Researchers Show How To Steal Payment Card Data From PIN Pads

Attack works even against chip-enabled EMV smartcards.

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BLACK HAT USA—Las Vegas—The manner in which many PIN pads used by consumers to pay for purchases and communicate with point-of-sale systems make it very easy for attackers to steal payment card data, researchers warned here this week.

Using a Raspberry Pi with specialized software and a laptop running a POS simulator, researchers Nir Valtman and Patrick Watson of NCR Corp showed how an attacker could intercept communications between a card reader and a POS system and extract sensitive cardholder data from it.

The problem, according to the researchers, has to do with a failure by many payment card readers to properly authenticate the systems with which they communicate and to encrypt data before sending it to POS systems.

When a card is swiped through a PIN pad or other card reader, the device reads data from either the magnetic stripe on the back of the card or the embedded microchip in it in the case of EMV smartcards.

The data is then sent to the POS system either via an Ethernet cable or via a serial port if the card reader is integrated with the POS system. If the payment system is online, as is typically the case, the data then goes to the payment processor for authorization. If the system is offline, the cardholder data is typically stored in encrypted fashion on the payment application server and then sent for processing later.

Regardless of the architecture, or whether the payment system is online or offline, an attacker can intercept the communication between the card reader and the payment application by routing it through a man-in-the-middle device running a shim such as the Raspberry Pi used in the demonstration, the researchers said.

The attack works because PIN pad devices from most manufactures do not authenticate POS systems when sending cardholder data. In other words, the devices do little to ensure that they are actually communicating with a legitimate POS system when sending cardholder data.

As a result, it becomes relatively easy for someone to stick a rogue device between the POS system and the PIN pad and capture the data flowing through. Because the data is usually unencrypted, it becomes easy for attackers to steal cardholder data.

The weaknesses make it possible for attackers to steal cardholder data even from chip-enabled EMV smartcards, which are touted as more secure than cards based on magnetic strip technology, the two researchers said.

In order to install such an MITM device, an individual would need physical access to the payment network. But it is also possible to intercept data from a PIN pad by making certain easy modifications to the Dynamic Link Library (DLL) on the payment application itself, according to the researchers.

As part of their demonstration, Valtman and Watson showed how an attacker could actually send prompts to the PIN pad to trick users into parting with even more information. For example, PINs that are entered into a PIN pad are encrypted. But an attacker could try to get the PIN by sending a message to the PIN pad screen, prompting the user to re-enter their PIN.

While such a ruse may not always work with security-savvy consumers, it will likely work with those who are less aware, they said.

According to Valtman and Watson, PIN pads and card readers from many manufacturers are susceptible to the kind of attacks they demonstrated at Black Hat. 

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About the Author

Jai Vijayan, Contributing Writer

Jai Vijayan is a seasoned technology reporter with over 20 years of experience in IT trade journalism. He was most recently a Senior Editor at Computerworld, where he covered information security and data privacy issues for the publication. Over the course of his 20-year career at Computerworld, Jai also covered a variety of other technology topics, including big data, Hadoop, Internet of Things, e-voting, and data analytics. Prior to Computerworld, Jai covered technology issues for The Economic Times in Bangalore, India. Jai has a Master's degree in Statistics and lives in Naperville, Ill.

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