Travis Goodspeed went to Twitter recently looking for a good BLE voltmeter for some vehicles.
Pokit Meter quickly came up as a possible solution. For around $100 it has all the features you'd expect out of a basic multimeter: voltage, current, resistance, continuity, diode check, and even temperature. The only caveat is that the app is apparently not that good.
Reversing BLE devices like this is the exact sort of thing we specialize in at ICE9, so I thought I'd volunteer my services to take a look at the protocol and see how complex it is. For an overview of the process, see my talk Bluetooth Hacking: Tools and Techniques from Hardwear.io 2019.
My usual approach with a device like this that is mainly operated from an app is to install that app on an Android test device and log the Bluetooth communications. This proved to be extremely effective with Pokit. I began by measuring the voltage of a battery and noting the values on the screen. I then tested other functions, always noting what I did and what values were displayed on the screen. Finally, I transferred the log file to my laptop and opened it in Wireshark.
Immediately it became evident that this device uses a very simple command-response protocol. No pairing or encryption are used. On boot, the app subscribes to notifications on a number of characteristics. It then sends a command to put the device into the user-requested mode. Measurements come as notifications from a specific characteristic. From here it was just a matter of comparing the log file to my notes to align which commands referred to which modes and which notifications referred to which measurements.
I observed all commands as write requests on characteristic 0x2f with UUID 53dc9a7a-bc19-4280-b76b-002d0e23b078 and responses were handle value notifications on chracteristic 0x31 with UUID 047d3559-8bee-423a-b229-4417fa603b90. Here is a list of commands I was able to figure out from interacting with the app:
00 ff f4 01 00 00 - disable
01 ff f4 01 00 00 - voltage DC
02 ff f4 01 00 00 - voltage AC
03 ff f4 01 00 00 - current DC
04 ff f4 01 00 00 - current AC
05 ff f4 01 00 00 - resistance
06 00 f4 01 00 00 - diode check
07 00 96 00 00 00 - continuity
08 00 d0 07 00 00 - temperature
I don't know the meaning of the five bytes following the command number. It's possible they may be range related arguments, but there does not appear to be a way to manually specify ranges from the app and I have never observed values other than those above.
The responses for all modes all come in a similar form. Some examples follow, but they clearly are a single byte flag followed by a 32-bit value followed by some more gibberish. The 32-bit value left me stumped for a bit. It was clearly little endian and roughly correlated with the values I had observed, but not exactly. Finally it dawned on me to treat it as a 32-bit float, and there were my measurements, exactly as I recorded from the app.
01 67 b4 cf 3f 01 01 - voltage of 0x3fcfb467: 1.6v
01 b5 18 93 41 07 00 - some continuity (see flag), resistance of 18.4Ω
00 47 35 fe 41 08 00 - temperature measurement of 31.8°C / 89.2°F (it's hot where I did this work!)
That's about all the info you need to communicate with the device. For Mr. Goodspeed's application, leaving a Pokit connected to each vehicle battery and connecting to them once a day (or as often as needed), putting them into voltage DC mode, taking one measurement, and disconnecting solves the problem.
For myself, I think I'll be keeping it as a useful tool in my bag and a handy temperature logger.
I hope this information aids people who are trying to replicate the functionality of the app! As always, if you have any Bluetooth or embedded development or security needs, feel free to reach out to us.
P.S., oscilloscope functions quite a bit differently from the modes listed above, and due to time constraints I did not look into it. Following the process I described above would be a great project for someone looking to get into reverse engineering BLE devices!
P.P.S., I was also able to observe a firmware update from version 1.4 to version 1.6. Extracting the blob from the btsnoop file is quite straightforward. It appears to be encrypted, compressed, or both, and I will not be posting it here.
I'm excited to announce a new tool: Uberducky, a wireless USB Rubber Ducky that can be triggered via BLE. If you have an Ubertooth One I would love you to give it a try. Instructions for building and using it are in the GitHub repo.
This post covers why I decided to build Uberducky and the technicial details on how it's actually built.
Backstory
I recently found myself in a situation where I needed a shell on a laptop. The usual methods wouldn't work: all network-accessible services were disabled on the laptop, and the owner of the laptop was a hard target with good screen locking discipline so a USB Rubber Ducky wouldn't do the trick. I did identify one weak point: the monitor that the laptop was regularly plugged into had USB ports hidden on the back. Ideally I'd be able to plug in something like a USB Rubber Ducky that I could trigger remotely. Distract the target while their screen is unlocked, send the signal, and the backconnect shell drops.
This is not a new idea: the Cactus WHID is an inexpensive tool for doing exactly this. In its default configuration, it broadcasts a WiFi network named "Exploit" that allows you to configure a duckyscript payload and trigger it remotely. Out of the box it's not the stealthiest option, but it's very cool and definitely worth a look.
I've worked extensively with Ubertooth (having written most of the BLE sniffing code) and I thought the platform would be a great fit for something a little stealthier. It has a USB microcontroller on which it is possible to implement the USB HID spec, and it has a generic radio that can be coerced to speak something akin to BLE.
Building Uberducky
The project started out as an empty firmware for Ubertooth because the main repo is too crufty. I did submodule in the main repo, as well as copying the firmware Makefiles into the root of the project. Quite a bit goes into bringing up the platform, but it's entirely hidden behind ubertooth_init(). While the Ubertooth repo wasn't really designed for out-of-tree builds like this, it was surprisingly painless to make it all work. Check out Makefile and common.mk if you're interested.
