FISSURE - Frequency Independent SDR-based Signal Understanding and Reverse Engineering

Frequency Independent SDR-based Signal Understanding and Reverse Engineering

FISSURE is an open-source RF and reverse engineering framework designed for all skill levels with hooks for signal detection and classification, protocol discovery, attack execution, IQ manipulation, vulnerability analysis, automation, and AI/ML. The framework was built to promote the rapid integration of software modules, radios, protocols, signal data, scripts, flow graphs, reference material, and third-party tools. FISSURE is a workflow enabler that keeps software in one location and allows teams to effortlessly get up to speed while sharing the same proven baseline configuration for specific Linux distributions.

The framework and tools included with FISSURE are designed to detect the presence of RF energy, understand the characteristics of a signal, collect and analyze samples, develop transmit and/or injection techniques, and craft custom payloads or messages. FISSURE contains a growing library of protocol and signal information to assist in identification, packet crafting, and fuzzing. Online archive capabilities exist to download signal files and build playlists to simulate traffic and test systems.

The friendly Python codebase and user interface allows beginners to quickly learn about popular tools and techniques involving RF and reverse engineering. Educators in cybersecurity and engineering can take advantage of the built-in material or utilize the framework to demonstrate their own real-world applications. Developers and researchers can use FISSURE for their daily tasks or to expose their cutting-edge solutions to a wider audience. As awareness and usage of FISSURE grows in the community, so will the extent of its capabilities and the breadth of the technology it encompasses.

Getting Started

Supported

There are two branches within FISSURE to make file navigation easier and reduce code redundancy. The Python2_maint-3.7 branch contains a codebase built around Python2, PyQt4, and GNU Radio 3.7; while the Python3_maint-3.8 branch is built around Python3, PyQt5, and GNU Radio 3.8.

In-Progress (beta)

Note: Certain software tools do not work for every OS. Refer to Software And Conflicts

Installation

git clone https://github.com/ainfosec/fissure.git
cd FISSURE
git checkout <Python2_maint-3.7> or <Python3_maint-3.8>
./install

This will automatically install PyQt software dependencies required to launch the installation GUIs if they are not found.

Next, select the option that best matches your operating system (should be detected automatically if your OS matches an option).

Python2_maint-3.7	Python3_maint-3.8

It is recommended to install FISSURE on a clean operating system to avoid existing conflicts. Select all the recommended checkboxes (Default button) to avoid errors while operating the various tools within FISSURE. There will be multiple prompts throughout the installation, mostly asking for elevated permissions and user names. If an item contains a "Verify" section at the end, the installer will run the command that follows and highlight the checkbox item green or red depending on if any errors are produced by the command. Checked items without a "Verify" section will remain black following the installation.

Usage

fissure

Refer to the FISSURE Help menu for more details on usage.

Details

Components

• Dashboard
• Central Hub (HIPRFISR)
• Target Signal Identification (TSI)
• Protocol Discovery (PD)
• Flow Graph & Script Executor (FGE)

Capabilities

Signal Detector

IQ Manipulation

Pattern Recognition

Attacks

Fuzzing

Signal Playlists

Image Gallery

Packet Crafting

Scapy Integration

CRC Calculator

Logging

Lessons

FISSURE comes with several helpful guides to become familiar with different technologies and techniques. Many include steps for using various tools that are integrated into FISSURE.

• Lesson1: OpenBTS
• Lesson2: Lua Dissectors
• Lesson3: Sound eXchange
• Lesson4: ESP Boards
• Lesson5: Radiosonde Tracking
• Lesson6: RFID
• Lesson7: Data Types
• Lesson8: Custom GNU Radio Blocks
• Lesson9: TPMS
• Lesson10: Ham Radio Exams
• Lesson11: Wi-Fi Tools

Roadmap

• Add more hardware types, RF protocols, signal parameters, analysis tools
• Support more operating systems
• Create a signal conditioner, feature extractor, and signal classifier with selectable AI/ML techniques
• Develop class material around FISSURE (RF Attacks, Wi-Fi, GNU Radio, PyQt, etc.)
• Transition the main FISSURE components to a generic sensor node deployment scheme

Contributing

Suggestions for improving FISSURE are strongly encouraged. Leave a comment in the Discussions page if you have any thoughts regarding the following:

• New feature suggestions and design changes
• Software tools with installation steps
• New lessons or additional material for existing lessons
• RF protocols of interest
• More hardware and SDR types for integration
• IQ analysis scripts in Python
• Installation corrections and improvements

Contributions to improve FISSURE are crucial to expediting its development. Any contributions you make are greatly appreciated. If you wish to contribute through code development, please fork the repo and create a pull request:

1. Fork the project
2. Create your feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a pull request

Creating Issues to bring attention to bugs is also welcomed.

Collaborating

Contact Assured Information Security, Inc. (AIS) Business Development to propose and formalize any FISSURE collaboration opportunities–whether that is through dedicating time towards integrating your software, having the talented people at AIS develop solutions for your technical challenges, or integrating FISSURE into other platforms/applications.

License

GPL-3.0

For license details, see LICENSE file.

Contact

Follow on Twitter: @FissureRF, @AinfoSec

Chris Poore - Assured Information Security, Inc. - poorec@ainfosec.com

Business Development - Assured Information Security, Inc. - bd@ainfosec.com

Acknowledgments

Special thanks to Dr. Samuel Mantravadi and Joseph Reith for their contributions to this project.

dBmonster - Track WiFi Devices With Their Recieved Signal Strength

With dBmonster you are able to scan for nearby WiFi devices and track them trough the signal strength (dBm) of their sent packets (sniffed with TShark). These dBm values will be plotted to a graph with matplotlib. It can help you to identify the exact location of nearby WiFi devices (use a directional WiFi antenna for the best results) or to find out how your self made antenna works the best (antenna radiation patterns).

Features on Linux and MacOS

Installation

git clone https://github.com/90N45-d3v/dBmonster
cd dBmonster

# Install required tools (On MacOS without sudo)
sudo python requirements.py

# Start dBmonster
sudo python dBmonster.py

Has been successfully tested on...

* should work on any MacOS or Debian based system and with every WiFi card that supports monitor-mode

Troubleshooting for MacOS

Normally, you can only enable monitor-mode on the internal wifi card from MacOS with the airport utility from Apple. Somehow, wireshark (or here TShark) can enable it too on MacOS. Cool, but because of the MacOS system and Wireshark’s workaround, there are many issues running dBmonster on MacOS. After some time, it could freeze and/or you have to stop dBmonster/Tshark manually from the CLI with the ps command. If you want to run it anyway, here are some helpful tips:

Kill dBmonster, if you can't stop it over the GUI

Look if there are any processes, named dBmonster, tshark or python:

sudo ps -U root

Now kill them with the following command:

sudo kill <PID OF PROCESS>

Stop monitor-mode, if it's enabled after running dBmonster

sudo airport <WiFi INTERFACE NAME> sniff

Press control + c after a few seconds

* Please contact me on twitter, if you have anymore problems

Working on...

• Capture signal strength data for offline graphs
• Generate graphs from normal wireshark.pcapng file
• Generate multiple graphs in one coordinate system

Additional information

• If the tracked WiFi device is out of range or doesn't send any packets, the graph stops plotting till there is new data. So don't panic ;)
• dBmonster wasn't tested on all systems... If there are any errors or something is going wrong, contact me.
• If you used dBmonster on a non-listed Platform or WiFi Adapter, please open an issue (with Platform and WiFi Adapter information) and I will add your specification to the README.md