Distributed Cuckoo

As mentioned in Submit an Analysis, Cuckoo provides a REST API for Distributed Cuckoo usage. The distributed script allows one to setup a single REST API point to which samples and URLs can be submitted which will then, in turn, be submitted to one of the configured Cuckoo nodes.

A typical setup thus includes a machine on which the distributed script is run and one or more machines running an instance of the Cuckoo daemon (./cuckoo.py) and the Cuckoo REST API.

A few notes;

  • Using the distributed script makes more sense when running at least two cuckoo nodes.
  • The distributed script can be run on a machine that also runs a Cuckoo daemon and REST API, however, make sure it has enough disk space if the intention is to submit a lot of samples.

Dependencies

The distributed script uses a few Python libraries which can be installed through the following command (on Debian/Ubuntu):

$ sudo pip install flask flask-sqlalchemy requests

Starting the Distributed REST API

The Distributed REST API requires a few commandline options in order to run. Following is a listing of all available commandline options:

$ ./distributed/app.py -h

usage: app.py [-h] [-s SETTINGS] [-v] [host] [port]

positional arguments:
    host                  Host to listen on.
    port                  Port to listen on.

optional arguments:
    -h, --help            show this help message and exit
    -s SETTINGS, --settings SETTINGS
                          Settings file.
    -v, --verbose         Enable verbose logging.

The various configuration options are described in the configuration file, but following we have more in-depth descriptions as well.

Report Formats

The reporting formats denote which reports you’d like to retrieve later on. Note that all task-related data will be removed from the Cuckoo nodes once the related reports have been fetches so that the machines are not running out of disk space. This does, however, force you to specify all the report formats that you’re interested in, because otherwise that information will be lost.

Reporting formats include, but are not limited to and may also include your own reporting formats, json, html, etc.

Samples Directory

The samples directory denotes the directory where the submitted samples will be stored temporarily, until they’re passed on to a Cuckoo node and processed.

Reports Directory

Much like the Samples Directory the Reports Directory defines the directory where reports will be stored until they’re fetched and deleted from the Distributed REST API.

RESTful resources

Following are all RESTful resources. Also make sure to check out the Quick usage section which documents the most commonly used commands.

Resource Description
GET GET /api/node Get a list of all enabled Cuckoo nodes.
POST POST /api/node Register a new Cuckoo node.
GET GET /api/node/<name> Get basic information about a node.
PUT PUT /api/node/<name> Update basic information of a node.
DELETE DELETE /api/node/<name> Disable (not completely remove!) a node.
GET GET /api/task Get a list of all (or a part) of the tasks in the database.
POST POST /api/task Create a new analysis task.
GET GET /api/task/<id> Get basic information about a task.
DELETE DELETE /api/task/<id> Delete all associated information of a task.
GET GET /api/report/<id>/<format> Fetch an analysis report.

GET /api/node

Returns all enabled nodes. For each node its associated name, API url, and machines are returned:

$ curl http://localhost:9003/api/node
{
    "success": true,
    "nodes": {
        "localhost": {
            "machines": [
                {
                    "name": "cuckoo1",
                    "platform": "windows",
                    "tags": []
                }
            ],
            "name": "localhost",
            "url": "http://localhost:8090/"
        }
    }
}

POST /api/node

Register a new Cuckoo node by providing the name and the URL:

$ curl http://localhost:9003/api/node -F name=localhost \
    -F url=http://localhost:8090/
{
    "success": true
}

GET /api/node/<name>

Get basic information about a particular Cuckoo node:

$ curl http://localhost:9003/api/node/localhost
{
    "success": true,
    "nodes": [
        {
            "name": "localhost",
            "url": "http://localhost:8090/"
            "machines": [
                {
                    "name": "cuckoo1",
                    "platform": "windows",
                    "tags": []
                }
            ]
        }
    ]
}

PUT /api/node/<name>

Update basic information of a Cuckoo node:

$ curl -XPUT http://localhost:9003/api/node/localhost -F name=newhost \
    -F url=http://1.2.3.4:8090/
{
    "success": true
}

DELETE /api/node/<name>

Disable a Cuckoo node, therefore not having it process any new tasks, but keeping its history in the Distributed’s database:

$ curl -XDELETE http://localhost:9003/node/localhost
{
    "success": true
}

GET /api/task

Get a list of all tasks in the database. In order to limit the amount of results, there’s an offset, limit, finished, and owner field available:

$ curl http://localhost:9003/api/task?limit=1
{
    "success": true,
    "tasks": {
        "1": {
            "clock": null,
            "custom": null,
            "owner": "",
            "enforce_timeout": null,
            "machine": null,
            "memory": null,
            "options": null,
            "package": null,
            "path": "/tmp/dist-samples/tmphal8mS",
            "platform": "windows",
            "priority": 1,
            "tags": null,
            "task_id": 1,
            "timeout": null
        }
    }
}

POST /api/task

Submit a new file or URL to be analyzed:

$ curl http://localhost:9003/api/task -F file=@sample.exe
{
    "success": true,
    "task_id": 2
}