As a starting point, I made a very simple PoC that would inject a random keystroke at intervals. LPCUSB is the USB stack used by Ubertooth, and it comes with rudimentary HID example code. In no time flat I was injecting random keystrokes every few seconds.
I ran into my first snag at this point: if you insert the example HID keyboard into an Apple computer, it pops open a dialog asking you to press certain keys so it can identify the layout. This obviously won't work for stealthy keystroke injection, so I needed to find a way to prevent this from happening. I knew that this dialog does not open on plugging in Apple branded keyboards, so I theorized that the OS uses the USB vendor and product IDs to determine whether the keyboard has a known layout. Fortunately these values can be set within LPCUSB, and sure enough by changing them to an Apple keyboard (05ac:2227) the dialog never opened.
Just injecting one keystroke wasn't very interesting, so I set to expanding to a complete alphabet. I've implemented HID before over BLE so it wasn't completely new to me. See my BLE Slide Quacker and some older work I did hacking Bluetooth keyboards. General HID is extremely flexible, but keyboards can be implemented very simply. Every time a key is pressed or released, the keyboard sends an 8 byte report via a USB interrupt descriptor. The first byte encodes modifiers (such as control and shift) using a bitfield, and the third byte encodes all other keys. I'm not sure what the other six bytes are used for, so I left them all set to 0 and was never an issue!
In order to learn the HID keycodes as well as perform general debugging of my implementation, I used Linux's debugfs capabilities. Under most kernels from the last few years, this is mounted under /sys/kernel/debug. HID devices show up under /sys/kernel/debug/hid/[hex_string]/, and you can watch the reports come in live by cat'ing the events file. I used a normal keyboard and pressed each key, making note of the value of the report descriptor. I later found a handful of HID keycode tables online and the values matched up.
At this point it was a SMOP (small matter of programming) to convert a given key and set of modifiers into a valid HID report. You can see the code in hid.c.
Injecting Duckyscript
The goal, of course, was to inject a sequence of keystrokes that would cause the target system to perform some malicious action. The people behind the USB Rubber Ducky invented a scripting language called Duckyscript to simplify this process and make it possible to share such scripts.
Duckyscript is designed for humans to read and write, but trying to implement a bulky parser on the microcontroller doesn't make much sense. Instead I wrote a Python parser to compile Duckyscript down into a binary language that's suitable for use on the MCU. The parser outputs a C file with an array that gets compiled into the firmware.
On the microcontroller, I use a state machine driven by the LPC1752's timer peripheral to run the script and actually do the keystroke injection. TIMER0 is configured to tick with a 1 millisecond period, and by using the match registers it is possible to cause an interrupt to occur at any given time. I chose 1 ms because Duckyscript encodes delays in units of milliseconds, and a single keypress takes around 10 ms to complete. The state machine lives in uberducky.c.
The compiled version of Duckyscript uses four opcodes: key, delay, string, and repeat. Key is a single keypress usually combined with a modifier, such as control-v, windows, or any printable ASCII character. Delay pauses the script for a specified number of ms. String is a sequence of characters all typed in a row, such as "echo hello". Repeat will repeat the previous opcode one or more times.
With the Duckyscript injector completed, the Ubertooth hardware was acting effectively as a clone of a real USB Rubber Ducky. As soon as it was inserted to a computer, it would run the script and inject the keystrokes. Now I just needed a way to trigger it wirelessly.
Triggering via BLE
For initial testing, I abused some of the range testing code from Ubertooth to trigger the Duckyscript injection using a second Ubertooth. While I personally have a lot of Uberteeth, most people probably only have one and wouldn't like to spend an extra $120 just for triggering their Uberducky. Ultimately I wanted a mechanism that would be accessible for most people with a single Ubertooth as well as being nearly impossible to accidentally trigger.
The author owns many Uberteeth
BLE advertising packets make the perfect solution. Nearly every laptop and smart phone from the past five years can speak BLE, and while a full link layer is complex just receiving advertising packets is very simple. Set the CC2400 to listen on one of three advertising channels, set the modulation parameters to match those of BLE, set the correct access code, and dewhiten the data received from the air.
I initially planned to lift some of the BLE code from Ubertooth, but like the rest of the firmware it is not written modularly and is overly complex for the task at hand. Instead I implemented it as simply and stupidly as possible using the CC2400's built-in FIFO. When a packet is received, the 32 byte FIFO fills. Once it is full, the radio stops receiving and goes into idle mode. Normally you might parse the packet header to read the length and turn off the radio when the full packet is received, but that would take more lines of code! Instead, Uberducky blindly receives 32 bytes no matter what, even if we're just decoding random radio noise. All the BLE code fits into fewer than 100 lines, check it out in ble.c.
The FIFO trick allows us to receive any advertising packet sent on a given channel, but we still need a trigger. Instead of even attempting to parse the packet, Uberducky searches for a magic 128-bit string of bytes anywhere within the packet. The magic string is defined at compile time and can be changed to suit the user's needs.
That only leaves us with how to send the trigger. Once again, a second Ubertooth is the simplest approach, but normal BLE devices also have a mechanism for sending 128-bit values: by including a list of 128-bit UUIDs in the AD data section of the advertising packet. The only trick is that the UUID needs to be within the first 32 bytes of the packet.
On Linux, it's possible to do this with the following commands:
This very briefly sets the system to advertise with the specified UUID and then disables advertising. The only caution is that if the script is very short it can be triggered multiple times.
It is possible to similar tricks on other OSes, but that is left as an exercise to the reader.
