Expert Insight On Scam-as-a-Service Operation Made More Than $6.5 Million In 2020

In a report released yesterday [https://www.group-ib.com/media/mammoth-migration/], security firm Group-IB has described a Russian-speaking scam operation that started targeting users of European marketplaces and classifieds.

The scheme, dubbed Classiscam, is an automated scam as a service designed to steal money and payment data. Experts have so far identified at least 40 active Classiscam gangs that use scam pages mimicking popular classified, marketplace, and delivery companies with every one of them running a separate Telegram bot.

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Andy Renshaw
Andy Renshaw , VP of Payments Strategy & Solutions
InfoSec Expert
January 18, 2021 2:36 pm

<p>These groups operate in plain sight: their ads are genuine, but victims are later directed to a malicious site where their credit card details are harvested. The reason why this type of scam continues to proliferate is that it can yield substantial returns and has a level of credibility – it is not just a matter of stealing victims\’ money once, but to store their payment details and continue to steal funds until the fraud is detected.</p> <p> </p> <p>The scale of the operation is certainly concerning, but there are tools that banks can deploy to identify suspicious transactions, flag them as such, or even block the funds from leaving the victim\’s account in the first place. There is a vital layer of information that lies between what the customer sees and what the payments tells fraud analysts and systems, and where there is a solid AI algorithm in place, malicious activity can be spotted quickly and efficiently. Increased fraud detection efficiency should also be complemented by ongoing customer education, which can also dramatically decrease the number of clicks on malicious ads. Ultimately, the goal of organisations should be to make operations like Classiscam unprofitable, which is the strongest deterrent for fraudsters looking for a quick gain.</p>

Last edited 1 year ago by Andy Renshaw
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