Giter VIP home page Giter VIP logo

nfc-laboratory's Introduction

SDR nfc-laboratory v2.0

A simple NFC signal sniffer and protocol decoder using SDR receiver, capable of demodulate in real-time the comunication with contacless cards up to 424Kpbs.

Description

By using an SDR receiver it is possible to capture, demodulate and decode the NFC signal between the card and the reader.

I do not have as an objective to explain the NFC norms or modulation techniques, there is a multitude of documentation accessible through Google, I will describe as simply as possible the method that i have used to implement this software.

Currently, detection and decoding for NFC-A, NFC-B and NFC-V modulation has been implemented.

Signal processing

The first step is receive the 13.56MHz signal and demodulate to get the baseband ASK stream, for this purpose any SDR device capable of tuning this frequency can be used, i have the fantastic and cheap AirSpy Mini capable of tuning from 24Mhz to 1700Mhz. (https://airspy.com/airspy-mini/)

However, it is not possible to tune 13.56Mhz with this receiver, instead I use the second harmonic at 27.12Mhz or third at 40.68Mhz with good results.

Let's see a capture of the signal received in baseband (after I/Q to magnitude transform) for the REQA command and its response:

REQA

As can be seen, it is a signal modulated in 100% ASK that corresponds to the REQA 26h command of the NFC specifications, the response of the card uses something called load modulation that manifests as a series of pulses on the main signal after the command.

Demodulation

Due to the digital nature of the signal i used a technique called symbol correlation which is equivalent to carrying out the convolution of the signal with the shape of each symbol to be detected. Without going into details, the NFC-A modulation is based on 6 patterns: Y, X and Z for reader commands and E, D, F for card responses (see NFC specifications for complete description).

Demodulation is performed by calculating the correlation for these patterns and detecting when the maximum approximation to each of them occurs. Below is the correlation functions for the two basic symbols S0, S1 used to calculate all the others. Last value is function SD represent the absolute difference between S0 and S1 necessary to detect the timmings.

CORRELATION

The response of the card is much weaker but enough to allow its detection using the same technique for patterns E, D, F, here it is shown in better scale.

CORRELATION

Symbol detection

For the detection of each symbol the value of each correlation is evaluated in the appropriate instants according to the synchronization. The number of samples per symbol is defined as N and must be calculated before starting the process knowing the sampling frequency (fc) and symbol duration.

The correlation process begins with the calculation of the S0 and S1 values that represent the basic symbols subsequently used to discriminate between the NFC patterns X, Y, Z, E, D and F, as shown below.

DEC1

This results in a flow of patterns X, Y, Z, E, D, F that are subsequently interpreted by a state machine in accordance with the specifications of ISO 14443-3 to obtain a byte stream that can be easily processed.

DEC2

Bitrate discrimination

So, we have seen how demodulation is performed, but how does this apply when there are different speeds? Well, since we do not know in advance the transmission speed it is necessary to apply the same process for all possible speeds through a bank of correlators. Really only is necessary to do it for the first symbol of each frame, once the bitrate is known the rest are decoded using that speed.

DEC3

BPSK modulation

ASK modulation is relatively simple and easy to implement, however the specification ISO 14443 defines the use of BPSK for card responses when the speed is 212Kbps or higher.

For BPSK demodulation a reference signal is required to detect the phase changes (carrier recovery), since that is complex i have chosen to implement it by multiplying each symbol by the preceding one, so that it is possible to determine the value of symbols through the changes produced between then.

BPSK1

Below you can see the signal modulated in BPSK for a response frame at 424Kbps, followed by the demodulation y(t) and integration process over a quarter of a symbol r(t).

BPSK2

Finally, by checking if the result is positive or negative, the value of each symbol can be determined. It is somewhat more complex since timing and synchronization must be considered.

Signal quality analysis

This version includes a OpenGL spectrum analyzer and IQ graph to show the quality of the received signal.

Application example

An example of the result can be seen below.

Signal capture with spectrum analysis and IQ diagram.

APP

Capture of the protocol and time measurement.

APP

Protocol detail view.

APP

Inside the "doc" folder you can find a video with an example of how it works.

SDR Receivers tested

I have tried several receivers obtaining the best results with AirSpy Mini, I do not have more devices, but surely it works with others.

  • AirSpy Mini or R2: Better results, tuning the third harmonic 40.68Mhz, with a sampling frequency of 10 Mbps, with these parameters it is possible to capture the communication up to 424 Kbps.

  • RTL SDR: It works by tuning the second harmonic 27.12Mhz, due to the limitation in the maximum sampling frequency of 3Mbps and its 8 bits of precision only allows you to capture the commands.

NOTE: Due to the above, the support for RTL-SDR is not finalized due to its limited application.

Devices

Devices

Upconverters

To avoid the use of harmonics it is possible to use an up-converter and thus tune directly to the carrier frequency of 13.56Mhz, although I have not tried this combination.

Hardware requirements and performance

The demodulator is designed to run in real time, so it requires a recent computer with a lot of processing capacity.