Wishlist
There are a few things I'd love to implement in the medium to long term. Primarily I'd like the ability to update the Duckyscript or trigger UUID without reflashing the entire firmware. It would also be nice to change the magic UUID in the same way.
I envision two possible approaches. The first is to implement a USB serial port. While this reduces stealthiness, it is very straightforward and accessible. A second (and cooler) approach would be to implement a wireless protocol that could be managed using a second Ubertooth. The dream, of course, is to drive it entirely from BLE, but that would entail building an entire link layer to run on Ubertooth. Easier said than done!
Finally, I would love to see ways of triggering it from other platforms. In particular, OS X or Android would be stupendous and I imagine not much code.
If these ideas or any others strike your fancy, I will happily accept pull requests on GitHub.
Parting thoughts
Please give Uberducky a try and let me know if it works for you! I'm a little suspect that my Duckyscript parser and injection are 100% complete and accurate, so bug reports are certainly welcome.
This article covers FUZE Card, a Bluetooth-enabled reprogrammable credit card. The size and shape of a regular credit card, FUZE promises to be "your whole wallet in one card."
After receiving a FUZE Card from @MBHbox (his blog), I decided to take a careful look at it. In the process, I X-rayed the card, fully reverse engineered its Bluetooth protocol, and found a security vulnerability that allows credit card numbers to be stolen via Bluetooth (CVE-2018-9119).
ICE9 reported this vulnerability to BrilliantTS, the maker of FUZE, but they did not respond to repeated follow-ups and did not take action on the basis of our report. As of this writing, CVE-2018-9119 continues to be exploitable on production FUZE Cards in the wild.
Update 2018-04-07: BrilliantTS reached out to ICE9 and informed us that they were already aware of this issue and are planning to release an updated firmware on 2018-04-19. They have also added a security@fuzecard.com email address so issues can be more easily reported in the future. Refer to their security notice for further details. I applaud BrilliantTS for taking steps to remediate this issue once it reached their attention.
The remainder of this article is organized into the following sections:
FUZE is an IoT device the size, shape, and thickness of a normal credit card. You program credit cards into it via Bluetooth (BLE) using a smart phone app. When you go to pay, you use the buttons and e-Paper display to select which card to emulate. The magnetic stripe reprograms itself to impersonate that card, and then FUZE can be swiped like a regular credit card.
To configure FUZE and add or remove credit cards, BrilliantTS publishes an app called eCARD Manager. To add a card, you must swipe it on your phone using an included card reader that plugs into the headphone jack (like a Square dongle). I found this process to be extremely unreliable, taking in excess of 20 swipes to finally accept my card. BrilliantTS claims FUZE can hold up to 30 cards.
FUZE does attempt to provide some level of security. When you set up FUZE for the first time you are prompted to configure a passcode as a sequence of six button presses, although this step can be skipped. With a passcode configured, the device remains locked unless you manually unlock it or your smartphone is nearby. In the locked state, you can't access any of the data on the card or program the magstripe. It also has a higher security mode in which the card will only function when it is connected to a phone via Bluetooth.
Based on promotional images on their site, BrilliantTS plans to release a version with EMV (chip) support. At the time of this writing, only the magnetic stripe version is available. The card also contains NFC circuitry to support contactless payment, but this does not work with the latest firmware.
X-ray hardware "teardown"
I wanted to get an understanding of how the device was built. With a typical IoT device, this usually involves removing the case with a few screws or a spudger and taking a glance at the PCB. At worst you're foiled by an epoxy-encased die.
In the case of FUZE, the device is a solid construction that is a mere 0.03" thick. It may be possible to very carefully remove the plastic packaging, but I only had one and did not want to risk destroying it.
X-ray imaging is great in this scenario. I reached out to John McMaster who has taken X-rays for me in the past. He captured the following image, which I have annotated:
From the image we can see some key features of FUZE's architecture. The main chips on the board are a microcontroller, an e-Paper driver, and a Bluetooth SoC. A number of features are present on the board but are not used, including NFC and EMV (chip card support).
The footprint of the Bluetooth chip is some BGA variant, and the ball land pattern is somewhat unique. With a little sleuthing, Alvaro Prieto[twitter] was able to pinpoint it to the CSR1013. Similar to the nRF51, the CSR101x series is a complete system-on-chip (SoC) with the ability to run custom code. Some of the application code likely lives on the CSR1013.
The microcontroller is an unidentified 68 pin QFP. The bulk of the application likely runs on this, including the code for displaying the screen, button input, and yet-to-be implemented NFC and EMV functionality. The QFP next to the microcontroller is likely a driver for the e-Paper display.
BrilliantTS plans to release a version of FUZE with EMV support, and their site has marketing images of that variant of the card. It is interesting (but not surprising) to note that they use a single board design for both cards. On the magstripe version of the card, the plastic packaging simply covers the smart card contacts for EMV.
A bit of Googling does reveal some press release and marketing photos showing the inside of the card. A review on Seoul Space shows a bare board for a prototype version of the card, and FUZE's main site includes a promotional photo of the hardware stackup.
Bluetooth Reverse Engineering
For a piece of technology like FUZE, the Bluetooth interface is of primary interest for reverse engineering. My toolchest for reverse engineering a Bluetooth device:
Android is absolutely indispensable for performing a blackbox analysis of a Bluetooth device. Out of the box, we can log all Bluetooth traffic from an app to a device. It is also possible to modify app code directly by disassembling and reassembling the Java bytecode, but I didn't have to perform any such app surgery on this assessment.
Burp acts as an HTTP proxy and allows you to inspect API requests made by the Android app to backend servers. Although it wasn't critical for understanding how the FUZE card worked, it did provide some clues.
