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Cybercrime is continuously growing in numbers and becoming moresophisticated. Currently, there are various monetisation and money launderingmethods, creating a huge, underground economy worldwide. A clear indicator ofthese activities is online marketplaces which allow cybercriminals to tradetheir stolen assets and services. While traditionally these marketplaces areavailable through the dark web, several of them have emerged in the surfaceweb. In this work, we perform a longitudinal analysis of a surface webmarketplace. The information was collected through targeted web scrapping thatallowed us to identify hundreds of merchants' profiles for the most widely usedsurface web marketplaces. In this regard, we discuss the products traded inthese markets, their prices, their availability, and the exchange currency.This analysis is performed in an automated way through a machine learning-basedpipeline, allowing us to quickly and accurately extract the needed information.The outcomes of our analysis evince that illegal practices are leveraged insurface marketplaces and that there are not effective mechanisms towards theirtakedown at the time of writing.

The Cynicism of Modern Cybercrime: Automating the Analysis of Surface Web Marketplaces