Installation

Requirements

The project leverages docker-compose with a custom python script so you need to have the following packages installed in your machine:

  • docker - v1.13.0+

  • docker-compose - v1.23.2+

  • python - v3.6+

  • There are additional python dependencies (mentioned in the requirements/pre-requirements.txt file) that can be installed using the initialize.sh script.

In some systems you could find pre-installed older versions. Please check this and install a supported version before attempting the installation. Otherwise it would fail.

Note

  • The project uses public docker images that are available on Docker Hub
  • IntelOwl is tested and supported to work in a Linux-based OS. It may also run on windows, but that is not officially supported yet.
  • Before installing remember that you must comply with the LICENSE and the Legal Terms

TL;DR

Obviously we strongly suggest reading through all the page to configure IntelOwl in the most appropriate way.

However, if you feel lazy, you could just install and test IntelOwl with the following steps. Be sure to run docker and python commands with sudo if permissions/roles have not been set

Note: We’ve added a new script initialize.sh that will check compatibility with your system and attempt to install the required dependencies.

# clone the IntelOwl project repository
git clone https://github.com/intelowlproject/IntelOwl
cd IntelOwl/

# construct environment files from templates
cp docker/env_file_app_template docker/env_file_app
cp docker/env_file_postgres_template docker/env_file_postgres
cp docker/env_file_integrations_template docker/env_file_integrations
cp frontend/public/env_template.js frontend/public/env.js

# verify installed dependencies
sudo ./initialize.sh

# start the app
sudo python3 start.py prod up

# now the application is running on http://localhost:80
# create a super user 
sudo docker exec -ti intelowl_uwsgi python3 manage.py createsuperuser

# now you can login with the created user form http://localhost:80

# Have fun!

Warning

The first time you start IntelOwl, a lot of database migrations are being applied. This requires some time. If you get 500 status code errors in the GUI, just wait few minutes and then refresh the page.

Hint

There is a YouTube video that may help in the installation process. (ManySteps have changed since v2.0.0)

Deployment Components

IntelOwl is composed of various different technologies, namely:

  • React: Frontend, using CRA and certego-ui

  • Django: Backend

  • PostgreSQL: Database

  • Rabbit-MQ: Message Broker

  • Celery: Task Queue

  • Nginx: Reverse proxy for the Django API and web asssets.

  • Uwsgi: Application Server

  • Elastic Search (optional): Auto-sync indexing of analysis’ results.

  • Kibana (optional): GUI for Elastic Search. We provide a saved configuration with dashboards and visualizations.

  • Flower (optional): Celery Management Web Interface

All these components are managed via docker-compose.

Deployment Preparation

Open a terminal and execute below commands to construct new environment files from provided templates.

cp docker/env_file_app_template docker/env_file_app
cp docker/env_file_postgres_template docker/env_file_postgres
cp docker/env_file_integrations_template docker/env_file_integrations
cp frontend/public/env_template.js frontend/public/env.js

sudo ./initialize.sh

Environment configuration (required)

In the docker/env_file_app, configure different variables as explained below.

REQUIRED variables to run the image:

  • DB_HOST, DB_PORT, DB_USER, DB_PASSWORD: PostgreSQL configuration (The DB credentals should match the ones in the env_file_postgres). If you like, you can configure the connection to an external PostgreSQL instance in the same variables. Then, to avoid to run PostgreSQL locally, please run IntelOwl with the option --use-external-database. Otherwise, DB_HOST must be postgres to have the app properly communicate with the PostgreSQL container.

Strongly recommended variable to set:

  • DJANGO_SECRET: random 50 chars key, must be unique. If you do not provide one, Intel Owl will automatically set a new secret on every run.

  • INTELOWL_WEB_CLIENT_DOMAIN (example: localhost/mywebsite.com): the web domain of your instance, this is used for generating links to analysis results.

Optional configuration:

  • OLD_JOBS_RETENTION_DAYS: Database retention for analysis results (default: 14 days). Change this if you want to keep your old analysis longer in the database.