Android ships a feature called "HCI snoop log" in the "Developer options" settings menu. Enabling this feature saves all Bluetooth activity on the phone to a file, and that includes every message exchanged between the app and device.
Wireshark can read the files produced by Android's HCI snoop log. It's useful for doing basic analysis and filtering. For bulk and semi-automated analysis I like to export the data to text files and munge them using Perl.
Finally, gatttool (and other BlueZ tools) can be used to probe the device directly. It's often useful to take a quick peek with gatttool before even firing up the app. It shines during analysis for experimenting with sending and receiving partially understood protocol messages.
Reversing FUZE
Using gatttool to connect to FUZE not work out as well as hoped. Immediately upon connecting to the card, it sends a "Security Request" over the Security Manager Protocol. This is the card demanding that we pair with it, which is actually uncommon among IoT devices in my experience. BLE's pairing protocol is known to be flawed and most devices implement their own security instead of relying on it. FUZE absolutely refuses to send any data to a device that isn't paired with it and isn't using BLE link layer encryption.
Since gatttool didn't work out, I moved onto my Android-based reverse engineering approach, which looks something like this:
Enable Bluetooth HCI snoop on Android
Do things in the app and with the card
Transfer HCI log to PC using adb
Review in Wireshark
Filter / export as text
Parse with crusty Perl
Smash face against keyboard repeatedly
Loading and filtering the data in Wireshark allowed me to discern that FUZE uses two characteristics for communication: the app writes to the card using write requests on one handle, and receives responses via notifications on another handle. This is extremely common, as it allows developers to treat the BLE channel almost as though it were a TCP socket or serial port.
Reverse engineering by eye in Wireshark
Eyeballing the data in Wireshark left me more hopeful. A great aspect of HCI snoop logging is that the data is captured before it is encrypted by the hardware Bluetooth chip on the phone. The plaintext data included some ASCII strings, and repeated application of step 7 led me to begin to understand some of the protocol format.
Wireshark does not lend itself well to bulk analysis, but it provides a rich set of export utilities to allow for post processing. It is a total hack, but I have had the best luck using "Export Packet Dissections" -> "As Plain Text". Before exporting, expand the "Attribute Protocol" dissection to show the data sent over the air. In the export window, ensure "Details" includes "As displayed". Finally a bit of gross Perl turns this into something I can work with.
At this point, I revisited gatttool. Using bluetoothctl I was able to scan for and pair with the card. It requires the use of Numeric PIN pairing mode in which a 6 digit number is displayed on FUZE's screen that must be entered in the client (a VM running BlueZ) to successfully pair. Once pairing is completed and encryption is established, the device happily responds to GATT messages over the Attribute Protocol.
First up was replaying some messages from the Wireshark dumps. I noticed one message was consistently occurring near the beginning of the conversation:
When sending the first line using gatttool, the second and third lines are reliably sent back. Parsing the data by eye a bit, version numbers become apparent for the hardware, microcontroller firmware, and BLE firmware.
That's interesting, but the very first message being sent is even more interesting:
As soon as this message is sent, the FUZE lock screen turns off and the main menu appears. This is implemented for user convenience, so the card is automatically unlocked when it is near a paired smart phone.
From here it is a matter of staring, thinking, a little experimentation, but mostly staring and thinking. This part should sound familiar to anyone who's ever reverse engineered anything.
Ultimately I was able to reverse engineer the majority of the protocol messages: including the message format and supported operations.
YY - total number of GATT write requests for the current operation
ZZ - current write request number
.. - message body
WW - checksum
I determined the following opcodes through a mix of interpreting messages I captured as well as light fuzzing:
b3 - upload a payment or membership card
b4 - delete a synced card
b5 - possibly change card information (discovered through fuzzing)
b6 - possibly reorder cards (discovered through fuzzing)
b9 - set card owner name (displayed on powered off screen)
ba - unknown function (discovered through fuzzing)
bb - set security level
bc - get total number of cards
bd - unknown function, related in some way to card index (discovered through fuzzing)
be - fetch a payment or membership card
bf - get card owner name
c4 - turn off passcode screen
c5 - set or disable passcode
c6 - factory reset
c7 - enable or disable data blind
d1 - enter firmware update mode
d2 - firmware update data
d3 - related to firmware update
d4 - related to firmware update
ea - fetch battery level
f5 - fetch hardware rev, Bluetooth firmware version, and MCU firmware version
The checksum is calculated by performing an exclusive-or (xor) of all message bytes except the initial 02. Props to Jason Benaim for identifying this highly secure Game Boy style checksum.
I looked briefly at the firmware update process, but I did not dive deeply. Since I only have one card, I knew I wasn't going to attempt any firmware flashing shenanigans. I was able to capture two MCU firmware samples by snooping the HTTP requests using Burp. The two samples are both high entropy, nearly the same size, and quite dissimilar in content. This suggests that they are encrypted. Without further analysis, it's not possible to say if they are signed or validated in any way during the firmware update process.
The BLE firmware update occurs over CSR's in-house OTA update protocol. I am not aware of any security analysis of this protocol. It would be interesting to study and understand, as I'm sure it is used by other devices with this or similar CSR BLE SoCs.
Security vulnerability and exploit PoC
With an understanding of the Bluetooth protocol used by FUZE (see previous section), ICE9 discovered CVE-2018-9119: an attacker with physical access to a FUZE Card can perform the following actions:
Bypass the lock screen
Read credit card numbers, with expiration date and CVV
Tamper with data on the card
At the time of this writing, the vulnerability has not been patched and remains exploitable on all production FUZE Cards.
