Manul is a coverage-guided parallel fuzzer for open-source and blackbox binaries on Windows, Linux and MacOS (beta) written in pure Python.
pip3 install psutil
git clone https://github.com/mxmssh/manul
cd manul
mkdir in
mkdir out
echo "AAAAAA" > in
python3 manul.py -i in -o out -n 4 "linux/test_afl @@"
sudo apt-get install gcc make git wget
git clone https://gitlab.com/akihe/radamsa.git && cd radamsa && make && sudo make install
There is no need to install radamsa on Windows, Manul is distributed with radamsa native library on this platform.
| CVE IDs | Product | Finder |
|---|---|---|
| CVE-2019-6931 CVE-2019-7310 CVE-2019-9959 | Poppler | Maksim Shudrak |
| CVE-2018-17019 CVE-2018-16807 CVE-2019-12175 | Bro/Zeek | Maksim Shudrak |
If you managed to find a new bug using Manul please contact me and I will add you in the list.
- psutil
- Python 2.7+ or Python 3.4+ (prefered)
Currently, Manul supports two types of instrumentation: afl-gcc and DBI.
Instrument your target with afl-gcc and Address Sanitizier (recommended for better results). For example:
CC=afl-gcc CXX=afl-g++ CFLAGS=-fsanitize=address CXXFLAGS=-fsanitize=address cmake <path_to_your_target>
make -j 8
See this instruction for more details.
You don't need to instrument your target in this mode but you need to download the latest version of DynamoRIO framework for Windows or Linux. The working version of Intel PIN is provided with Manul. You can find it in the dbi_clients_src/pin/pin-3.6-97554-g31f0a167d-gcc-linux folder.
Manul is distributed with x86/x64 pre-compiled clients for Linux and Windows. You can find them in the following folders:
linux/dbi_32|dbi_64/afl-pin.so (Intel PIN client)
linux/dbi_32|dbi_64/libbinafl.so (DynamoRIO client)
win/dbi_32|dbi_64/binafl.dll
Unfortunately, DynamoRIO is not officially supported on OS X. Intel PIN client on OS X is not yet ported.
You can find DynamoRIO release packages at DynamoRIO download page. Choose one of the archive available such as:
DynamoRIO-i386-Linux-7.91.18103-0.tar.gz - 32bit Linux.
DynamoRIO-x86_64-Linux-7.91.18103-0.tar.gz - 64bit Linux.
DynamoRIO-Windows-7.91.18103-0.zip - 32/64bit Windows.
You have to uncomment the following lines in the manul.config file and provide correct path to DynamoRIO launcher and client.
# Choose DBI framework to provide coverage back to Manul ("dynamorio" or "pin"). Example dbi = dynamorio
dbi = dynamorio
# If dbi parameter is not None the path to dbi engine launcher and dbi client should be specified.
dbi_root = /home/max/DynamoRIO/bin64/drrun
dbi_client_root = /home/max/manul/linux/dbi_64/libbinafl.so
dbi_client_libs = None
IMPORTANT NOTE: you should use 32bit launcher and 32bit client to fuzz 32bit binaries and 64bit launcher and 64bit client for 64bit binaries!
TBD
The most frequently used options can be provided via the command line. The more options are supported using configuration file (manul.config).
Example: python3 manul.py -i corpus -o out_dir -n 40 "target @@"
positional arguments:
target_binary The target binary and options to be executed (don't forget to include quotes e.g. "target e @@").
optional arguments:
-h, --help show this help message and exit
-n NFUZZERS Number of parallel fuzzers
-s Run dumb fuzzing (no code instrumentation)
-c CONFIG Path to config file with additional options (see Configuration File Options section below)
-r Restore previous session
Required parameters:
-i INPUT Path to directory with initial corpus
-o OUTPUT Path to output directory
Manul is distributed with default manul.config file where user can find all supported options and usage examples. Options should be specified in the following format Format: <option_name> = <value>. Symbol # can be used to ignore a line.
dict = /home/max/dictionaries/test.dict. AFL mutation strategy allows user to specify a list of custom tokens that can be inserted at random places in the fuzzed file. Manul supports this functionality via this option (absolute paths prefered).
mutator_weights=afl:7,radamsa:2,my_mutator:1. Mutator weights allow user to tell Manul how many mutations per 10 executions should be performed by certain fuzzer. In this example, AFL mutator will be executed in 7/10 mutations, Radamsa 2/10 and some custom my_mutator will get 1/10. If you want to disable certain mutator, the weight should be assigned to 0 (e.g. mutator_weights=afl:0,radamsa:1,my_mutator:9).
determenistic_seed = False|True. By providing True, Radamsa mutations will become determentistic thereby each run of Manul will lead to same outputs.
print_per_thread = False|True. By enabling this option, Manul will print summary for each thread being executed instead of total summary.
disable_volatile_bytes = False|True By enabling this option, Manul will not blacklist volatile paths.
dbi = dynamorio|pin. This option tells Manul which DBI framework will be used to instrument the target.
dbi_root = <path>. This options tells Manul where to find DBI framework main launcher.
dbi_client_root = <path>. This options tells Manul where to find DBI client to perform instrumentation.
dbi_client_libs = name_#1,name_#2|None. This option can be used to specify list of libraries that need to be instrumented along with the main target (e.g. you have executable that loads the target library where you want to find bugs).
timeout = 10. Time to wait before kill the target and send the next test case.
The options net_config_master and net_config_slave are used to distrubute manul instances over network. You have to perform the following 3 steps to run distributed fuzzing.
- Create a file with a list of hosts in the following format:
IP:portwhere your slaves will be executed. - Start all Manul slave instances on remote machines (with all required options and path to target binary) and enable the following option:
net_config_slave = 0.0.0.0:1337. Manul will launch the instance and will wait for incoming connection from master instance on port 1337. - Start the master instance and provide the file with a list of slave instances created on Step 1 using
net_config_master = file_name.
debug = False|True - print debug info.
logging_enable = False|True - save debug info in the log.
manul_logo = False|True - print Manul logo at the beginning.
no_stats = False|True - save statistics.
sync_freq = 10000. Allows user to change coverage bitmap syncronization frequency. This options tells Manul how often it should syncronize coverage between parallel fuzzing instances. Lower value decreases performance but increases coordination between instances.
#custom_path = test_path - this option allows to save the test case in the custom folder (if target wants to load it from some predefined place).
cmd_fuzzing = True|False. If this option is enabled, Manul will provide the input in the target via command line instead of saving in the file.
user_signals = 6,2,1|None. User can tell Manul which signals from the target should be ignored (not considered as crash).
target_ip_port = 127.0.0.1:7715|None - used to spefiy target IP and PORT.
target_protocol = tcp|tcp - used to spefify the protocol to send input in the target over network.
net_init_wait = 1. This option can be used to wait while the target is launching before actually start sending test cases.
net_sleep_between_cases = 0.0. This option can be used to define a delay between test cases being send in the target.
Currently, network fuzzing is an experimental feature (see issues for more details).
Custom mutator can be added in the following three steps: Step 1. Create a python (.py) file and give it some name (e.g. example_mutator.py)
Step 2. Create two functions def init(fuzzer_id) and def mutate(data). See example_mutator for more details. Manul will call init function during fuzzing initalization and mutate for each file being provided into the target.
Step 3. Enable mutator by specifying its name using mutator_weights in manul.config. E.g. mutator_weights=afl:2,radamsa:0,example_mutator:8.
NOTE: AFL and Radamsa mutators should always be specified. If you want to disable AFL and/or Radamsa just assign 0 weights to them.
TBD