Other optional configuration to enable specific services / features

Configuration required to enable integration with Slack:

  • SLACK_TOKEN: Slack token of your Slack application that will be used to send/receive notifications

  • DEFAULT_SLACK_CHANNEL: ID of the Slack channel you want to post the message to

Configuration required to enable Re-Captcha in the Login and the Registration Page: In the docker/env_file_app:

  • USE_RECAPTCHA: if you want to use recaptcha on your login

  • RECAPTCHA_SECRET_KEY: your recaptcha secret key In the frontend/public/env.js:

  • RECAPTCHA_SITEKEY: Recaptcha Key for your site

Configuration required to have InteOwl sending Emails (registration requests, mail verification, password reset/change, etc)

  • DEFAULT_FROM_EMAIL: email address used for automated correspondence from the site manager (example: noreply@mydomain.com)

  • DEFAULT_EMAIL: email address used for correspondence with users (example: info@mydomain.com)

  • EMAIL_HOST: the host to use for sending email with SMTP

  • EMAIL_HOST_USER: username to use for the SMTP server defined in EMAIL_HOST

  • EMAIL_HOST_PASSWORD: password to use for the SMTP server defined in EMAIL_HOST. This setting is used in conjunction with EMAIL_HOST_USER when authenticating to the SMTP server.

  • EMAIL_PORT: port to use for the SMTP server defined in EMAIL_HOST.

  • EMAIL_USE_TLS: whether to use an explicit TLS (secure) connection when talking to the SMTP server, generally used on port 587.

  • EMAIL_USE_SSL: whether to use an implicit TLS (secure) connection when talking to the SMTP server, generally used on port 465.

Database configuration (required if running PostgreSQL locally)

If you use a local PostgreSQL instance (this is the default), in the env_file_postgres you have to configure different variables as explained below.

Required variables:

  • POSTGRES_PASSWORD (same as DB_PASSWORD)

  • POSTGRES_USER (same as DB_USER)

  • POSTGRES_DB (default: intel_owl_db)

Web server configuration (required for enabling HTTPS)

Intel Owl provides basic configuration for:

  • Nginx (configuration/nginx/http.conf)

  • Uwsgi (configuration/intel_owl.ini)

In case you enable HTTPS, remember to set the environment variable HTTPS_ENABLED as “enabled” to increment the security of the application.

There are 3 options to execute the web server:

  • HTTP only (default)

    The project would use the default deployment configuration and HTTP only.

  • HTTPS with your own certificate

    The project provides a template file to configure Nginx to serve HTTPS: configuration/nginx/https.conf.

    You should change ssl_certificate, ssl_certificate_key and server_name in that file and put those required files in the specified locations.

    Then you should call the start.py script with the parameter --https to leverage the right Docker Compose file for HTTPS.

    Plus, if you use Flower, you should change in the docker/flower.override.yml the flower_http.conf with flower_https.conf.

  • HTTPS with Let’s Encrypt

    We provide a specific docker-compose file that leverages Traefik to allow fast deployments of public-faced and HTTPS-enabled applications.

    Before using it, you should configure the configuration file docker/traefik.override.yml by changing the email address and the hostname where the application is served. For a detailed explanation follow the official documentation: Traefix doc.

    After the configuration is done, you can add the option --traefik while executing the start.py

Run

Important Info

IntelOwl depends heavily on docker and docker compose so as to hide this complexity from the enduser the project leverages a custom script (start.py) to interface with docker-compose.

You may invoke $ python3 start.py –help to get help and usage info.

The CLI provides the primitives to correctly build, run or stop the containers for IntelOwl. Therefore,

  • It is possible to attach every optional docker container that IntelOwl has: multi_queue with traefik enabled while every optional docker analyzer is active.
  • It is possible to insert an optional docker argument that the CLI will pass to docker-compose

Now that you have completed different configurations, starting the containers is as simple as invoking:

$ python3 start.py prod up

You can add the parameter -d to run the application in the background.

Hint

Starting from IntelOwl 4.0.0, with the startup script you can select which version of IntelOwl you want to run (--version). This can be helpful to keep using old versions in case of retrocompatibility issues. The --version parameter checks out the Git Repository to the Tag of the version that you have chosen. This means that if you checkout to a v3.x.x version, you won't have the --version parameter anymore so you would need to manually checkout back to the master branch to use newer versions.

Stop

To stop the application you have to:

  • if executed without -d parameter: press CTRL+C

  • if executed with -d parameter: python3 start.py prod down

Cleanup of database and application

This is a destructive operation but can be useful to start again the project from scratch

python3 start.py prod down -v

After Deployment

Users creation

You may want to run docker exec -ti intelowl_uwsgi python3 manage.py createsuperuser after first run to create a superuser. Then you can add other users directly from the Django Admin Interface after having logged with the superuser account. To manage users, organizations and their visibility please refer to this section

Update and Rebuild

Rebuilding the project / Creating custom docker build

If you make some code changes and you like to rebuild the project, follow these steps:

  1. python3 start.py test build --tag=<your_tag> . to build the new docker image.

