关于GDBFuzz
GDBFuzz是一款功能强大的模糊测试工具，在该工具的帮助下，广大研究人员可以使用硬件断点对嵌入式系统进行模糊测试。
GDBFuzz的理念是利用微控制器的硬件断点作为覆盖引导模糊测试的反馈。因此，GDB被用作通用接口以实现广泛的适用性。对于固件的二进制分析，GDBFuzz使用了Ghidra实现。
工具要求
Java
Python 3
工具安装
注意，GDBFuzz已在 Ubuntu 20.04 LTS 和 Raspberry Pie OS 32 位上进行了测试。
首先，我们需要在本地设备上安装并配置好最新版本的Java和Python 3环境，然后创建一个新的虚拟环境并安装所有的依赖组件：
virtualenv .venvsource .venv/bin/activatemakechmod a+x ./src/GDBFuzz/main.py
工具使用
本地运行样例
GDBFuzz会使用以下键来从配置文件中读取设置：
[SUT]# Path to the binary file of the SUT.# This can, for example, be an .elf file or a .bin file.binary_file_path = <path># Address of the root node of the CFG.# Breakpoints are placed at nodes of this CFG.# e.g. 'LLVMFuzzerTestOneInput' or 'main'entrypoint = <entrypoint># Number of inputs that must be executed without a breakpoint hit until# breakpoints are rotated.until_rotate_breakpoints = <number># Maximum number of breakpoints that can be placed at any given time.max_breakpoints = <number># Blacklist functions that shall be ignored.# ignore_functions is a space separated list of function names e.g. 'malloc free'.ignore_functions = <space separated list># One of {Hardware, QEMU, SUTRunsOnHost}# Hardware: An external component starts a gdb server and GDBFuzz can connect to this gdb server.# QEMU: GDBFuzz starts QEMU. QEMU emulates binary_file_path and starts gdbserver.# SUTRunsOnHost: GDBFuzz start the target program within GDB.target_mode = <mode># Set this to False if you want to start ghidra, analyze the SUT,# and start the ghidra bridge server manually.start_ghidra = True# Space separated list of addresses where software breakpoints (for error# handling code) are set. Execution of those is considered a crash.# Example: software_breakpoint_addresses = 0x123 0x432software_breakpoint_addresses =# Whether all triggered software breakpoints are considered as crashconsider_sw_breakpoint_as_error = False[SUTConnection]# The class 'SUT_connection_class' in file 'SUT_connection_path' implements# how inputs are sent to the SUT.# Inputs can, for example, be sent over Wi-Fi, Serial, Bluetooth, ...# This class must inherit from ./connections/SUTConnection.py.# See ./connections/SUTConnection.py for more information.SUT_connection_file = FIFOConnection.py[GDB]path_to_gdb = gdb-multiarch#Written in address:portgdb_server_address = localhost:4242[Fuzzer]# In Bytesmaximum_input_length = 100000# In secondssingle_run_timeout = 20# In secondstotal_runtime = 3600# Optional# Path to a directory where each file contains one seed. If you don't want to# use seeds, leave the value empty.seeds_directory =[BreakpointStrategy]# Strategies to choose basic blocks are located in# 'src/GDBFuzz/breakpoint_strategies/'# For the paper we use the following strategies# 'RandomBasicBlockStrategy.py' - Randomly choosing unreached basic blocks# 'RandomBasicBlockNoDomStrategy.py' - Like previous, but doesn't use dominance relations to derive transitively reached nodes.# 'RandomBasicBlockNoCorpusStrategy.py' - Like first, but prevents growing the input corpus and therefore behaves like blackbox fuzzing with coverage measurement.# 'BlackboxStrategy.py', - Doesn't set any breakpointsbreakpoint_strategy_file = RandomBasicBlockStrategy.py[Dependencies]path_to_qemu = dependencies/qemu/build/x86_64-linux-user/qemu-x86_64path_to_ghidra = dependencies/ghidra[LogsAndVisualizations]# One of {DEBUG, INFO, WARNING, ERROR, CRITICAL}loglevel = INFO# Path to a directory where output files (e.g. graphs, logfiles) are stored.output_directory = ./output# If set to True, an MQTT client sends UI elements (e.g. graphs)enable_UI = False
项目的./example_programs/目录中提供了一个配置文件样例，benchmark/benchSUTs/GDBFuzz_wrapper/common/路径下也有一个可以进行模糊测试的样例程序。
下列命令可以直接对目标程序执行模糊测试：
chmod a+x ./example_programs/json-2017-02-12./src/GDBFuzz/main.py --config ./example_programs/fuzz_json.cfg
在 Docker 容器中安装并运行
make dockerimage
如需在Docker中执行上述测试，需要先将example_programs和output文件夹映射为卷，然后按如下方式启动GDBFuzz：
chmod a+x ./example_programs/json-2017-02-12docker run -it --env CONFIG_FILE=/example_programs/fuzz_json_docker_qemu.cfg -v $(pwd)/example_programs:/example_programs -v $(pwd)/output:/output gdbfuzz:1.0
模糊测试输出
根据配置文件中指定的output_directory内容，工具将会生成一个包含下列结构的“trial-0”文件夹：
.├── corpus ├── crashes ├── cfg ├── fuzzer_stats ├── plot_data ├── reverse_cfg
可视化实现
GDBFuzz 有一个可选功能，可以绘制覆盖节点的控制流图。默认情况下，此功能处于禁用状态。我们可以在用户配置中将“enable_UI”设置为“True”来启用它。
执行下列命令安装graphviz：
sudo apt-get install graphviz
然后安装最新版本的Node.js：
$ node --versionv16.9.1$ npm --version7.21.1
安装 Web UI 依赖项：
cd ./src/webuinpm install
安装并更新mosquitto MQTT代理，并使用以下内容替换/etc/mosquitto/conf.d/mosquitto.conf文件中的内容：
listener 1883allow_anonymous truelistener 9001protocol websockets
重新启动 mosquitto 代理：
sudo service mosquitto restart
检查 mosquitto 代理是否正在运行：
sudo service mosquitto status
启动网页用户界面：
cd ./src/webuinpm start
打开Web浏览器并访问“http://localhost:3000/”即可。
许可证协议
本项目的开发与发布遵循AGPL-3.0开源许可协议。
项目地址
GDBFuzz：【GitHub传送门】
参考资料
Fuzzing Embedded Systems Using Debug Interfaces - CISPA
Installieren von Node.js unter Ubuntu 20.04 | DigitalOcean
How to Install The Mosquitto MQTT Broker on Linux