During development, I have opted for a mixed approach where some optimizations are sacrificed in favor of maintaining clarity in the code and facilitating its monitoring and debugging.

For this reason it is possible that certain parts can be improved in performance, but I have done it as a didactic exercise rather than a production application.

The real-time spectrum analyzer requires a graphics card with OpenGL support and geometry shaders, otherwise the "NFC Frequency" view will not be displayed correctly.

Build instructions

This project has two main components and is based on Qt5 and MinGW-W64:

  • /src/nfc-app: Application interface based on Qt Widgets
  • /src/nfc-lib: A core library without dependencies of Qt (for other uses)

And can be build with mingw-g64

Prerequisites:

Manual build without IDE

Using git-bash, download repository:

$ git clone https://github.com/josevcm/nfc-laboratory.git
Cloning into 'nfc-laboratory'...
remote: Enumerating objects: 1629, done.
remote: Counting objects: 100% (1003/1003), done.
remote: Compressing objects: 100% (776/776), done.
remote: Total 1629 (delta 188), reused 990 (delta 179), pack-reused 626
Receiving objects: 100% (1629/1629), 32.09 MiB | 10.60 MiB/s, done.
Resolving deltas: 100% (312/312), done.
Updating files: 100% (975/975), done.

Prepare release makefiles, or change CMAKE_BUILD_TYPE=Debug and -B cmake-build-debug for debug output:

$ cmake.exe -DCMAKE_BUILD_TYPE=Release -G "CodeBlocks - MinGW Makefiles" -S nfc-laboratory -B cmake-build-release
-- The C compiler identification is GNU 8.1.0
-- The CXX compiler identification is GNU 8.1.0
-- Detecting C compiler ABI info
-- Detecting C compiler ABI info - done
-- Check for working C compiler: D:/develop/mingw-w64/x86_64-8.1.0-posix-seh-rt_v6-rev0/mingw64/bin/gcc.exe - skipped
-- Detecting C compile features
-- Detecting C compile features - done
-- Detecting CXX compiler ABI info
-- Detecting CXX compiler ABI info - done
-- Check for working CXX compiler: D:/develop/mingw-w64/x86_64-8.1.0-posix-seh-rt_v6-rev0/mingw64/bin/g++.exe - skipped
-- Detecting CXX compile features
-- Detecting CXX compile features - done
-- USB_LIBRARY: C:/Users/jvcampos/build/nfc-laboratory/dll/usb-1.0.20/x86_64-w64-mingw32/lib/libusb-1.0.dll.a
-- GLEW_LIBRARY: C:/Users/jvcampos/build/nfc-laboratory/dll/glew-2.1.0/x86_64-w64-mingw32/lib/libglew32.dll.a
-- FT_LIBRARY: C:/Users/jvcampos/build/nfc-laboratory/dll/freetype-2.11.0/x86_64-w64-mingw32/lib/libfreetype.dll.a
-- Configuring done
-- Generating done
-- Build files have been written to: C:/Users/jvcampos/build/cmake-build-release

Launch build:

$ cmake.exe --build cmake-build-release --target nfc-lab -- -j 6
Scanning dependencies of target mufft-sse
Scanning dependencies of target mufft-sse3
Scanning dependencies of target rt-lang
Scanning dependencies of target mufft-avx
Scanning dependencies of target airspy
Scanning dependencies of target rtlsdr
[  1%] Building C object src/nfc-lib/lib-ext/mufft/CMakeFiles/mufft-sse.dir/src/main/cpp/x86/kernel.sse.c.obj
[  2%] Building C object src/nfc-lib/lib-ext/mufft/CMakeFiles/mufft-sse3.dir/src/main/cpp/x86/kernel.sse3.c.obj
[  3%] Building C object src/nfc-lib/lib-ext/mufft/CMakeFiles/mufft-avx.dir/src/main/cpp/x86/kernel.avx.c.obj
[  4%] Building CXX object src/nfc-lib/lib-rt/rt-lang/CMakeFiles/rt-lang.dir/src/main/cpp/Executor.cpp.obj
[  4%] Building C object src/nfc-lib/lib-ext/airspy/CMakeFiles/airspy.dir/src/main/cpp/airspy.c.obj
[  5%] Building C object src/nfc-lib/lib-ext/rtlsdr/CMakeFiles/rtlsdr.dir/src/main/cpp/librtlsdr.c.obj
....
[100%] Linking CXX executable nfc-lab.exe
[100%] Built target nfc-lab

Prepare Qt deployment

To run the application correctly it is necessary to deploy the Qt components together with the libraries, fonts and the generated artifact.

mkdir qt-deploy
cp -rf nfc-laboratory/dat/conf/ qt-deploy/
cp -rf nfc-laboratory/dat/fonts/ qt-deploy/
cp nfc-laboratory/dll/glew-2.1.0/x86_64-w64-mingw32/bin/*.dll qt-deploy/
cp nfc-laboratory/dll/usb-1.0.20/x86_64-w64-mingw32/bin/*.dll qt-deploy/
cp nfc-laboratory/dll/freetype-2.11.0/x86_64-w64-mingw32/bin/*.dll qt-deploy/
cp cmake-build-release/src/nfc-app/app-qt/nfc-lab.exe qt-deploy/

