Submit an Analysis

Submission Utility

API

Distributed CAPE

Web Interface

Python Functions

Submission Utility

The easiest way to submit an analysis is to use the provided submit.py command-line utility. It currently has the following options available:

usage: submit.py [-h] [--remote REMOTE] [--url] [--package PACKAGE]
                 [--custom CUSTOM] [--timeout TIMEOUT] [--options OPTIONS]
                 [--priority PRIORITY] [--machine MACHINE]
                 [--platform PLATFORM] [--memory] [--enforce-timeout]
                 [--clock CLOCK] [--tags TAGS] [--max MAX] [--pattern PATTERN]
                 [--shuffle] [--unique] [--quiet]
                 target

positional arguments:
  target               URL, path to the file or folder to analyze

optional arguments:
  -h, --help           show this help message and exit
  --remote REMOTE      Specify IP:port to a CAPE API server to submit
                       remotely
  --url                Specify whether the target is an URL
  --package PACKAGE    Specify an analysis package
  --custom CUSTOM      Specify any custom value
  --timeout TIMEOUT    Specify an analysis timeout
  --options OPTIONS    Specify options for the analysis package (e.g.
                       "name=value,name2=value2")
  --priority PRIORITY  Specify a priority for the analysis represented by an
                       integer
  --machine MACHINE    Specify the identifier of a machine you want to use
  --platform PLATFORM  Specify the operating system platform you want to use
                       (windows/darwin/linux)
  --memory             Enable to take a memory dump of the analysis machine
  --enforce-timeout    Enable to force the analysis to run for the full
                       timeout period
  --clock CLOCK        Set virtual machine clock
  --tags TAGS          Specify tags identifier of a machine you want to use
  --max MAX            Maximum samples to add in a row
  --pattern PATTERN    Pattern of files to submit
  --shuffle            Shuffle samples before submitting them
  --unique             Only submit new samples, ignore duplicates
  --quiet              Only print text on failure

If you specify a directory as the target path, all of the files contained within that directory will be submitted for analysis.

The concept of analysis packages will be dealt with later in this documentation (at Analysis Packages). The following are some examples of how to use the submit.py tool:

Warning

Remember to use the cape user. The following commands are executed as cape.

Example: Submit a local binary:

$ poetry run python utils/submit.py /path/to/binary

Example: Submit an URL:

$ poetry run python utils/submit.py --url http://www.example.com

Example: Submit a local binary and specify a higher priority:

$ poetry run python utils/submit.py --priority 5 /path/to/binary

Example: Submit a local binary and specify a custom analysis timeout of 60 seconds:

$ poetry run python utils/submit.py --timeout 60 /path/to/binary

Example: Submit a local binary and specify a custom analysis package:

$ poetry run python utils/submit.py --package <name of package> /path/to/binary

Example: Submit a local binary and specify a custom analysis package and some options (in this case a command line argument for the malware):

$ poetry run python utils/submit.py --package exe --options arguments=--dosomething /path/to/binary.exe

Example: Submit a local binary to be run on the virtual machine cape1:

$ poetry run python utils/submit.py --machine cape1 /path/to/binary

Example: Submit a local binary to be run on a Windows machine:

$ poetry run python utils/submit.py --platform windows /path/to/binary

Example: Submit a local binary and take a full memory dump of the analysis machine once the analysis is complete:

$ poetry run python utils/submit.py --memory /path/to/binary

Example: Submit a local binary and force the analysis to be executed for the full timeout (disregarding the internal mechanism that CAPE uses to decide when to terminate the analysis):

$ poetry run python utils/submit.py --enforce-timeout /path/to/binary

Example: Submit a local binary and set the virtual machine clock. The format is %m-%d-%Y %H:%M:%S. If not specified, the current time is used. For example, if we want to run a sample on January 24th, 2001, at 14:41:20:

$ poetry run python utils/submit.py --clock "01-24-2001 14:41:20" /path/to/binary

Example: Submit a sample for Volatility analysis (to reduce side effects of the CAPE hooking, switch it off with options free=True):

