/blesser

BLE over-the-air fuzzer

Primary LanguageC

Blesser: A Stateful Fuzzer Tool

Blesser is a stateful fuzzer tool designed to help developers and security researchers find vulnerabilities in software applications. It is based on a state machine model that allows for intelligent fuzzing of input data, making it an effective and efficient tool for finding bugs.

Project Overview

Installation and Usage

Requirements

Software Requirements

  • Python 3.x
  • nRF Connect for Desktop v4.0.1
  • nRF Command Line Tools v1.2.4
  • nRF Connect SDK v2.3.0

Hardware Requirements

  • nRF52840 DK
  • nRF52840 Dongle(for testing)

Installation

To prepare Blesser, follow these steps:

  1. Clone the Blesser repository from GitHub:
git clone https://github.com/Just1ceP4rtn3r/blesser.git
  1. Navigate to the blesser directory:
cd blesser
  1. lnstall the nRF Connect SDK,including the following steps(See details at nRF Connect SDK/Get started):

  • Install nRF Command Line Tools

  • Install nRF Connect for Desktop

  • Install nRF Connect SDK through the TooIchain Manager in nRF Connect for Desktop

  • Install Visual Studio Code

  • Install nRF Connect Extension Pack(Download from inside VS Code or using Toolchain Manager in nRF Connect for Desktop)

  1. Use the nRF Connect for VS Code plug-in to create an application.

Move all the files in the blesser/BlessBackend/Backend folder to the newly created application folder, overwriting the original files.

mv -f blesser/BlessBackend/Backend/* {your_application_folder}/

Move the files in the blesser/BlessBackend/SDK to the zephyr directory of the dependent nRF Connect SDK and overwrite the original files.

mv -f blesser/BlessBackend/SDK/* {your_nRF_Connect_SDK_folder}/zephyr/
  1. Connect the nRF52840 DK and flash the modified application to the development board. At this point, the lower-level customized message communication module starts to run.

Usage

We also need to run upper-layer fuzzing module of Blesser.To use the module, follow these steps:

  1. Navigate to the src directory:
cd src
  1. Install the required Python packages:
pip install -r requirements.txt
  1. Run the core.py script:
python core.py
  • Upper-layer fuzzing module will start running and will automatically generate input data based on the current state of the state machine.
  • To stop the module, press CTRL+C.

TODO

Challenges

  • EQ如果找到了反例，是否需要优化（例如证明反例的新状态是否与假设模型中的某个状态一致）
  • 有没有意义做Peripheral对Central进行Fuzzing测试
  • Out Of Bound (OOB)这种连接如何自动化
  • 优化方式：如果前面的状态中协商了等级A的能力，后续变异增加使用其他等级能力的概率
  • random的值，是否需要进行重放的变异