Python Taint - A Static Analysis Tool for Detecting Security Vulnerabilities in Python Web Applications


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

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.


Python Taint - A Static Analysis Tool for Detecting Security Vulnerabilities in Python Web Applications Python Taint - A Static Analysis Tool for Detecting Security Vulnerabilities in Python Web Applications Reviewed by Lydecker Black on 10:31 AM Rating: 5