Entries Tagged "PINs"

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PIN-Stealing Android Malware

This is an old piece of malware—the Chameleon Android banking Trojan—that now disables biometric authentication in order to steal the PIN:

The second notable new feature is the ability to interrupt biometric operations on the device, like fingerprint and face unlock, by using the Accessibility service to force a fallback to PIN or password authentication.

The malware captures any PINs and passwords the victim enters to unlock their device and can later use them to unlock the device at will to perform malicious activities hidden from view.

Posted on January 9, 2024 at 7:03 AM • View Comments

Interesting Attack on the EMV Smartcard Payment Standard

It’s complicated, but it’s basically a man-in-the-middle attack that involves two smartphones. The first phone reads the actual smartcard, and then forwards the required information to a second phone. That second phone actually conducts the transaction on the POS terminal. That second phone is able to convince the POS terminal to conduct the transaction without requiring the normally required PIN.

From a news article:

The researchers were able to demonstrate that it is possible to exploit the vulnerability in practice, although it is a fairly complex process. They first developed an Android app and installed it on two NFC-enabled mobile phones. This allowed the two devices to read data from the credit card chip and exchange information with payment terminals. Incidentally, the researchers did not have to bypass any special security features in the Android operating system to install the app.

To obtain unauthorized funds from a third-party credit card, the first mobile phone is used to scan the necessary data from the credit card and transfer it to the second phone. The second phone is then used to simultaneously debit the amount at the checkout, as many cardholders do nowadays. As the app declares that the customer is the authorized user of the credit card, the vendor does not realize that the transaction is fraudulent. The crucial factor is that the app outsmarts the card’s security system. Although the amount is over the limit and requires PIN verification, no code is requested.

The paper: “The EMV Standard: Break, Fix, Verify.”

Abstract: EMV is the international protocol standard for smartcard payment and is used in over 9 billion cards worldwide. Despite the standard’s advertised security, various issues have been previously uncovered, deriving from logical flaws that are hard to spot in EMV’s lengthy and complex specification, running over 2,000 pages.

We formalize a comprehensive symbolic model of EMV in Tamarin, a state-of-the-art protocol verifier. Our model is the first that supports a fine-grained analysis of all relevant security guarantees that EMV is intended to offer. We use our model to automatically identify flaws that lead to two critical attacks: one that defrauds the cardholder and another that defrauds the merchant. First, criminals can use a victim’s Visa contact-less card for high-value purchases, without knowledge of the card’s PIN. We built a proof-of-concept Android application and successfully demonstrated this attack on real-world payment terminals. Second, criminals can trick the terminal into accepting an unauthentic offline transaction, which the issuing bank should later decline, after the criminal has walked away with the goods. This attack is possible for implementations following the standard, although we did not test it on actual terminals for ethical reasons. Finally, we propose and verify improvements to the standard that prevent these attacks, as well as any other attacks that violate the considered security properties.The proposed improvements can be easily implemented in the terminals and do not affect the cards in circulation.

Posted on September 14, 2020 at 6:21 AM • View Comments

Bank Card "Master Key" Stolen

South Africa’s Postbank experienced a catastrophic security failure. The bank’s master PIN key was stolen, forcing it to cancel and replace 12 million bank cards.

The breach resulted from the printing of the bank’s encrypted master key in plain, unencrypted digital language at the Postbank’s old data centre in the Pretoria city centre.

According to a number of internal Postbank reports, which the Sunday Times obtained, the master key was then stolen by employees.

One of the reports said that the cards would cost about R1bn to replace. The master key, a 36-digit code, allows anyone who has it to gain unfettered access to the bank’s systems, and allows them to read and rewrite account balances, and change information and data on any of the bank’s 12-million cards.

The bank lost $3.2 million in fraudulent transactions before the theft was discovered. Replacing all the cards will cost an estimated $58 million.

Posted on June 17, 2020 at 6:21 AM • View Comments

Recovering Smartphone Typing from Microphone Sounds

Yet another side-channel attack on smartphones: “Hearing your touch: A new acoustic side channel on smartphones,” by Ilia Shumailov, Laurent Simon, Jeff Yan, and Ross Anderson.

