Overview

Skunk is a framework that enables to test linux kernel functions in user space, using python. Current kernel testing solutions either require to write kernel code (for Unit Test solutions such as Kunit and KTF) or perform end to end tests (such as Kselftest, Linux Test Project, Kernel CI, Syzbot).

Since writing kernel code takes time and experience, Skunk facilitates writing unit test (i.e. testing kernel functions) or integration tests (e.g. testing a kernel subsystem or driver) by writing python code in user mode.

A simple example of Skunk's usage is testing the kernel implementation of strstr. Here's a simple test in python:

sk = Skunk()
ret = sk.call_function_two_arg(
                                "strstr",                                               # Function name
                                2,                                                      # Number of arguments
                                skunk_pb2.FunctionCall.string,                          # Type of return value
                                "whatisthemeaningoflife", skunk_pb2.Argument.string,    # First argument value and type
                                "ning", skunk_pb2.Argument.string)                      # Second argument value and type

assert ret.string=="ningoflife", "error"

Currently, you can test only functions with limited dependencies. In the next milestone of Skunk, we intend to enable to mock kernel functions so that you can extend your test coverage and flexibility.

Architecture

Basically, the skunk.py library packs the function call in a protobuf message and sends it to skunk.ko via an ioctl.

skunk.ko then unpacks the message and performs the call within the kernel.

The return value is returned to user space via another protobuf message.

Setup

Prerequisites

Compiled Linux Kernel source code of your target machine.

Install the following packages:

''' sudo apt install -y linux-source python3 python3-pip autoconf libtool pkg-config '''

See the before_install section in .travis.yml for an example of a specific kernel version.

Or, See a tutorial explaining how to compile your kernel version sources.

Install

Simply run repo.sh -i. This might take some time.

Run

Simply run repo.sh -r, and then run your python code. For example you can run examples/examples1.py

Contributing

There is a list of issues that we need help with. Waiting for your PRs! If you want to make a big change, it might be best to consult first on the issue conversation.