Tirreno User Guide
=============================================

.. _overview:

.. index::
    single: Overview

Overview
========

.. epigraph::

   *“The art of war teaches us to rely not on the likelihood of the
   enemy’s not coming, but on our own readiness to receive him; not on
   the chance of his not attacking, but rather on the fact that we have
   made our position unassailable.”*

   — Sun Tzu, The Art of War

:tirreno:`Tirreno` is an open-source platform for preventing fraud,
account takeovers, and abuse.

In order to achieve the declared objective, :tirreno:`Tirreno` collects
intelligence to detect signals related to user identity and behaviour.
This solution enables a detailed investigation of anomalies and a manual
review of complex fraudulent patterns. It helps to maintain
non-interrupted services and protect private information.

:tirreno:`Tirreno` brings enterprise-level fraud prevention
techniques to a wide variety of digital platforms and businesses.
It is developed for platforms with a demand for utmost control
or for integration into a complex defence system, facilitating
risk assessment during user onboarding.

:tirreno:`Tirreno` comes in two versions:

Community
    An open-source solution for preventing fraud, account takeovers,
    and abuse. It is available for free on `GitHub
    <https://github.com/TirrenoTechnologies/tirreno>`_.

Enterprise
    A commercially licensed product offering extended risk management
    capabilities via the :tirreno:`Tirreno` :term:`Enrichment API`.

.. _privacy:

.. index::
    single: Privacy

Privacy
-------

By saying that :tirreno:`Tirreno` is an ethical tool, we highlight our
commitment to not crossing a thin line between taking mandatory actions
for fraud prevention and breaking user privacy.

In fact, :tirreno:`Tirreno` does not use cookies or browser
fingerprinting and does not expose more user data than is strictly
necessary.

User data is safe with us. We do not share it with third parties and
follow data retention policies. Full control over data and its security
is exercised by a hosting platform.

.. index::
    single: System Workflow

.. _system-workflow:

System Workflow
---------------

The :tirreno:`Tirreno`’s workflow consists of the following main parts:

1. Gathering of user request data.
2. Enrichment and management of the collected data.
3. Machine-led data processing.
4. Manual review of the processed data.

In the next subsections, we briefly describe each of these stages. When
applicable, materials covering the subject more fully are linked.

.. index::
    single: Data Collection

.. _data-collection:

Data Collection
~~~~~~~~~~~~~~~

This stage is an entry point to :tirreno:`Tirreno` setup and further
usage. It requires the installation of a lightweight script for sending
user request data to :tirreno:`Tirreno`. And this is the *only*
requirement for :tirreno:`Tirreno` to start operating!

For more information on this, see :ref:`API Integration
<api-integration>`.

.. index::
    single: Data Enrichment

.. _data-enrichment:

Data Enrichment
~~~~~~~~~~~~~~~

A perceived magic 🪄 is happening during this stage: raw pieces of data
are carefully prepared and then intermingled with the
:tirreno:`Tirreno`’s internal as well as external proprietary and
open-sourced data.

.. index::
    single: Machine Processing

.. _machine-processing:

Machine Processing
~~~~~~~~~~~~~~~~~~

This is the backbone of the :tirreno:`Tirreno` background workings. Each
user request data is processed through a set of specific conditions
(:term:`rules<rule>`). During this stage, the :term:`rules engine`
detects irregularities and suspicious activities. The received results
define the calculated :term:`user score<trust score>`, which is a
determinative characteristic to consider at the stage of manual review.

For more details, see the :ref:`Rules <rules>` section.

.. index::
    single: Manual Review

.. _manual-review:

Manual Review
~~~~~~~~~~~~~

:tirreno:`Tirreno` outputs the accumulated knowledge base via a
web-accessible user interface. The interface is designed to be a
convenient tool for human-led investigation of the machine-preprocessed
data analytics. It provides varying ways to proceed with investigation
and can thus be flexibly adapted to different workflows and
undertakings.

For a description of all the capabilities provided, advance to the
chapters :ref:`Console <console>` and :ref:`Operator Procedures
<operator-procedures>`.

.. toctree::
   :hidden:
   :caption: User Guide

   getting-started
   installation
   api-integration
   console
   operator-procedures
   tutorials
   glossary
   genindex