Python Taint

Static analysis of Python web applications based on theoretical foundations (Control flow graphs, fixed point, dataflow analysis)

Features

• Detect Command injection
• Detect SQL injection
• Detect XSS
• Detect directory traversal
• Get a control flow graph
• Get a def-use and/or a use-def chain
• Search GitHub and analyse hits with PyT
• Scan intraprocedural or interprocedural
• A lot of customisation possible

Example usage and output:

Install

1. git clone https://github.com/python-security/pyt.git
2. python setup.py install
3. pyt -h

Usage from Source

Using it like a user python -m pyt -f example/vulnerable_code/XSS_call.py save -du

Running the tests python -m tests

Running an individual test file python -m unittest tests.import_test

Running an individual test python -m unittest tests.import_test.ImportTest.test_import

Contributions

Join our slack group: https://pyt-dev.slack.com/ - ask for invite: [email protected]

Guidelines

Virtual env setup guide

Create a directory to hold the virtual env and project

mkdir ~/a_folder

cd ~/a_folder

Clone the project into the directory

git clone https://github.com/python-security/pyt.git

Create the virtual environment

python3 -m venv ~/a_folder/

Check that you have the right versions

python --version sample output Python 3.6.0

pip --version sample output pip 9.0.1 from /Users/kevinhock/a_folder/lib/python3.6/site-packages (python 3.6)

Change to project directory

cd pyt

Install dependencies

pip install -r requirements.txt

pip list sample output

gitdb (0.6.4)
GitPython (2.0.8)
graphviz (0.4.10)
pip (9.0.1)
requests (2.10.0)
setuptools (28.8.0)
smmap (0.9.0)

In the future, just type source ~/a_folder/bin/activate to start developing.