This vulnerability affects MCU firmware 0.1.73 and BLE firmware 0.7.4, the most recently released versions of both.
Update 2018-04-07: BrilliantTS plans to release an updated firmware on 2018-04-19. See the beginning of this article for full details.
The attacker must have physical access to the card because of how the card uses BLE link layer security. In addition to encrypting data, BLE link layer security acts as an authentication mechanism. If you aren't paired with the FUZE card, it will reject every message you send to it. Although BLE link layer security has well known weaknesses (also discovered by ICE9), it works reasonably well for FUZE's use case.
Where FUZE went right was using the Numeric PIN pairing mode. When you pair with FUZE, the card displays a 6 digit random number on its e-Paper screen. You must enter this on your phone (or Linux attack VM) in order for pairing to succeed. If you attempt to pair with a card that is not in your possession, you will have a one in a million chance of guessing the 6 digit pairing code correctly.
Rigorous testing indicated that it was not possible to bypass the pairing requirement, and also it was not possible to downgrade to a weaker pairing mechanism (Just Works) that does not require entering a passcode.
Some may argue that the physical access requirement makes this vulnerability uninteresting. I would like to emphasize two points: the first is that handing a credit card to strangers is a normal part of making many types of purchases, so it is impossible to ensure that the card is not tampered with out of sight. Secondly, the card presents itself as more secure than a normal credit card with its use of a lock screen. As demonstrated by this weakness, that is a false sense of security.
Proof-of-Concept Exploit
ICE9 developed a proof-of-concept exploit that can be run from a Linux system or VM. The exploit has been tested in Debian Stretch inside VMware using a BLE dongle via USB passthrough. This attack requires BlueZ to be installed.
First, scan for and pair with the device using bluetoothctl:
Launch bluetoothctl: sudo bluetoothctl
Enable the agent (used for pairing): agent on
Scan for devices: scan on
Once a FUZE Card is found, disable scanning: scan off
Pair wih the FUZE Card: pair <bdaddr>
Enter the Numeric PIN displayed on the device
Disconnect from the card: disconnect <bdaddr>
Pairing with the FUZE Card
From here, it is possible to send commands to the card using gatttool:
Launch gatttool: sudo gatttool -I -b <bdaddr>
Connect to the device: connect
Subscribe to notifications: char-write-req 1b 0100
Send commands: char-write-req 18 <command data>
The following commands are of interest:
02c40101300000000000000000000000000000f4
02be01013030310000000000000000000000008f
The first will bypass the lock screen, and the second will read the first credit card number, expiration date, and CVV.
Stealing credit card numbers via Bluetooth
Disclosure to BrilliantTS
ICE9 disclosed the details of this vulnerability to BrilliantTS via email on the following timeline:
2018-01-30 - Initial email to info@fuzecard.com and support@fuzecard.com
2018-01-31 - Follow-up email sent
2018-02-04 - Third follow-up sent
2018-02-05 - Response received from BrilliantTS (FUZE tech support individual)
2018-02-06 - Report sent to FUZE tech support individual
2018-02-09 - Follow-up sent to FUZE tech support individual
2018-02-13 - Final follow-up sent to FUZE tech support individual
2018-03-22 - Disclosure period expired
The report included a complete description of the vulnerability, proof-of-concept exploit code, and noted that ICE9's standard disclosure period is 45 days. BrilliantTS did not respond to any message after the report was delivered, and the 45 day disclosure period has since expired.
As of this writing, BrilliantTS has not released a firmware update for the FUZE Card.
Cracking the Encryption
For completeness, I will note that the Numeric PIN pairing mode (along with other LE Legacy Pairing modes) is vulnerable to a brute force attack if an attacker is able to sniff the pairing conversation. I consider this an unlikely scenario with FUZE. It's likely that the user will pair in a secure location (such as their home), far from attackers. When they go to use the card, the phone and card use the previously established encryption key. During this phase of encryption, there are no known weaknesses.
Nonetheless, as a proof-of-concept, I was able to sniff a pairing conversation and crack it using crackle.
A few words about Coin
Some readers of this article probably remember that FUZE is not the first attempt at a Bluetooth credit card. Way back in the ancient days of 2013, Coin announced a similar product, and delivered it to users by 2015. Fitbit acquired coin in 2016 and killed the product and backend by 2017.
From the X-ray it is clear that Coin is a much simpler design than FUZE.
Like FUZE, Coin is the size and thickness of a regular credit card and communicates via Bluetooth. It has a simpler TN LCD segment-based screen and only a single button. Even still, it also has a passcode feature similar to FUZE. Unlike FUZE, the battery is not rechargeable, and users were expected to return their cards for replacement every two years.
One key way in which FUZE attempts to differentiate itself is by including NFC and EMV support. At the time of this writing, neither of those features is available, so it's a moot point.
I never owned a Coin device, so I can't say how its security compared to FUZE. To the best of my knowledge, nobody ever succeeded in extracting credit card numbers from Coin over Bluetooth. However, since the product is completely dead, it's again a moot point.
Conclusion
Some IoT ideas are unusually sticky. No matter how bad they sound, someone goes out and makes them. A Bluetooth credit card meets this definition for me. With Apple Pay, Google Pay, and other contactless payments shaking up the payments industry, I don't see a lot of value in a Bluetooth credit card. Even with those options available, I still see myself carrying around ordinary credit cards for the foreseeable future. At the end of the day, the risks of a Bluetooth card aren't worth the questionable convenience benefit.
