Starting CAPE

Make sure to run it inside CAPE’s root directory:

$ cd /opt/CAPEv2

To start CAPE, use the command:

$ python3

You will get an output similar to this:

Cuckoo Sandbox 2.1-CAPE
Copyright (c) 2010-2015

CAPE: Config and Payload Extraction

2020-07-06 10:24:38,490 [lib.cuckoo.core.scheduler] INFO: Using "kvm" machine manager with max_analysis_count=0, max_machines_count=10, and max_vmstartup_count=10
2020-07-06 10:24:38,552 [lib.cuckoo.core.scheduler] INFO: Loaded 100 machine/s
2020-07-06 10:24:38,571 [lib.cuckoo.core.scheduler] INFO: Waiting for analysis tasks.

Now CAPE is ready to run and it’s waiting for submissions. accepts some command line options as shown by the help:

usage: [-h] [-q] [-d] [-v] [-a] [-t] [-m MAX_ANALYSIS_COUNT]

optional arguments:
-h, --help            show this help message and exit
-q, --quiet           Display only error messages
-d, --debug           Display debug messages
-v, --version         show program's version number and exit
-a, --artwork         Show artwork
-t, --test            Test startup
                        Maximum number of analyses

Most importantly --debug and --quiet respectively increase and decrease the logging verbosity.

Poetry users

If you used poetry to install dependencies, you should launch cape with the following command:

$ sudo -u cape poetry run python3

If you get any dependency-related error, make sure you execute the extra/ script.:

$ sudo -u cape poetry run extra/


If you wanted to launch CAPE and received an error like PermissionError: [Errno 13] Permission denied: '/opt/CAPEv2/log/cuckoo.log' it means that you are not executing the CAPE ( file with the appropriate user. Remember that the user meant to execute CAPE is the cape user. In fact, after installing CAPE with, the directory should look similar to the following structure:


In order to execute CAPE as the cape user you can either launch a shell or execute the following command (notice the command is using Poetry):

$ sudo -u cape poetry run python3

Starting processing data generated by virtual machine

See -h for all latest options, for better customization:

usage: [-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

$ python3 utils/ -p7 auto