Run windeployqt.exe tool to create required folders and copy required Qt DLLs

$ windeployqt.exe --release --compiler-runtime --no-translations --no-system-d3d-compiler --no-angle --no-opengl-sw qt-deploy/nfc-lab.exe
C:\Users\jvcampos\build\qt-deploy\nfc-lab.exe 64 bit, release executable
Adding Qt5Svg for qsvgicon.dll
Direct dependencies: Qt5Core Qt5Gui Qt5PrintSupport Qt5Widgets
All dependencies   : Qt5Core Qt5Gui Qt5PrintSupport Qt5Widgets
To be deployed     : Qt5Core Qt5Gui Qt5PrintSupport Qt5Svg Qt5Widgets
Updating Qt5Core.dll.
Updating Qt5Gui.dll.
Updating Qt5PrintSupport.dll.
Updating Qt5Svg.dll.
Updating Qt5Widgets.dll.
Updating libgcc_s_seh-1.dll.
Updating libstdc++-6.dll.
Updating libwinpthread-1.dll.
Patching Qt5Core.dll...
Creating directory C:/Users/jvcampos/build/qt-deploy/iconengines.
Updating qsvgicon.dll.
Creating directory C:/Users/jvcampos/build/qt-deploy/imageformats.
Updating qgif.dll.
Updating qicns.dll.
Updating qico.dll.
Updating qjpeg.dll.
Updating qsvg.dll.
Updating qtga.dll.
Updating qtiff.dll.
Updating qwbmp.dll.
Updating qwebp.dll.
Creating directory C:/Users/jvcampos/build/qt-deploy/platforms.
Updating qwindows.dll.
Creating directory C:/Users/jvcampos/build/qt-deploy/printsupport.
Updating windowsprintersupport.dll.
Creating directory C:/Users/jvcampos/build/qt-deploy/styles.
Updating qwindowsvistastyle.dll.

Application is ready to use!

If you do not have an SDR receiver, I have included a small capture sample signal in file "wav/capture-424kbps.wav" that serves as an example to test demodulation.

Build from QtCreator

Thanks to bvernoux for this instructions:

Working solution is to use Qt Creator (Tested with latest Qt Creator 5.0.1 with Qt 5.15.2 + mingw81_64 ) then import the nfc-laboratory/CMakeLists.txt project and built it with MinGW 64-bit (Tested with success with Qt 5.15.2 + mingw81_64 on Windows10Pro 21H1) Example of batch used(requires msys2/linux cp/rm commands) to do the deployment (after build of the release version with Qt Creator)

set qtpath=C:\Qt\5.15.2\mingw81_64\bin\
set PATH=%qtpath%;%PATH%
set execpath="%qtpath%\windeployqt.exe"
set nflab_git_path=D:\_proj\__Lab_Tools\NFC\nfc-laboratory
set build_path=%nflab_git_path%\..\build-nfc-laboratory-Desktop_Qt_5_15_2_MinGW_64_bit-Release\src\nfc-app\app-qt

cp %build_path%/nfc-lab.exe ./
%execpath% --no-translations --no-system-d3d-compiler --no-angle --no-opengl-sw nfc-lab.exe

cp %qtpath%\libgcc_s_seh-1.dll ./
cp %qtpath%\libwinpthread-1.dll ./
cp %qtpath%\libstdc++-6.dll ./

cp -a %nflab_git_path%\dat\conf ./
cp -a %nflab_git_path%\dat\fonts ./

cp %nflab_git_path%\dll\glew-2.1.0\x86_64-w64-mingw32\bin\libglew32.dll ./
cp %nflab_git_path%\dll\freetype-2.11.0\x86_64-w64-mingw32\bin\libfreetype.dll ./
cp %nflab_git_path%\dll\usb-1.0.20\x86_64-w64-mingw32\bin\libusb-1.0.dll ./

Build from Jetbrains CLion

This is my favorite IDE and that I use for all projects.

Install all prerequisites, and register MinGW toolchain in File->Settings->Build, Execution, Deployment->Toolchains

Build Settings

Next download project from GITHUB and create new CMake project from source, then build release and debug verions.

Prepare the Qt deployment environment by executing the script build-runenv.ps1, now is ready to launch!

Source code and licensing

If you think it is an interesting job or you plan to use it for something please send me an email and let me know, I will be happy to exchange experiences, thank you very much.

This project is published under the terms of the MIT license, however there are parts of it subject to other types of licenses, please check if you are interested in this work.

Next steps, work in Android?

I have not spent much time, but i been able to migrate this SW to Android (very simplified) by connecting an SDR receiver and sniff NFC frames in real-time, interesting thing to investigate, maybe start a new project with this...

Releases

Precompiled installer for x86 64 bit can be found in repository, check this MD5 first! cf088515b4321b9c10d9d5d37bfebbc8

nfc-laboratory's People

Stargazers

 avatar  avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.