Abstract: We present the first acoustic side-channel attack that recovers what users type on the virtual keyboard of their touch-screen smartphone or tablet. When a user taps the screen with a finger, the tap generates a sound wave that propagates on the screen surface and in the air. We found the device’s microphone(s) can recover this wave and “hear” the finger’s touch, and the wave’s distortions are characteristic of the tap’s location on the screen. Hence, by recording audio through the built-in microphone(s), a malicious app can infer text as the user enters it on their device. We evaluate the effectiveness of the attack with 45 participants in a real-world environment on an Android tablet and an Android smartphone. For the tablet, we recover 61% of 200 4-digit PIN-codes within 20 attempts, even if the model is not trained with the victim’s data. For the smartphone, we recover 9 words of size 7-13 letters with 50 attempts in a common side-channel attack benchmark. Our results suggest that it not always sufficient to rely on isolation mechanisms such as TrustZone to protect user input. We propose and discuss hardware, operating-system and application-level mechanisms to block this attack more effectively. Mobile devices may need a richer capability model, a more user-friendly notification system for sensor usage and a more thorough evaluation of the information leaked by the underlying hardware.

Blog post.

Posted on April 1, 2019 at 9:44 AM • View Comments

Hacking a Segway

The Segway has a mobile app. It is hackable:

While analyzing the communication between the app and the Segway scooter itself, Kilbride noticed that a user PIN number meant to protect the Bluetooth communication from unauthorized access wasn’t being used for authentication at every level of the system. As a result, Kilbride could send arbitrary commands to the scooter without needing the user-chosen PIN.

He also discovered that the hoverboard’s software update platform didn’t have a mechanism in place to confirm that firmware updates sent to the device were really from Segway (often called an “integrity check”). This meant that in addition to sending the scooter commands, an attacker could easily trick the device into installing a malicious firmware update that could override its fundamental programming. In this way an attacker would be able to nullify built-in safety mechanisms that prevented the app from remote-controlling or shutting off the vehicle while someone was on it.

“The app allows you to do things like change LED colors, it allows you to remote-control the hoverboard and also apply firmware updates, which is the interesting part,” Kilbride says. “Under the right circumstances, if somebody applies a malicious firmware update, any attacker who knows the right assembly language could then leverage this to basically do as they wish with the hoverboard.”

Posted on July 21, 2017 at 6:23 AM • View Comments

Forced Authorization Attacks Against Chip-and-Pin Credit Card Terminals

Clever:

The way forced authorisation fraud works is that the retailer sets up the terminal for a transaction by inserting the customer’s card and entering the amount, then hands the terminal over to the customer so they can type in the PIN. But the criminal has used a stolen or counterfeit card, and due to the high value of the transaction the terminal performs a “referral”—asking the retailer to call the bank to perform additional checks such as the customer answering a security question. If the security checks pass, the bank will give the retailer an authorisation code to enter into the terminal.

The problem is that when the terminal asks for these security checks, it’s still in the hands of the criminal, and it’s the criminal that follows the steps that the retailer should have. Since there’s no phone conversation with the bank, the criminal doesn’t know the correct authorisation code. But what surprises retailers is that the criminal can type in anything at this stage and the transaction will go through. The criminal might also be able to bypass other security features, for example they could override the checking of the PIN by following the steps the retailer would if the customer has forgotten the PIN.

By the time the terminal is passed back to the retailer, it looks like the transaction was completed successfully. The receipt will differ only very subtly from that of a normal transaction, if at all. The criminal walks off with the goods and it’s only at the end of the day that the authorisation code is checked by the bank. By that time, the criminal is long gone. Because some of the security checks the bank asked for weren’t completed, the retailer doesn’t get the money.

Posted on December 7, 2015 at 5:35 AM • View Comments

Brute-Forcing iPhone PINs

This is a clever attack, using a black box that attaches to the iPhone via USB:

As you know, an iPhone keeps a count of how many wrong PINs have been entered, in case you have turned on the Erase Data option on the Settings | Touch ID & Passcode screen.

