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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: git clone https://github.com/python-security/pyt.git python setup.py install 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: mr.thalmann@gmail.com 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. Download pyt-master.zip Source: https://github.com/python-security/pyt