$ poetry run python utils/submit.py --memory --options free=True /path/to/binary

`--options` Options Available

filename: Rename the sample file
name: This will force family extractor to run, Ex: name=trickbot
curdir: Change from where execute sample, by default %TEMP%, Ex: curdir=%APPDATA% or
curdir=%APPDATA%MicrosoftWindowsStart MenuProgramsStartup
executiondir: Sets directory to launch the file from. Need not be the same as the directory of sample file. Defaults to %TEMP% if both executiondir and curdir are not specified. Only supports full paths
free: Run without monitoring (disables many capabilities) Ex: free=1
force-sleepskip: Override default sleep skipping behavior: 0 disables all sleep skipping, 1 skips all sleeps.
full-logs: By default, logs prior to network activity for URL analyses and prior to access of the file in question for non-executable formats are suppressed. Set to 1 to disable log suppression.
force-flush: For performance reasons, logs are buffered before being sent back to the result server. We make every attempt to flush the buffer at critical points including when exceptions occur, but in some rare termination scenarios, logs may be lost. Set to 1 to force flushing of the log buffers after any non-duplicate API is called, set to 2 to force flushing of every log.
no-stealth: Set to 1 to disable anti-anti-VM/sandbox code enabled by default.
buffer-max: When set to an integer of your choice, changes the maximum number of bytes that can be logged for most API buffers.
large-buffer-max: Some hooked APIs permit larger buffers to be logged. To change the limit for this, set this to an integer of your choice.
norefer: Disables use of a fake referrer when performing URL analyses
file: When using the zip or rar package, set the name of the file to execute
password: When using the zip or rar package, set the password to use for extraction. Also used when analyzing password-protected Office documents.
function: When using the dll package, set the name of the exported function to execute
dllloader: When using the dll package, set the name of the process loading the DLL (defaults to rundll32.exe).
arguments: When using the dll, exe, or python packages, set the arguments to be passed to the executable or exported function.
appdata: When using the exe package, set to 1 to run the executable out of the Application Data path instead of the Temp directory.
startbrowser: Setting this option to 1 will launch a browser 30 seconds into the analysis (useful for some banking trojans).
browserdelay: Sets the number of seconds to wait before starting the browser with the startbrowser option. Defaults to 30 seconds.
url: When used with the startbrowser option, this will determine the URL the started browser will access.
debug: Set to 1 to enable reporting of critical exceptions occurring during analysis, set to 2 to enable reporting of all exceptions.
disable_hook_content: Set to 1 to remove functionality of all hooks except those critical for monitoring other processes. Set to 2 to apply to all hooks.
hook-type: Valid for 32-bit analyses only. Specifies the hook type to use: direct, indirect, or safe. Safe attempts a Detours-style hook.
serial: Spoof the serial of the system volume as the provided hex value
single-process: When set to 1 this will limit behavior monitoring to the initial process only.
exclude-apis: Exclude the colon-separated list of APIs from being hooked
exclude-dlls: Exclude the colon-separated list of DLLs from being hooked
dropped-limit: Override the default dropped file limit of 100 files
compression: When set to 1 this will enable CAPE’s extraction of compressed payloads
extraction: When set to 1 this will enable CAPE’s extraction of payloads from within each process
injection: When set to 1 this will enable CAPE’s capture of injected payloads between processes
combo: This combines compression, injection and extraction with process dumps
dump-on-api: Dump the calling module when a function from the colon-separated list of APIs is used
bp0: Sets breakpoint 0 (processor/hardware) to a VA or RVA value (or module::export). Applies also to bp1-bp3.
file-offsets: Breakpoints in bp0-bp3 will be interpreted as PE file offsets rather than RVAs
break-on-return: Sets breakpoints on the return address(es) from a colon-separated list of APIs
base-on-api: Sets the base address to which breakpoints will be applied (and sets breakpoints)
depth: Sets the depth an instruction trace will step into (defaults to 0, requires Trace package)
count: Sets the number of instructions in a trace (defaults to 128, requires Trace package)
referrer: Specify the referrer to be used for URL tasks, overriding the default Google referrer
loop_detection: Set this option to 1 to enable loop detection (compress call logs - behavior analysis)
static: Check if config can be extracted statically, if not, send to vm
Dl&Exec add headers: Example: dnl_user_agent: “CAPE Sandbox”, dnl_referrer: google
servicedesc - for service package: Service description
arguments - for service package: Service arguments
store_memdump: Will force STORE memdump, only when submitting to analyzer node directly, as distributed cluster can modify this
pre_script_args: Command line arguments for pre_script. Example: pre_script_args=file1 file2 file3
pre_script_timeout: pre_script_timeout will default to 60 seconds. Script will stop after timeout Example: pre_script_timeout=30
during_script_args: Command line arguments for during_script. Example: during_script_args=file1 file2 file3
pwsh: - for ps1 package: prefer PowerShell Core, if available in the vm

Web Interface

Detailed usage of the web interface is described in Web interface.

