# onionscan **Repository Path**: xgadmin/onionscan ## Basic Information - **Project Name**: onionscan - **Description**: OnionScan is a free and open source tool for investigating the Dark Web. - **Primary Language**: Go - **License**: MIT - **Default Branch**: master - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2019-04-20 - **Last Updated**: 2024-05-29 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README # What is OnionScan? [![Build Status](https://travis-ci.org/s-rah/onionscan.svg?branch=onionscan-0.2)](https://travis-ci.org/s-rah/onionscan) [![Go Report Card](https://goreportcard.com/badge/github.com/s-rah/onionscan)](https://goreportcard.com/report/github.com/s-rah/onionscan) OnionScan is a free and open source tool for investigating the Dark Web. For all the amazing technological innovations in the anonymity and privacy space, there is always a constant threat that has no effective technological patch - human error. Whether it is operational security leaks or software misconfiguration - most often times the attacks on anonymity don't come from breaking the underlying systems, but from ourselves. OnionScan has two primary goals: * We want to help **operators of hidden services find and fix operational security issues with their services**. We want to help them detect misconfigurations and we want to inspire a new generation of anonymity engineering projects to help make the world a more private place. * Secondly we want to help **researchers** and **investigators monitor and track Dark Web sites**. In fact we want to make this as easy as possible. Not because we agree with the goals and motives of every investigation force out there - most often we don't. But by making these kinds of investigations easy, we hope to create a powerful incentive for new anonymity technology (see goal #1) ## Installing ### A Note on Dependencies OnionScan requires either Go 1.6 or 1.7. In order to install OnionScan you will need the following dependencies not provided by the core go standard library: * golang.org/x/net/proxy - For the Tor SOCKS Proxy connection. * golang.org/x/net/crypto - For PGP parsing * golang.org/x/net/html - For HTML parsing * github.com/rwcarlsen/goexif - For EXIF data extraction. * github.com/HouzuoGuo/tiedot/db - For crawl database. See the wiki for guidance. ### Grab with go get `go get github.com/s-rah/onionscan` ### Compile/Run from git cloned source Once you have cloned the repository into somewhere that go can find it you can run `go install github.com/s-rah/onionscan` and then run the binary in `$GOPATH/bin/onionscan`. Alternatively, you can just do `go run github.com/s-rah/onionscan.go` to run without compiling. ## Quick Start For a simple report detailing the high, medium and low risk areas found with a hidden service: `onionscan notarealhiddenservice.onion` The most interesting output comes from the verbose option: `onionscan --verbose notarealhiddenservice.onion` There is also a JSON output, if you want to integrate with another program or application: `onionscan --jsonReport notarealhiddenservice.onion` If you would like to use a proxy server listening on something other that `127.0.0.1:9050`, then you can use the --torProxyAddress flag: `onionscan --torProxyAddress=127.0.0.1:9150 notarealhiddenservice.onion` More detailed documentation on usage can be found in [doc](doc/README.md). ## What is scanned for? A list of privacy and security problems which are detected by OnionScan can be found [here](doc/what-is-scanned-for.md). You can also directly configure the types of scanning that onionscan does using the scans parameter. `./bin/onionscan --scans web notarealhiddenservice.onion` ## Running the OnionScan Correlation Lab If you are a researcher monitoring multiple sites you will definitely want to use the OnionScan Correlation Lab - a web interface hosted by OnionScan that allows you to discover, search and tag different identity correlations. You can find a full guide on the OnionScan correlation lab [here](doc/correlation-lab.md). #