to identify leaked credentials

Explore the following Cybersixgill solutions which address this use case: