<commit_before># Gransk - Document processing for investigations

A tool for when you have a bunch of documents to figure out of. [Introduction to Gransk (YouTube)](https://www.youtube.com/watch?v=hkfLQFRShJ8)

[![Build Status](https://travis-ci.org/pcbje/gransk.svg?branch=master)](https://travis-ci.org/pcbje/gransk) [![Documentation Status](https://readthedocs.org/projects/gransk/badge/?version=latest)](http://gransk.readthedocs.io/?badge=latest)
 [![Coverage Status](https://coveralls.io/repos/github/pcbje/gransk/badge.svg?branch=master)](https://coveralls.io/github/pcbje/gransk?branch=master)

Gransk is an open source tool that aims to be a Swiss army knife of document processing and analysis.
Its primary objective is to quikly provide users with insight to their documents during investigations.
It includes a processing engine written in Python and a web interface. Under the hood it uses Apache Tika for
content extraction, Elasticsearch for data indexing, and dfVFS to unpack disk images.

## Quickstart

##### Using [VirtualBox](https://www.virtualbox.org/wiki/Downloads):

1. Download Gransk VM: https://drive.google.com/uc?export=download&id=0B6iPjQOwe4MKOVhma2VhWmpWaEE
2. Open VirtualBox and click "File" -> "Import appliance". Choose downloaded VM.
3. Double click on the imported machine. (Hold shift to run in background)
4. After a couple of seconds. open a web browser and go to [http://localhost:8084](http://localhost:8084)

##### Using [Docker](https://www.docker.com):

```
curl -o docker-quickstart.sh -X GET https://github.com/pcbje/gransk/raw/master/docker-quickstart.sh
sh ./docker-quickstart.sh
```


## Features

* Unpack disk images with dfVFS and archives with 7zip
* Extract metadata and text from documents with Apache Tika<commit_msg>Fix docker-quickstart.sh link in README.md<commit_after># Gransk - Document processing for investigations

A tool for when you have a bunch of documents to figure out of. [Introduction to Gransk (YouTube)](https://www.youtube.com/watch?v=hkfLQFRShJ8)

[![Build Status](https://travis-ci.org/pcbje/gransk.svg?branch=master)](https://travis-ci.org/pcbje/gransk) [![Documentation Status](https://readthedocs.org/projects/gransk/badge/?version=latest)](http://gransk.readthedocs.io/?badge=latest)
 [![Coverage Status](https://coveralls.io/repos/github/pcbje/gransk/badge.svg?branch=master)](https://coveralls.io/github/pcbje/gransk?branch=master)

Gransk is an open source tool that aims to be a Swiss army knife of document processing and analysis.
Its primary objective is to quikly provide users with insight to their documents during investigations.
It includes a processing engine written in Python and a web interface. Under the hood it uses Apache Tika for
content extraction, Elasticsearch for data indexing, and dfVFS to unpack disk images.

## Quickstart

##### Using [VirtualBox](https://www.virtualbox.org/wiki/Downloads):

1. Download Gransk VM: https://drive.google.com/uc?export=download&id=0B6iPjQOwe4MKOVhma2VhWmpWaEE
2. Open VirtualBox and click "File" -> "Import appliance". Choose downloaded VM.
3. Double click on the imported machine. (Hold shift to run in background)
4. After a couple of seconds. open a web browser and go to [http://localhost:8084](http://localhost:8084)

##### Using [Docker](https://www.docker.com):

```
curl -o docker-quickstart.sh -X GET https://raw.githubusercontent.com/pcbje/gransk/master/docker-quickstart.sh
sh ./docker-quickstart.sh
```


## Features

* Unpack disk images with dfVFS and archives with 7zip
* Extract metadata and text from documents with Apache Tika
{'fraction_non_alphanumeric': 0.11838440111420613, 'fraction_numerical': 0.010027855153203343, 'mean_word_length': 5.1279863481228665, 'pattern_counts': {'":': 0, '<': 3, '<?xml version=': 0, '>': 5, 'https://': 20, 'lorem ipsum': 0, 'www.': 6, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 8, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '1932910', 'n_tokens_mistral': 1156, 'n_tokens_neox': 1098, 'n_words': 345}