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This project forked from cyberreboot/vent

0.0 2.0 0.0 15.57 MB

Vent is a light-weight platform built to automate network collection and analysis pipelines using a flexible set of popular open source tools and technologies. Vent is python-based, extensible, leverages docker containers, and provides both an API and CLI.

License: Apache License 2.0

Makefile 1.08% Python 98.40% Shell 0.48% Go 0.05%

vent's Introduction

vent

Network Visibility (an anagram)

Codacy Badge Build Status Documentation Status PyPI version codecov Github Release Downloads Docker Hub Downloads

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overview

vent is a library that includes a CLI designed to serve as a general platform for analyzing network traffic. built with some basic functionality, vent serves as a user-friendly platform to build custom plugins on to perform user-defined processing on incoming network data. vent supports any filetype, but only processes ones based on the types of plugins installed for that instance of vent.

simply create your plugins, point vent to them & install them, and drop a file in vent to begin processing!

dependencies

docker>=1.13.1
git
make (if building from source)
pip
python2.7.x

option 1: running inside of a Docker container

docker run -it -v /var/run/docker.sock:/var/run/docker.sock cyberreboot/vent

option 2: installing

pip install vent

option 3: getting the bits and building

git clone https://github.com/CyberReboot/vent.git
cd vent
make # (sudo may be required to install the vent command in the system bin path)

Note - If you already have docker-py installed on your machine, you may need to pip uninstall docker-py first. vent will install docker-py as part of the installation process, however there are known incompatibilities of docker-py with older versions.

option 4: deploying with an ISO

go to releases and download the ISO from the latest release (or build your own: cd dev && make) deploy the ISO as a VM or on bare metal.

running

vent

contributing to vent

Want to contribute? Awesome! Issue a pull request or see more details here.

See this for a crash course on npyscreen: the TUI used by Vent!

vent's People

Watchers

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