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

Python boilerplate using uv, pre-commit, prettier, pytest, GitHub Actions, mypy, ruff, bandit & docformatter.

Thompson Sampling Tutorial

A pre-commit hook to find common security issues in your Python code

Another A/B test library

Code for Paper (Policy Optimization in RLHF: The Impact of Out-of-preference Data)

Frontend to display data from huskyCI analyses

[NeurIPS 2023 Spotlight] In-Context Impersonation Reveals Large Language Models' Strengths and Biases

github action to run the bandit security linter

pytest plugin to execute bandit across a codebase

An official JAX-based code for our NeuraLCB paper, "Offline Neural Contextual Bandits: Pessimism, Optimization and Generalization", ICLR 2022.

Effortlessly expose and monitor your Revolt activities

Flask Project Made with Poetry

GitHub Action to run Bandit

Combine multiple popular python security tools and generate reports or output into different formats

We use policy gradient to help agents learn optimal policies in a competitive multi-agent contextual bandit setting