Code Monkey home page Code Monkey logo

apisec-toolbox's Introduction

APIsec Toolbox

The APIsec toolbox is a Swiss knife for API Security testing.

This repository includes a wordlist bundle, dedicated docker image, labs, and resources. It's dedicated to experimenting around automatic and manual flows related to security testing for APIs.

WARNING: This is a development repository, use it at your own risk !!!

1 - workdlists bundle

Collect several wordlists and build a bundle.

2 - build docker image for apisec-toolbox

The apisec-toolbox is a swiss knife for API security testing.

The main image is based on the Dockerfile and has the following features:

  • multi-stage build to save disk space
  • linux os utilities installed as root
  • tools and utilities installed as appuser (normal user with sudo)

Note: there is an old image called api-security-toolbox that will be removed in the future.

3. run the apisec-toolbox

docker run -it --rm arainho/apisec-toolbox /bin/bash

Set a password for user

passwd appuser

warning: for simplicity, the sudo works without password for any command.
You are advised to remove the NOPASSWD word from the line appuser ALL=(ALL) ALL in /etc/sudoers.d/appuser file and the linux will start asking your password to run commands as sudo.

If you need apicheck tools inside the apisec-toolbox you need to share 'docker unix socket' from the host

docker run -it --rm -v /var/run/docker.sock:/var/run/docker.sock arainho/apisec-toolbox /bin/bash

warning: Using docker.sock could expose your host within the apisec-toolbox container as stated in this article.

Then you can install apicheck tools

acp install jwt-checker
acp install acurl
acp install oas-checker
acp install send-to-proxy
acp install apicheck-curl
acp install sensitive-data
acp install replay
acp install openapiv3-lint
acp install openapiv2-lint
acp install oas-checker

4 - run vulnerable API's locally

The labs folders has scripts to build and run vulnerable APIs locally.
The purpose is to have local labs to exploit and learn API security.

5. collaboration

For adding new tools or fix broken entries from ToDo list use the following procedure:

  1. Clone the repository

    git clone https://github.com/arainho/apisec-toolbox
    git checkout -b tool-xyz
  2. Open the Dockerfile.testing with a text editor and change the following lines:

    • ENV TOOL_NAME="tool-name"
    • RUN <add installation commands here>
  3. Build the image

    docker build -t apisec-toolbox:local -f Dockerfile.testing
  4. If everything looks good, create a pull request

    git add Dockerfile.testing
    git commit -m "new entry for tool-xyz"
    git push origin tool-xyz

    you can check more information on creating a pull request here

  5. A maintainer will review the pull request

    • manual review
    • add extra lines on Dockerfile.multistage
    • github actions workflow will run
    • If all looks good your PR will pass ๐Ÿ˜ƒ

apisec-toolbox's People

Contributors

arainho avatar pantaleao avatar

Stargazers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

Watchers

 avatar  avatar  avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.