  2. Add this new image tag in the docker/test.override.yml file.

  3. Start the containers with python3 start.py test up --build.

Update to the most recent version

To update the project with the most recent available code you have to follow these steps:

$ cd <your_intel_owl_directory> # go into the project directory
$ git pull # pull new changes
$ python3 start.py prod down # kill and destroy the currently running IntelOwl containers 
$ python3 start.py prod up # restart the IntelOwl application

Note

After an upgrade, sometimes a database error in Celery Containers could happen. That could be related to new DB migrations which are not applied by the main Uwsgi Container yet. Do not worry. Wait few seconds for the Uwsgi container to start correctly, then put down the application again and restart it. The problem should be solved. If not, please feel free to open an issue on Github

Note

After having upgraded IntelOwl, in case the application does not start and you get an error like this:
PermissionError: [Errno 13] Permission denied: '/var/log/intel_owl/django/authentication.log

just run this:

sudo chown -R www-data:www-data /var/lib/docker/volumes/intel_owl_generic_logs/_data/django

and restart IntelOwl. It should solve the permissions problem.

Warning

Major versions of IntelOwl are usually incompatible from one another. Maintainers strive to keep the upgrade between major version easy but it's not always like that. Below you can find the additional process required to upgrade from each major versions.

Updating to >=5.0.0 from a 4.x.x version

IntelOwl v5 introduced some major changes regarding how the plugins and their related configuration are managed in the application. Before upgrading, some important things should be checked by the administrator:

  • A lot of database migrations will need to be applied. Just be patient few minutes once you install the new major release. If you get 500 status code errors in the GUI, just wait few minutes and then refresh the page.

  • We moved away from the old big analyzer_config.json which was storing all the base configuration of the Analyzers to a database model (we did the same for all the other plugins types too). This allows us to manage plugins creation/modification/deletion in a more reliable manner and via the Django Admin Interface. If you have created custom plugins and changed those <plugins>_config.json file manually, you would need to re-create those custom plugins again from the Django Admin Interface. To do that please follow the related new documentation

  • We have REMOVED all the analyzers that we deprecated during the v4 releases cycle. Please substitute them with their respective new names, in case they have a replacement.

    • REMOVED Pulsedive_Active_IOC analyzer. Please substitute it with the new Pulsedive analyzer.

    • REMOVED Fortiguard analyzer because endpoint does not work anymore. No substitute.

    • REMOVED Rendertron analyzer not working as intended. No substitute.

    • REMOVED ThreatMiner, SecurityTrails and Robtex various analyzers and substituted with new versions.

    • REMOVED Doc_Info_Experimental. Its functionality (XLM Macro parsing) is moved to Doc_Info

    • REMOVED Strings_Info_Classic. Please use Strings_Info

    • REMOVED Strings_Info_ML. Please use Strings_Info and set the parameter rank_strings to True

    • REMOVED all Yara_Scan_<repo> analyzers. They all went merged in the single Yara analyzer

    • REMOVED Darksearch_Query analyzer because the service does not exist anymore. No substitute.

    • REMOVED UnpacMe_EXE_Unpacker. Please use UnpacMe

    • REMOVED BoxJS_Scan_JavaScript. Please use BoxJS

    • REMOVED all Anomali_Threatstream_<option> analyzers. Now we have a single Anomali_Threatstream analyzer. Use the parameters to select the specific API you need.

Updating to >=5.0.0 from a 3.x.x version

This is not supported. Please perform a major upgrade once at a time.

Updating to >=4.0.0 from a 3.x.x version

IntelOwl v4 introduced some major changes regarding the permission management, allowing an easier way to manage users and visibility. But that did break the previous available DB. So, to migrate to the new major version you would need to delete your DB. To do that, you would need to delete your volumes and start the application from scratch.

python3 start.py prod down -v

Please be aware that, while this can be an important effort to manage, the v4 IntelOwl provides an easier way to add, invite and manage users from the application itself. See the Organization section.

Updating to >=2.0.0 from a 1.x.x version

Users upgrading from previous versions need to manually move env_file_app, env_file_postgres and env_file_integrations files under the new docker directory.

Updating to >v1.3.x from any prior version

If you are updating to >v1.3.0 from any prior version, you need to execute a helper script so that the old data present in the database doesn’t break.

  1. Follow the above updation steps, once the docker containers are up and running execute the following in a new terminal

    docker exec -ti intelowl_uwsgi bash

    to get a shell session inside the IntelOwl’s container.

  2. Now just copy and paste the below command into this new session,

    curl https://gist.githubusercontent.com/Eshaan7/b111f887fa8b860c762aa38d99ec5482/raw/758517acf87f9b45bd22f06aee57251b1f3b1bbf/update_to_v1.3.0.py | python -

  3. If you see “Update successful!”, everything went fine and now you can enjoy the new features!