Taranis AI: A Cutting-Edge OSINT Tool Leveraging AI for Advanced Information Gathering and Situational Analysis

GitHub: https://github.com/taranis-ai/taranis-ai
Last Commit: September 6th, 2024

Taranis AI is an advanced Open-Source Intelligence (OSINT) tool, leveraging Artificial Intelligence to revolutionize information gathering and situational analysis.

Taranis navigates through diverse data sources like websites to collect unstructured news articles, utilizing Natural Language Processing and Artificial Intelligence to enhance content quality. Analysts then refine these AI-augmented articles into structured reports that serve as the foundation for deliverables such as PDF files, which are ultimately published.

Getting Started

For production deployments see our Deployment Guide using docker compose

For Development read our Dev Setup Guide

Documentation

See ADVANCED OSINT ANALYSIS FOR NIS AUTHORITIES, CSIRT TEAMS AND ORGANISATIONS for a presentation about the current features.

See taranis.ai for documentation of user stories and deployment guides.

Services

Type	Name	Description
Backend	core	Backend for communication with the Database and offering REST Endpoints to workers and frontend
Frontend	gui	Vuejs3 based Frontend
Worker	worker	Celery Worker offering collectors, bots, presenters and publisher features
Worker	beat	Celery Beat instance for scheduling tasks

Support services

Type	Name	Description
Database	database	Supported are PostgreSQL and SQLite with PostgreSQL as our primary citizen
Message-broker	rabbitmq	Message Broker for distribution of Workers and Publish Subscribe Queue Management
SSE	sse	SSE Broker

Features

Advanced OSINT Capabilities: Taranis AI scours multiple data sources, such as websites, for unstructured news articles, providing a comprehensive intelligence feed.
AI-Enhanced Analysis: Utilizes Artificial Intelligence and Natural Language Processing to automatically enhance and enrich collected articles for higher content quality.
Analyst-Friendly Workflow: Offers a streamlined process where analysts can easily convert unstructured news into structured report items, optimizing the data transformation journey.
Multi-Format Output: Generates a variety of end products, including structured reports and PDF files, tailored to specific informational needs.
Seamless Publishing: Facilitates the effortless publication of finalized intelligence products, ensuring timely dissemination of critical information.

OpenAPI

An OpenAPI spec for the REST API is included and can be accessed in a running installation under config/openapi.

Hardware requirements

To use all NLP features make sure to have at least: 16 GB RAM, 4 CPU cores and 50GB of disk storage.

Without NLP: 2 GB of RAM, 2 CPU cores and 20 GB of disk storage

Directory structure

src/ - Taranis AI source code:
- Core is the REST API, the central component of Taranis AI
- GUI is the web user interface
- Worker retrieve OSINT information from various sources (such as web, twitter, email, atom, rss, slack, and more) and create news items.
docker/ - Support files for Docker image creation and example docker-compose file