That’s a highly-recommended option, because it wipes your device after 10 passcode mistakes.

Even if you only set a 4-digit PIN, that gives a crook who steals your phone just a 10 in 10,000 chance, or 0.1%, of guessing your unlock code in time.

But this Black Box has a trick up its cable.

Apparently, the device uses a light sensor to work out, from the change in screen intensity, when it has got the right PIN.

In other words, it also knows when it gets the PIN wrong, as it will most of the time, so it can kill the power to your iPhone when that happens.

And the power-down happens quickly enough (it seems you need to open up the iPhone and bypass the battery so you can power the device entirely via the USB cable) that your iPhone doesn’t have time to subtract one from the “PIN guesses remaining” counter stored on the device.

Because every set of wrong guesses requires a reboot, the process takes about five days. Still, a very clever attack.

More details.

Posted on March 30, 2015 at 6:47 AM • View Comments

Security Risks from Remote-Controlled Smart Devices

We’re starting to see a proliferation of smart devices that can be controlled from your phone. The security risk is, of course, that anyone can control them from their phones. Like this Japanese smart toilet:

The toilet, manufactured by Japanese firm Lixil, is controlled via an Android app called My Satis.

But a hardware flaw means any phone with the app could activate any of the toilets, researchers say.

The toilet uses bluetooth to receive instructions via the app, but the Pin code for every model is hardwired to be four zeros (0000), meaning that it cannot be reset and can be activated by any phone with the My Satis app, a report by Trustwave’s Spiderlabs information security experts reveals.

This particular attack requires Bluetooth connectivity and doesn’t work over the Internet, but many other similar attacks will. And because these devices send to have their code in firmware, a lot of them won’t be patchable. My guess is that the toilet’s manufacturer will ignore it.

On the other end of your home, a smart TV protocol is vulnerable to attack:

The attack uses the Hybrid Broadcast Broadband TV (HbbTV) standard that is widely supported in smart television sets sold in Europe.

The HbbTV system was designed to help broadcasters exploit the internet connection of a smart TV to add extra information to programmes or so advertisers can do a better job of targeting viewers.

But Yossef Oren and Angelos Keromytis, from the Network Security Lab, at Columbia University, have found a way to hijack HbbTV using a cheap antenna and carefully crafted broadcast messages.

The attacker could impersonate the user to the TV provider, websites, and so on. This attack also doesn’t use the Internet, but instead a nearby antenna. And in this case, we know that the manufacturers are going to ignore it:

Mr Oren said the standards body that oversaw HbbTV had been told about the security loophole. However, he added, the body did not think the threat from the attack was serious enough to require a re-write of the technology’s security.

Posted on June 10, 2014 at 8:24 AM • View Comments

Guessing Smart Phone PINs by Monitoring the Accelerometer

“Practicality of Accelerometer Side Channels on Smartphones,” by Adam J. Aviv. Benjamin Sapp, Matt Blaze, and Jonathan M. Smith.

Abstract: Modern smartphones are equipped with a plethora of sensors that enable a wide range of interactions, but some of these sensors can be employed as a side channel to surreptitiously learn about user input. In this paper, we show that the accelerometer sensor can also be employed as a high-bandwidth side channel; particularly, we demonstrate how to use the accelerometer sensor to learn user tap and gesture-based input as required to unlock smartphones using a PIN/password or Android’s graphical password pattern. Using data collected from a diverse group of 24 users in controlled (while sitting) and uncontrolled (while walking) settings, we develop sample rate independent features for accelerometer readings based on signal processing and polynomial fitting techniques. In controlled settings, our prediction model can on average classify the PIN entered 43% of the time and pattern 73% of the time within 5 attempts when selecting from a test set of 50 PINs and 50 patterns. In uncontrolled settings, while users are walking, our model can still classify 20% of the PINs and 40% of the patterns within 5 attempts. We additionally explore the possibility of constructing an accelerometer-reading-to-input dictionary and find that such dictionaries would be greatly challenged by movement-noise and cross-user training.

Article.

Posted on February 15, 2013 at 6:48 AM • View Comments

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Sidebar photo of Bruce Schneier by Joe MacInnis.