Bandit is a tool designed to find common security issues in Python code.
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Updated
May 10, 2024 - Python
Bandit is a tool designed to find common security issues in Python code.
Performing security tests inside your CI
Automated security testing using bandit and flake8.
Python application to setup and run streaming (contextual) bandit experiments.
Contextual Bandits in R - simulation and evaluation of Multi-Armed Bandit Policies
Thompson Sampling Tutorial
A pre-commit hook to find common security issues in your Python code
Python boilerplate using Poetry, pre-commit, prettier, pytest, GitHub Actions, mypy, ruff, black, bandit & docformatter.
Code for Paper (Policy Optimization in RLHF: The Impact of Out-of-preference Data)
Frontend to display data from huskyCI analyses
Another A/B test library
[NeurIPS 2023 Spotlight] In-Context Impersonation Reveals Large Language Models' Strengths and Biases
pytest plugin to execute bandit across a codebase
github action to run the bandit security linter
Effortlessly expose and monitor your Revolt activities
We use policy gradient to help agents learn optimal policies in a competitive multi-agent contextual bandit setting
An official JAX-based code for our NeuraLCB paper, "Offline Neural Contextual Bandits: Pessimism, Optimization and Generalization", ICLR 2022.
Combine multiple popular python security tools and generate reports or output into different formats
A minimal demonstration of setting up a modern development environment using Python 3.10, Pyenv, Poetry, Pytest, Pre-Commit, Tox, mypy, bandit, interrogate, and related hooks.
Add a description, image, and links to the bandit topic page so that developers can more easily learn about it.
To associate your repository with the bandit topic, visit your repo's landing page and select "manage topics."