In 2017 and 2018, threat actors utilized a toolkit called KoffeyMaker in multiple black box ATM attacks targeting Eastern European financial institutions.
When Kaspersky Lab investigated KoffeyMaker in connection with the attacks, researchers discovered that the devices in the campaign consisted of Windows laptops containing ATM dispenser drivers and a patched KDIAG tool.
Those behind the attacks secretly opened an ATM at each targeted bank, connected the device to the cash dispenser, closed the ATM and walked away with the device still inside the machine.
Returning at a later time, attackers leveraged a USB GPRS modem to gain remote access to the device, run the KDIAG tool and execute a command for the ATM to dispense bank notes before retrieving the laptop — all while another attacker collected the money. Together, they then made their escape with potentially tens of thousands of dollars in tow.
ATM Attacks Aren’t New to Europe
Attacks like those involving KoffeyMaker aren’t new. As reported by Information Security Media Group (ISMG), the number of jackpotting attacks against ATMs in European countries grew by 231 percent in 2017. Of those attacks, the majority were black box campaigns. One of these cases involved the use of Cutlet Maker, ATM malware detected by Kaspersky Lab that is not unlike KoffeyMaker in its design.
Fortunately, law enforcement had some success in arresting criminals during that same span of time. In one of the most noteworthy takedowns, several EU member states and Norway, supported by Europol’s European Cybercrime Centre (EC3) and the Joint Cybercrime Action Taskforce (J-CAT), arrested 27 individuals responsible for conducting black box ATM attacks across Europe.
How to Defend Against Tools Like KoffeyMaker
According to Kaspersky Lab, the only way for banks to defend against black box attacks is to use hardware encryption between an ATM’s computer and dispenser. Organizations should also implement a stronger data security strategy. This plan should include the use of encryption to protect sensitive cloud-based data.