API

Detailed usage of the REST API interface is described in REST API.

Distributed CAPE

Detailed usage of the Distributed CAPE API interface is described in Distributed CAPE.

Python Functions

To keep track of submissions, samples, and overall execution, CAPE uses a popular Python ORM called SQLAlchemy that allows you to make the sandbox use PostgreSQL, SQLite, MySQL, and several other SQL database systems.

CAPE is designed to be easily integrated into larger solutions and to be fully automated. To automate analysis submission we suggest using the REST API interface described in REST API, but in case you want to write a Python submission script, you can also use the add_path() and add_url() functions.

add_path(file_path[, timeout=0[, package=None[, options=None[, priority=1[, custom=None[, machine=None[, platform=None[, memory=False[, enforce_timeout=False], clock=None[]]]]]]]]])

Add a local file to the list of pending analysis tasks. Returns the ID of the newly generated task.

Parameters:

file_path (string) – path to the file to submit
timeout (integer) – maximum amount of seconds to run the analysis for
package (string or None) – analysis package you want to use for the specified file
options (string or None) – list of options to be passed to the analysis package (in the format key=value,key=value)
priority (integer) – numeric representation of the priority to assign to the specified file (1 being low, 2 medium, 3 high)
custom (string or None) – custom value to be passed over and possibly reused at processing or reporting
machine (string or None) – CAPE identifier of the virtual machine you want to use, if none is specified one will be selected automatically
platform (string or None) – operating system platform you want to run the analysis one (currently only Windows)
memory (True or False) – set to True to generate a full memory dump of the analysis machine
enforce_timeout (True or False) – set to True to force the execution for the full timeout
clock (string or None) – provide a custom clock time to set in the analysis machine

Return type:

integer

Example usage:

>>> from lib.cuckoo.core.database import Database
>>> db = Database()
>>> db.add_path("/tmp/malware.exe")
1
>>>

add_url(url[, timeout=0[, package=None[, options=None[, priority=1[, custom=None[, machine=None[, platform=None[, memory=False[, enforce_timeout=False], clock=None[]]]]]]]]])

Add a local file to the list of pending analysis tasks. Returns the ID of the newly generated task.

Parameters:

url (string) – URL to analyze
timeout (integer) – maximum amount of seconds to run the analysis for
package (string or None) – analysis package you want to use for the specified URL
options (string or None) – list of options to be passed to the analysis package (in the format key=value,key=value)
priority (integer) – numeric representation of the priority to assign to the specified URL (1 being low, 2 medium, 3 high)
custom (string or None) – custom value to be passed over and possibly reused at processing or reporting
machine (string or None) – CAPE identifier of the virtual machine you want to use, if none is specified one will be selected automatically
platform (string or None) – operating system platform you want to run the analysis one (currently only Windows)
memory (True or False) – set to True to generate a full memory dump of the analysis machine
enforce_timeout (True or False) – set to True to force the execution for the full timeout
clock (string or None) – provide a custom clock time to set in the analysis machine

Return type:

integer

Example Usage:

>>> from lib.cuckoo.core.database import Database
>>> db = Database()
>>> db.add_url("http://www.cuckoosandbox.org")
2
>>>

Troubleshooting

submit.py

If you try to submit an analysis using submit.py and your output looks like:

$ sudo -u cape poetry run python submit.py /path/to/binary/test.exe
Error: adding task to database

It could be due to errors while trying to communicate with the PostgreSQL instance. PostgreSQL is installed and configured by default when executing cape2.sh. Make sure your PostgreSQL instance is active and running. To check it out execute the following command:

$ sudo systemctl status postgresql

If the status is other than Active (it can be in exited status, as long as it is Active), there is something that needs to be fixed.

The logs for PostgreSQL can be found under /var/log/postgresql/*.log.

If everything is working regarding PostgreSQL, make sure the cape user is able to access (both read and write) the directories involved in the analysis. For example, cape must be able to read and write in /tmp.

Analysis results

Check Analysis Results.

Submit an Analysis

Submission Utility

--options Options Available

Web Interface

API

Distributed CAPE

Python Functions

Troubleshooting

submit.py

Analysis results

`--options` Options Available