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https://github.com/s-rah/onionscan
OnionScan is a free and open source tool for investigating the Dark Web.
https://github.com/s-rah/onionscan
Last synced: 3 days ago
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OnionScan is a free and open source tool for investigating the Dark Web.
- Host: GitHub
- URL: https://github.com/s-rah/onionscan
- Owner: s-rah
- License: other
- Created: 2016-04-08T06:58:16.000Z (over 8 years ago)
- Default Branch: master
- Last Pushed: 2024-08-09T23:55:59.000Z (4 months ago)
- Last Synced: 2024-11-26T13:03:10.508Z (17 days ago)
- Language: Go
- Homepage: https://twitter.com/OnionScan
- Size: 885 KB
- Stars: 2,889
- Watchers: 169
- Forks: 599
- Open Issues: 82
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
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README
# What is OnionScan?
[](https://travis-ci.org/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).
# 