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Moved to https://github.com/liquidinvestigations/hoover-snoop2

And documentation moved to https://hoover-snoop2.readthedocs.io/en/latest/

Snoop

Snoop will walk a file dump, extract text and metadata for each document found and index that data into elasticsearch.

Snoop serves as a standalone web server that outputs all the data available for each indexed document.

Supported file formats

Installation

Snoop depends on lxml (which compiles against libxml2 and libxslt) and psycopg2 (which compiles against the PostgreSQL client headers). On Debian/Ubuntu the required packages are build-essential, libmagic, python3-dev, libxml2-dev, libxslt1-dev and postgresql-server-dev-9.4 (or newer).

Snoop can talk to a bunch of tools. Some understand a certain data format, others do useful processing. See "Optional Dependencies" to install them.

  1. Create a virtualenv and run pip install -r requirements.txt

  2. Configuration - create snoop/site/settings/local.py, you can use example_local.py as a template.

    • DATABASES: django database configuration
    • SNOOP_ROOT: path to the dump
    • SNOOP_ELASTICSEARCH_URL: url to elasticsearch server
    • SNOOP_ELASTICSEARCH_INDEX: name of elasticsearch index where to index the data
    • SNOOP_LOG_DIR: path to the dir where worker logs will be dumped

  3. Run the migrations:

    $ ./manage.py migrate

Getting started

  1. List the files in the dump, from the path configured in SNOOP_ROOT, and create entries in the database.

    $ ./manage.py walk

  2. Select documents for analysis. The argument to the digestqueue command is an SQL WHERE clause to choose which documents will be analyzed. true means all documents. They are added to the digest queue.

    $ ./manage.py digestqueue

  3. Run the digest worker to process. All documents successfully digested will be automatically added to the index queue. Run as many of these processes as you want, they don't spawn any threads but are designed to be concurrent.

    $ ./manage.py worker digest

    The worker command accepts a -x

  4. Create/reset the elasticsearch index that you set up as ELASTICSEARCH_INDEX.

    $ ./manage.py resetindex

  5. Run the index worker to push digested documents to elasticsearch.

    $ ./manage.py worker index

To digest a single document and view the JSON output:

$ ./manage.py digest 123

Optional Dependencies

Apache Tika (for metadata extraction)

Tika is used for text, language and metadata extraction.

You can download the server .jar from the Apache archive and run it:

$ wget http://archive.apache.org/dist/tika/tika-server-1.17.jar
$ java -jar tika-server-1.17.jar

After that, configure the following settings:

7z (for archive extraction)

Current setup uses 7z to process archives. On Debian/linux, use the p7zip implementation. Rar support is also needed.

$ sudo apt-get install p7zip-full
$ sudo apt-get install p7zip-rar

Configure SNOOP_SEVENZIP_BINARY to the 7z binary's path. If it's installed system-wide, just use 7z.

Set SNOOP_ARCHIVE_CACHE_ROOT to an existing folder with write access. This folder will serve as a cache for all the extracted archives.

msgconvert (for Outlook .msg emails)

Current setup uses the msgconvert script to convert .msg emails to .eml. Docs: http://www.matijs.net/software/msgconv/

$ cpanm --notest Email::Outlook::Message

Set SNOOP_MSGCONVERT_SCRIPT to the script's path. If it's installed system-wide, just use msgconvert.

Set SNOOP_MSG_CACHE to an existing folder with write access.

readpst (for Outlook .pst and .ost emails)

Current setup uses the readpst binary to convert .pst and .ost emails to the mbox format.

$ brew install libpst  #  mac
$ sudo apt-get install pst-utils  #  debian / ubuntu

Set SNOOP_READPST_BINARY to the binary's path. If it's installed system-wide, just use readpst.

Set SNOOP_PST_CACHE_ROOT to an existing folder with write access.

gpg for Hushmail-like emails

Set: