CAPE comes with a set of pre-built utilities to automate several common tasks. You can find them under the “utils” folder. There more utilities than documented

Cleanup utility

Use Clean all Tasks and Samples instead which also takes care of cleaning sample and task information from MySQL and PostgreSQL databases. This utility will also delete all data from the configured MongoDB or ElasticSearch databases.

Submission Utility

Submits samples to analysis. This tool is already described in Submit an Analysis.

Web Utility

CAPE’s web interface. This tool is already described in Submit an Analysis.

Processing Utility

Run the results processing engine and optionally the reporting engine (run all reports) on an already available analysis folder, in order to not re-run the analysis if you want to re-generate the reports for it. This is used mainly in debugging and developing CAPE. For example if you want run again the report engine for analysis number 1:

$ ./utils/process.py -r 1

If you want to re-generate the reports:

$ ./utils/process.py --report 1

Following are the usage options:

$ ./utils/process.py -h

usage: process.py [-h] [-c] [-d] [-r] [-s] [-p PARALLEL] [-fp] [-mc MAXTASKSPERCHILD] [-md] [-pt PROCESSING_TIMEOUT] id

positional arguments:
  id                    ID of the analysis to process (auto for continuous processing of unprocessed tasks).

optional arguments:
  -h, --help            show this help message and exit
  -c, --caperesubmit    Allow CAPE resubmit processing.
  -d, --debug           Display debug messages
  -r, --report          Re-generate report
  -s, --signatures      Re-execute signatures on the report
  -p PARALLEL, --parallel PARALLEL
                        Number of parallel threads to use (auto mode only).
  -fp, --failed-processing
                        reprocess failed processing
                        Max children tasks per worker
  -md, --memory-debugging
                        Enable logging garbage collection related info
                        Max amount of time spent in processing before we fail a task

As best practice we suggest to adopt the following configuration if you are running CAPE with many virtual machines:

  • Run a stand alone process.py in auto mode (you choose the number of parallel threads)

This could increase the performance of your system because the reporting is not yet demanded to CAPE.

Community Download Utility

This utility downloads signatures from CAPE Community Repository and installs specific additional modules in your local setup. Following are the usage options:

$ ./utils/community.py -h

usage: community.py [-h] [-a] [-s] [-p] [-m] [-r] [-f] [-w] [-b BRANCH]

optional arguments:
  -h, --help            show this help message and exit
  -a, --all             Download everything
  -s, --signatures      Download Cuckoo signatures
  -p, --processing      Download processing modules
  -m, --machinemanagers
                        Download machine managers
  -r, --reporting       Download reporting modules
  -f, --force           Install files without confirmation
  -w, --rewrite         Rewrite existing files
  -b BRANCH, --branch BRANCH
                        Specify a different branch

Example: install all available signatures:

$ ./utils/community.py --signatures --force

Database migration utility

This utility is developed to migrate your data between CAPE’s release. It’s developed on top of the Alembic framework and it should provide data migration for both SQL database and Mongo database. This tool is already described in Upgrade from a previous release.

Stats utility

This is a really simple utility which prints some statistics about processed samples:

$ ./utils/stats.py

1 samples in db
1 tasks in db
pending 0 tasks
running 0 tasks
completed 0 tasks
recovered 0 tasks
reported 1 tasks
failed_analysis 0 tasks
failed_processing 0 tasks
roughly 32 tasks an hour
roughly 778 tasks a day

Machine utility

The machine.py utility is designed to help you automatize the configuration of virtual machines in CAPE. It takes a list of machine details as arguments and write them in the specified configuration file of the machinery module enabled in cuckoo.conf. Following are the available options:

$ ./utils/machine.py -h
usage: machine.py [-h] [--debug] [--add] [--ip IP] [--platform PLATFORM]
                [--tags TAGS] [--interface INTERFACE] [--snapshot SNAPSHOT]
                [--resultserver RESULTSERVER]

positional arguments:
  vmname                Name of the Virtual Machine.

optional arguments:
  -h, --help            show this help message and exit
  --debug               Debug log in case of errors.
  --add                 Add a Virtual Machine.
  --ip IP               Static IP Address.
  --platform PLATFORM   Guest Operating System.
  --tags TAGS           Tags for this Virtual Machine.
  --interface INTERFACE
                        Sniffer interface for this machine.
  --snapshot SNAPSHOT   Specific Virtual Machine Snapshot to use.
  --resultserver RESULTSERVER
                        IP:Port of the Result Server.