Operation BONANZA

Overview

Operation BONANZA is a fictional law enforcement investigation designed to demonstrate how Elasticsearch can be used for criminal intelligence, digital forensics and OSINT analysis in complex organised crime cases.

⚠️ DISCLAIMER: This is entirely fictional content created for educational and demonstration purposes only. All names, locations, and criminal activities are fabricated.

Purpose

This repository showcases how modern search and analytics technologies can assist law enforcement agencies in:

• Intelligence Analysis: Connecting disparate data points across multiple sources
• Digital Forensics: Analysing communications data and financial transactions

Fictional Scenario

Operation BONANZA targets a sophisticated organised crime group involved in firearms trafficking, featuring:

• Multi-tier criminal organisation with leadership, operational, and distribution levels
• Complex money laundering operations through legitimate businesses
• International supply chains and corrupt officials
• Digital communications evidence and financial intelligence

Repository Structure

operation-bonanza/
├── data/
│   ├── intel-reports/         # Criminal intelligence reports (NDJSON)
│   └── df/                   # Digital forensics extracts
│       └── messages/         # Message threads from seized devices
├── elasticsearch/
│   ├── indices/              # Index mappings and settings
│   └── pipelines/            # Ingest pipeline configurations
├── notebooks/                # Jupyter notebooks for data analysis
│   └── ingest_data_elasticsearch.ipynb  # Data ingestion tutorial
├── requirements.txt          # Python dependencies
├── pyproject.toml           # Project configuration
├── uv.lock                  # Dependency lock file
└── .env.example             # Environment variables template

Key Features Demonstrated

Sample Datasets Included

Sample Queries

Getting Started

Prerequisites

• Elasticsearch 8.x deployment (Cloud or self-hosted)
• Python 3.12+ with uv package manager
• Jupyter Notebook environment

Quick Setup

# Clone the repository
git clone https://github.com/face0b1101/operation-bonanza.git
cd operation-bonanza

# Install Python dependencies
uv sync

# Set up environment variables
cp .env.example .env
# Edit .env with your Elasticsearch credentials

# Start Jupyter and run the ingestion notebook
uv run jupyter lab
# Open notebooks/ingest_data_elasticsearch.ipynb

Environment Configuration

Create a .env file with your Elasticsearch settings:

ES_CLOUD_ID=your_cloud_id_here
ES_API_KEY=your_api_key_here
ES_CLOUD_URL=your_elasticsearch_url

Use Cases Demonstrated

Educational Value

Technical Architecture

Contributing

This is an educational project demonstrating Elasticsearch capabilities for law enforcement intelligence analysis. Contributions that enhance the demonstration are welcome:

• Additional realistic datasets
• New analytical queries and search patterns
• Enhanced data processing pipelines
• Documentation improvements and use case examples

Please ensure all contributions maintain the fictional nature of the dataset and follow the established data structure patterns.

Licence

This project is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0).

What this means:

• ✅ Educational Use: Free to use for academic research, training, and educational purposes
• ✅ Attribution Required: Must credit the original work when used
• ❌ No Commercial Use: Cannot be used for commercial demos, products, or services without permission
• ❌ No Derivatives: Cannot modify or build upon the datasets without permission

For Commercial Use

If you're interested in using these datasets for commercial purposes (demos, products, consulting), please raise an issue wiht your request.

All content is fictional and created solely for educational and demonstration purposes.

Acknowledgements

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Remember: This is entirely fictional content. Any resemblance to real persons, organisations, or investigations is purely coincidental.