GET /api/task/<id>

Get basic information about a particular task:

$ curl http://localhost:9003/api/task/2
{
    "success": true,
    "tasks": {
        "2": {
            "id": 2,
            "clock": null,
            "custom": null,
            "owner": "",
            "enforce_timeout": null,
            "machine": null,
            "memory": null,
            "options": null,
            "package": null,
            "path": "/tmp/tmpPwUeXm",
            "platform": "windows",
            "priority": 1,
            "tags": null,
            "timeout": null,
            "task_id": 1,
            "node_id": 2,
            "finished": false
        }
    }
}

DELETE /api/task/<id>

Delete all associated data of a task, namely the binary and the reports:

$ curl -XDELETE http://localhost:9003/api/task/2
{
    "success": true
}

GET /api/report/<id>/<format>

Fetch a report for the given task in the specified format:

# Defaults to the JSON report.
$ curl http://localhost:9003/report/2
...

Quick usage

For practical usage the following few commands will be most interesting.

Register a Cuckoo node - a Cuckoo API running on the same machine in this case:

$ curl http://localhost:9003/api/node \
    -F name=localhost -F url=http://localhost:8090/

Disable a Cuckoo node:

$ curl -XDELETE http://localhost:9003/api/node/localhost

Submit a new analysis task without any special requirements (e.g., using Cuckoo tags, a particular machine, etc):

$ curl http://localhost:9003/api/task -F file=@/path/to/sample.exe

Get the report of a task has been finished (if it hasn’t finished you’ll get an error with code 420). Following example will default to the JSON report:

$ curl http://localhost:9003/api/report/1

Proposed setup

The following description depicts a Distributed Cuckoo setup with two Cuckoo machines, cuckoo0 and cuckoo1. In this setup the first machine, cuckoo0, also hosts the Distributed Cuckoo REST API.

Configuration settings

Our setup will require a couple of updates with regards to the configuration files.

conf/cuckoo.conf

Update process_results to off as we will be running our own results processing script (for performance reasons).

Update tmppath to something that holds enough storage to store a few hundred binaries. On some servers or setups /tmp may have a limited amount of space and thus this wouldn’t suffice.

Update connection to use something not sqlite3. Preferably PostgreSQL or MySQL. SQLite3 doesn’t support multi-threaded applications that well and this will give errors at random if used.

You should create your own empty database for the distributed cuckoo setup. Do not be tempted to use any existing cuckoo database in order to avoid update problems with the DB scripts. In the config use the new database name, the remaining stuff like usernames , servers can be the same as for your cuckoo install.Don´t forget to use one DB per node and another one more for the first machine which run the distributed script (so the say the “management machine” ).

conf/processing.conf

You may want to disable some processing modules, such as virustotal.

conf/reporting.conf

Depending on which report(s) are required for integration with your system it might make sense to only make those report(s) that you’re going to use. Thus disable the other ones.

conf/virtualbox.conf

Assuming VirtualBox is the Virtual Machine manager of choice, the mode will have to be changed to headless or you will have some restless nights.

Setup Cuckoo

On each machine the following three scripts should be ran:

./cuckoo.py
./utils/api.py -H 1.2.3.4  # IP accessible by the Distributed script.
./utils/process.py auto

One way to do this is by placing each script in its own screen(1) session as follows, this allows one to check back on each script to ensure it’s (still) running successfully:

$ screen -S cuckoo  ./cuckoo.py
$ screen -S api     ./utils/api.py
$ screen -S process ./utils/process.py auto

Setup Distributed Cuckoo

On the first machine (so the say the “management machine” ) start a few separate screen(1) sessions for the Distributed Cuckoo scripts with all the required parameters (see the rest of the documentation on the parameters for this script):

$ screen -S distributed ./distributed/app.py
$ SCREEN -S dist_scheduler ./distributed/instance.py dist.scheduler
$ SCREEN -S dist_status ./distributed/instance.py dist.status
$ SCREEN -S cuckoo0 ./distributed/instance.py -v cuckoo0
$ SCREEN -S cuckoo1 ./distributed/instance.py -v cuckoo1

The -v parameter enables verbose output and the cuckoo1 parameter is the name assigned to the actual cuckoo instance running the virtual machine while registering the node as outlined below.It´s mandatory to register the nodes before run the instance.py due to the script check the DB.

Register Cuckoo nodes

As outlined in Quick usage the Cuckoo nodes have to be registered with the Distributed Cuckoo script:

$ curl http://localhost:9003/api/node -F name=cuckoo0 -F url=http://localhost:8090/
$ curl http://localhost:9003/api/node -F name=cuckoo1 -F url=http://1.2.3.4:8090/

Having registered the Cuckoo nodes all that’s left to do now is to submit tasks and fetch reports once finished. Documentation on these commands can be found in the Quick usage section. In case you are not using localhost, replace localhost with the IP of the node where there distributed.py is running and the -F url parameter points to the nodes running the actual virtual machines.

If you want to experiment a real load balancing between the nodes you should use a lower value for the threshold parameter in the distributed/settings.py file, the default value is 500.