If you would like to hear more and you're in the Bay Area, I will be presenting my research on FUZE Card at the Mountain View Reverse Engineering Meetup (in Santa Clara) on Wednesday April 11, 2018 at 8 PM.
ICE9 Consulting is an independent security firm specializing in Bluetooth and IoT. For more information, visit our main site.
Who doesn’t love electronic con badges? They look fly as heck, blink LEDs, and… well… that’s all most of them do. Don’t get me wrong, there have been some neat game badges and even a few useful ones (hat tip to Mike Ossmann for releasing a HackRF as a badge(!)). But those are the exception. Most go straight into the ewaste old badge pile after the con.
That’s why when I set out to create a conference badge, I wanted to make something I’d actually use for something other than bling. Enter the Slide Quacker!
This summer ICE9 Consulting (that’s me!) sponsored Wrong Island Con 2+ε, a roaming conference put on by ducklord richö butts that took place on Catalina Island in Los Angeles, CA. Along with our pal nico, we sunk a bunch of time, effort, and money into creating the best conference badge we could imagine.
The Slide Quacker is a Bluetooth Smart (BLE) slide clicker. You can pair it with your laptop and use it to change slides in a presentation. Neato. It is an open source, open hardware design, so if you like what you see you can even make one yourself.
The firmware is based on Apache Mynewt, a project by Runtime.io that is incubating its way (hopefully) into the Apache Software Foundation. Mynewt provides a full embedded RTOS (real time operating system) as well as a fully open source BLE stack. I did run into a few rough edges at the time. It’s a little underdocumented, and I did find some bugs (it turns out when you report bugs in a Bluetooth stack the default assumption is “crackpot”, reasonably so). That being said, it’s come a tremendous way since then, and they just released milestone 1.0.0. If you’re in the market for a lightweight, featureful RTOS, give it a look.
On top of Mynewt, we implemented a very basic HID over GATT implementation to emulate a HID keyboard. Our super sick keyboard only has two buttons: left and right arrow, although you can of course map any button to any function since the firmware is open.
The hardware was lovingly handcrafted by nico. The design centers around a Nordic nRF51 SoC (System on Chip) with integrated BLE-compatible radio. Nordic does ship source code that you can use in designs, but it’s not an open-source compatible license. Thus our choice to use Mynewt. Other peripherals include an I2C accelerometer for pairing, a USB UART for firmware updating, and a whole bunch of LEDs because no conference badge would be complete without them. It even includes some easter eggs for setting your preferred orientation (though I did morally struggle with whether to include the UPRIGHT option).
This was our first experience building a con badge, and holy moly was it a frosted buttload of work. But it was totally worth it in the end to see the badge ACTUALLY BEING USED by some of the speakers! Plus there were some fun shenanigans to be had at the con, making sure everyone knew that flat ducks ultimately reign supreme.
If you’re interested in the hardware design and the firmware, check out the repo! As always, feel free to leave any questions and comments below.
And before you ask… no I do not plan to make any more of these. But if you come to the next Wrong Island Con (hint: bug richö to run it again) maybe you’ll get your hands on our next creation.
In August Silicon Labs released the BGM111, a Bluetooth Smart (BLE) module that might be powering the next generation of IoT devices in customers' hands and on hackers' workbenches.
I was curious about the module so I grabbed the datasheet. It's behind a registration wall on the Silicon Labs site, but strangely a direct link turns up on the first page of a Google search.
The datasheet is fairly pedestrian. It appears to be running a custom Bluetooth stack on a Cortex-M4, the most powerful CPU core I've seen in a Bluetooth SoC to date. Developers have a few different options for running code. It is possible to use a custom API over a UART and run application code on an external MCU (similar to the BLE112 and Nordic nRF8001). It is also possible to upload code written in BGScript, a custom scripting language, and run it directly on the device (again like the BLE112).
Not much else really caught my eye in the datasheet. JTAG is exposed on the header, so it may be possible to dump the code running onboard and reverse engineer that. However once I reached regulatory section at the end of the datasheet, I noticed this odd statement:
This piqued my interest. What strange chip could be inside? I know of no existing Bluetooth chips on the market with an M4 core. The product web site has a rendered image of the module without the RF cage blocking the chip, but I hadn't heard of Blue Gecko nor seen the logo.
A quick bit of googling indicated that this is a new line of chips produced by Silicon Labs loaded with the EFM32 core. There is plenty of documentation about the CPU core, but no documentation about any wireless SoCs.
Curiosity got the better of me and I picked one up from DigiKey (not cheap at $10/unit). The RF cage came up easily enough after cooking it in an IR oven for a few minutes, though a hot air gun would have also done the trick.
Curiously the label EFR32 turned up very few results in a web search. A little snooping around the Silicon Labs site exposes the story.
In 2013 Silicon Labs acquired Energy Micro, a fabless semiconductor company working on low power wireless chips. At the time Energy Micro was hard at work on their EFR4 Draco line, aimed at the super low power market.
After the acquisition, it appears Silicon Labs renamed the EFR4 to EFR32. They have focused their entire marketing effort on the BGM111 module and have not even released the EFR32 to distributors. The sole reference I have found to the chip in official documentation is in the Blue Gecko Bluetooth Smart Module Wireless Starter Kit User's Guide.
This is an interesting development, the first new Bluetooth silicon to enter the market in quite a while. I'm interested to see where this module ends up, and I'm even more interested in the stack running on the device. If you come across a BGM111 in any end-user products, let me know!
