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

2. Navigate to the blesser directory:

cd blesser

3. 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)

4. 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/

5. 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

2. Install the required Python packages:

pip install -r requirements.txt

3. 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