Look before you pip

- (3 min read)

For Python programmers, downloading Python packages from PyPI, the Python Package Index, is second nature. Tools like pip and conventions like the requirements.txt file that most Python projects follow provides a consistent way of specifying project dependencies.

However, installing random packages from PyPI is actually very dangerous, a fact that not many people are aware of. There are a few factors that contribute to this.

  1. Python packages can execute arbitrary Python code during the installation process.

  2. PyPI packages are not moderated. Unlike the package managers used in Linux distros, anyone can register an account and upload Python packages without going through a review process. While this is one factor contributing to PyPI's success as a package repository, you will have to trust the maintainer of the package that the package is safe.

As a proof of concept, I have written a setup.py file that connects to a Metasploit listener and downloads a Meterpreter shell during installation. This demonstrates that it is trivial for someone to execute arbitrary code on a machine through the installation of a Python package. You can obtain the code from GitHub.

Run the Metasploit listener.

msf > use exploit/multi/handler
msf exploit(handler) > set payload python/meterpreter/reverse_tcp
msf exploit(handler) > set LHOST

Finally, run the setup.py file.

python setup.py install

You should obtain a Meterpreter shell with the same privileges that you ran the setup.py script with.

While my example involves connecting to a Metasploit listener on localhost, the same attack can be extended to install malware from remote systems or do almost anything a Python script can do.

The problematic thing about this attack is that there are valid reasons for Python packages to execute code during installation. This ranges from things like OS version checks to compiling C code for packages that rely on C extensions. Restricting setuptools to a subset of Python during installation isn't exactly foolproof as demonstrated by the numerous Python sandbox escape techniques. Moderating PyPI isn't a solution either as that will greatly diminish PyPI's attractiveness as a package repository.

Here are two recommendations to limit the potential of such attacks.

  1. NEVER install Python packages as root. This limits the privileges an attacker has if the attack succeeds. virtualenv is incredibly useful for this.

  2. If you are in an organization with larger resources, audit the third-party packages you depend on. Mirror trusted packages on an internal devpi server instead of installing packages directly from PyPI.

While I am limiting the details in this post to Python packages as that is the ecosystem I am most familiar with, I believe that this issue also extends to other languages and ecosystems such as Ruby and the gems ecosystem. While there has been an increased focus over the years on paying attention to good security practices when writing code, many forget about third-party code. This worries me because third-party code represents such a large attack surface open to exploits. As we all know, security is only as strong as the weakest link.