Recently at DEFCON 23 Richö Butts and I gave a talk about hacking electric skateboards. One of the skateboards, the Yuneec E-GO, uses a custom wireless protocol between its handheld remote and the board. We touched on how we reverse engineered the protocol during the talk, but I wanted to go into more depth on our methodology.
In short, this is the story of how we went from HackRF to skateboard jammer on Ubertooth. Read on for the gory details!
Finding the Signal
We theorized that the skateboard and remote used the 2.4 GHz band, which is well supported by HackRF One. Ordinarily one would use GNU Radio and a basic waterfall sink to look at spectrum, but GNU Radio can be a bit cumbersome.
Luckily we had a PortaPack to play with! The PortaPack sits on top of the HackRF and acts as a wideband spectrum analyzer (among other things). We tuned up to 2400 MHz and swept the spectrum in 20 MHz increments looking for our signal.
By holding the remote near the antenna, we could easily see short bursts occuring regularly at four frequencies: 2408 MHz, 2418 MHz, 2423 MHz, and 2463 MHz. Conveniently enough, by tuning the HackRF to 2416 MHz we could see from 2406 MHz to 2426 MHz, allowing us to capture the lower three frequencies at the same time.
Recovering Modulation Parameters
We next turned to GNU Radio and Baudline for doing further signal analysis. Using a very simple flowgraph, we could capture samples of the remote transmitting, save them to disk, and load them up into Baudline. Once we had loaded the capture into baudline, we could zoom in on individual transmissions and inspect them visually.
By looking at an individual transmission we could tell that the device uses a lower frequency to represent a 0 and a higher frequency a 1. This modulation mode is called frequency shift keying, or 2FSK. By measuring with Baudline, we could see that the lower frequency and upper frequency were around 300 kHz apart, giving a frequency offset of 150 kHz. In addition to discovering the modulation mode and frequency offset, we could also see that the transmissions included long sequences of 0's, meaning it was highly unlikely the device used encryption or data whitening.
Turning back to GNU Radio, we set out to create a flowgraph to demodulate 2FSK. This is somewhat complicated business, but thanks to Mike Ossmann's latest SDR tutorial video and an excellent blog post by Don C. Weber we were able to puzzle out some of the finer points of 2FSK demodulation. The workhorse is the Quadrature Demod block, which tracks changes in angle of a complex-valued signal. This somehow translates into changes in frequency, but this is the part where we admit that neither of us had any idea what we were doing with DSP (as evidenced by Richo's BSidesLV talk).
At this point we had turned our complex RF signal into a real-valued signal. I doubt it is the best tool for the job, but Audacity did a fine job dealing with this data. After importing the raw data into Audacity, we finally had something that resembled actual data.
At the beginning of the packet is the preamble. The signal alternates between 0 and 1 so that the receiving radio can lock on and recover the symbol rate. Following that is the first meaningful data, the access code (also called a sync word). This is a fixed-length value, usually 16, 24, or 32 bits long, which the receiving radio can synchronize on to differentiate the signal from noise. Finally the rest of the packet is the payload.
Zooming in on the signal, the first order of business was recovering the data rate. The preamble makes this convenient as it always alternates between 0 and 1. This allowed us to count the number of samples from a peak to a valley, which gave us samples/symbol (symbols being bits, since this was 2FSK). Dividing the samples/second by the samples/symbol gives symbols/second, the actual data rate.
In our case, we measured around 80 samples/symbol. Dividing our sample rate of 20 million samples/second by 80 gave a data rate of 250,000. This suggests a data rate of 250 kbit which is very commonly supported by off-the-shelf 2.4 GHz radios.
The final piece of the puzzle was the access code. To recover this value, we began the tedious process of counting bits. We measured the length (in samples) of each stretch of 1's and 0's using Audacity. By dividing these lengths by our samples/symbol, we could recover the number of bits in each stretch. After recovering around 12 bits of the access code we turned back to GNU Radio.
The Correlate Access Code block takes as input an access code and tags the data stream with a value of 0x02 or 0x03 (the actual data is one byte of 0x00 or 0x01 for each bit). We took the output of this block and dumped it to a file. To analyze this file, once again Don C. Weber has us covered with grc_bit_converter. This tool reads the tagged output, packs the bits into bytes, and dumps the data in ASCII hex. We we treated the first 32 bits of this output as a candidate access code.
Sniffing with Ubertooth
Armed with the frequencies the device transmitted on, modulation mode of 2FSK, frequency offset of 150 Hz, data rate of 250 kbit, and access code, we finally had enough information to use a narrowband transceiver to attempt to receive packets. Ubertooth makes an ideal platform to implement a sniffer, as its CC2400 is more than up to the task.
The details of tuning up the CC2400 are best left to code, but it was fairly straightforward to rig it up to tune to one of the known channels and dump packets over USB. This gave us our first samples of packet data.
Of note is the 80 00 80 00 starting at the 11th byte of the data. By adjusting the speed control on the remote, these values varied linearly according to position of the speed control. It was thus clear at this point that the remote communicated in plaintext to the controller.
Hopping Along
The final order of business was figuring out the hop pattern and hop interval. As indicated in the above capture from the Ubertooth data, each packet was timestamped using Ubertooth's internal 100 ns clock. This gave us a high-resolution time source for measurements. Sitting on a single channel, we could calculate the delta between consecutive packets and plot these. The minimum value observed was 44 ms between packets, with all other values being multiples of 44 ms (accounting for false positives). The fact that we were seeing multiples of 44 ms indicates we were probably missing some packets, which is to be expected.
