2.5 KiB
Using dfDewey
usage: dfdcli.py [-h] [--no_base64] [--no_gzip] [--no_zip] [-s SEARCH] [--search_list SEARCH_LIST] case [image]
positional arguments:
case case ID
image image file (default: 'all')
optional arguments:
-h, --help show this help message and exit
--no_base64 don't decode base64
--no_gzip don't decompress gzip
--no_zip don't decompress zip
-s SEARCH, --search SEARCH
search query
--search_list SEARCH_LIST
file with search queries
Docker
If using Elasticsearch and PostgreSQL in Docker, they can be started using
docker-compose from the docker
folder.
docker-compose up -d
Note: Java memory for Elasticsearch is set high to improve performance when
indexing large volumes of data. If running on a system with limited resources,
you can change the setting in docker/docker-compose.yml
.
To shut the containers down again (and purge the data), run:
docker-compose down
Running dfDewey in Docker
The docker
folder also contains a Dockerfile
to build dfDewey and its
dependencies into a Docker image.
Build the image from the docker
folder with:
docker build -t <docker_name> ./
When running dfDewey within a Docker container, we need to give the container access to the host network so it will be able to access Elasticsearch and PostgreSQL in their respective containers. We also need to map a folder in the container to allow access to the image we want to process. For example:
docker run --network=host -v ~/images/:/mnt/images <docker_name> dfdewey -h
Processing an Image
To process an image in dfDewey, you need to supply a CASE
and IMAGE
.
dfdcli.py testcase /path/to/image.dd
dfDewey will have bulk_extractor decode base64 data, and decompress gzip / zip
data by default. These can be disabled by adding the flags --no_base64
,
--no_gzip
, and --no_zip
.
Searching
To search the index for a single image, you need to supply a CASE
, IMAGE
,
and SEARCH
.
dfdcli.py testcase /path/to/image.dd -s 'foo'
If an IMAGE
is not provided, dfDewey will search all images in the given case.
dfDewey can also search for a list of terms at once. The terms can be placed in a text file one per line. In this case, only the number of results for each term is returned.
dfdcli.py testcase /path/to/image.dd --search_list search_terms.txt