Last up was the hop pattern. Looking at the three lower channels in Baudline, it is fairly evident that the device hops between at least the visible three channels in order before returning to the initial channel. We measured the delta between the start of one packet and the start of the next packet to be 11 ms. There was a gap between the third visible channel and the initial channel of 22 ms, so it wasn't much of a stretch to deduce the device hopped to the fourth channel and then back to the first channel in that window. Thus the simple hopping pattern was: channel 1 -> channel 2 -> channel 3 -> channel 4 -> back to channel 1, with a delay of 11 ms between each channel.
Finally having figured out the hop interval and hop pattern, we had all the variables needed to completely follow the E-GO remote as it transmitted to the board. Implementing this in Ubertooth was again relatively straightforward, though the code was now somewhat complicated by a state machine.
Jamming
Since the goal of the research was to attack the skateboards, we set out to create a jammer. In order to jam a narrowband communication such as this, it is sufficient to generate random noise during transmission that confuses the receiving device. The CC2400 has a special mode that produces pseudorandom data, so we made use of this.
The jamming code co-opts the connection following code we introduced to sniff connections. When the CC2400 detects the access code, instead of receiving the packet data we turn the radio into transmit mode and configure it to send pseudorandom data for around 2 ms. Although there is a delay of around 200 us to switch the radio into TX mode, enough of the packet data is obscured by noise that the board stops responding to the remote after around half a second.
For robustness, the jammer also includes a timeout. If no access code is detected after 11 ms plus a bit of slop, the Ubertooth begins transmitting anyway before hopping to the next channel and waiting for the access code again. Without this trick, the code would not reliably jam the connection.
Once the connection was jammed, the board immediately stopped driving the wheels and turned back into a regular skateboard. This is normally not an issue, as the rider would likely coast to a stop before anything bad happened. However, if the rider had been going downhill this attack would also disable the brakes, which could have obvious consequences.
Miscellany
One oddity that we noticed is that occasionally the board responds to packets with packets of its own. We haven't decoded the contents of these packets, but it is likely that they contain basic telemetry such as battery level. In the interest of open research, here is a link to a sample capture of the board and remote both transmitting on the same channel back-to-back.
Code for this has been pushed to Ubertooth master which you can grab from GitHub. Instructions for building and flashing firmware can be found in the wiki.
If you have an E-GO skateboard and an Ubertooth, give it a try and let me know how it goes!
As always, this was not possible without the help of many people. We would like to thank Jared Boone from ShareBrained Technology for his incredible patience assisting us with GNU Radio while he was in the midst of pushing out a product. We would also like to thank Don C. Weber for publishing an excellent walkthrough on decoding FSK with GNU Radio as well as Michael Ossmann for his incredibly awesome SDR tutorial video series. Finally, thanks to @safehex for winning the E-GO we used in this research at the BSidesLV charity auction.
At CanSecWest last week I demonstrated a remote Bluetooth stack crash in Bluedroid, Android's Bluetooth stack since Android 4.3. This post briefly describes the bug.
The vulnerability is in Bluedroid's BLE (Bluetooth Smart) packet parsing code. In order to exercise this vulnerability, an attacker must force a user to connect to a malicious BLE device. Upon connection, the malicious device will issue a malformed GATT notification packet that causes the stack to crash.
It may sound a bit far-fetched that an attacker could force a user to connect to a device, but consider the fact that many BLE apps for Android opportunistically connect to any advertising device in order to determine if it is the device associated with that app. The app need only connect for this attack to succeed.
This vulnerability is not exploitable: the crash is caused by a FORTIFY_SOURCE check failure. Additionally, the vulnerability has been fixed since Android 4.4.
Show me the code
The code in question can be found in stack/gatt/gatt_cl.c, in gatt_process_notification (line 614). This is code for parsing notification packets, which are messages that a BLE device can periodically send to a BLE master. On line 626 you see the following code:
value.len is uint16_t. Both p and len are controlled by the attacker, though in this case we're only interested in len. p is the content of the packet sent by the attacker and len is the number of bytes in the packet.
The code expects a packet with a length of at least two bytes. If an attacker sends a malformed single byte packet, the calculation value.len = len - 2 will underflow to 65534. The memcpy will attempt to copy nearly 64k of data from p.
I built an attack platform using a modified version of BlueZ, the Linux Bluetooth stack. BlueZ is configured to act as a BLE device running a GATT server. Whenever a BLE master connects to it, it automatically sends a malformed notification packet that is one byte long.
In the video, I demonstrate the vulnerability using a BLE heart rate monitor app. For the purpose of demonstration, I manually connect the app to the evil BlueZ. The stack crashes when the music stops playing.
The output of adb logcat contains lines similar to the following:
F/libc (19174): FORTIFY_SOURCE: memcpy buffer overflow. Calling abort().
F/libc (19174): Fatal signal 11 (SIGSEGV) at 0xdeadbaad (code=1), thread 19956 (BTU)
Again I note that this attack is not exploitable due to FORTIFY_SOURCE runtime checks. The code is instrumented at compile time where the length of the target buffer is known. At runtime, the code checks to see if the memcpy length is larger than the target buffer length and if so calls abort().
Timeline
This is the timeline following discovery of the bug:
2013-09-30: Vulnerability disclosed to Google
2013-10-07: Fix committed
2013-10-30: Android 4.4 r0.9 tagged
2013-10-31: Android 4.4 released with fix
Google did not issue a fix for this on Android 4.3, the rationale being that all users should upgrade to 4.4.
More Info
If you're interested in learning more about BLE active attacks and BLE fuzzing, check out the video of my CanSecWest talk, Outsmarting Bluetooth Smart.
