Skip to content

Integration examples and documentation for Sonotheia voice fraud detection API - deepfake detection, MFA, and SAR generation.

License

Notifications You must be signed in to change notification settings

doronpers/sonotheia-examples

Folders and files

NameName
Last commit message
Last commit date

Latest commit

Β 

History

198 Commits
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 

Repository files navigation

Sonotheia Examples

Unified showcase repository for the Sono Platform's commercial voice fraud mitigation capabilities

License: MIT Python 3.9+ Python 3.11+ (Evaluation) Node.js 18+ TypeScript

⚠️ Active Development: This repository and all components are in active development. Examples and frameworks are being refined, APIs may change, and features are continuously being added.

This monorepo combines two complementary showcase components for the Sono Platform:

  • Integration Examples - Integration examples for the Sonotheia API (in active development)
  • Evaluation Framework - Research and evaluation tool for testing acoustic indicator robustness (in active development)

What's This?

This repository demonstrates the commercial voice fraud mitigation direction for the Sono Platform through:

  1. Production Integration (examples/) - Real-world integration patterns and code examples
  2. Evaluation & Research (evaluation/) - Stress-testing framework for indicator robustness

Both components work together to showcase:

  • How to integrate Sono Platform in production environments
  • How to evaluate and validate detection systems
  • Best practices for voice fraud mitigation workflows

πŸš€ Golden Path Demo (Start Here)

Run a complete end-to-end workflow in minutesβ€”no API key required for mock mode.

The Golden Path demo shows the complete Sonotheia workflow: deepfake detection β†’ voice MFA verification β†’ routing decision β†’ optional SAR submission.

Quick Start (Mock Mode - No API Key)

Python:

cd examples/python
python -m venv .venv && source .venv/bin/activate
pip install -r requirements.txt

# Start mock server (in one terminal)
python mock_api_server.py

# Run golden path demo (in another terminal)
python golden_path_demo.py ../test-audio/clean_tone.wav --mock

TypeScript:

cd examples/typescript
npm install && npm run build

# Start mock server (Python, in one terminal)
cd ../python && python mock_api_server.py

# Run golden path demo (in another terminal)
cd ../typescript
npm run golden-path -- ../test-audio/clean_tone.wav --mock

Real API Mode (Requires API Key)

# Python
export SONOTHEIA_API_KEY=your_key
python golden_path_demo.py audio.wav

# TypeScript
export SONOTHEIA_API_KEY=your_key
npm run golden-path -- audio.wav

πŸ“– Showcase Quickstart Guide - Complete guide with all modes and troubleshooting


Governance & Interpretation (Read This First)

⚠️ Important: Outputs are suggestive signals, not identity proofs. Results should be interpreted within the context of your security workflow and used as part of a broader decision-making process.

Before integrating or evaluating, please review:

πŸ“– How to Interpret Results - Comprehensive guide on understanding outputs, confidence bounds, and proper usage


Repository Structure

sonotheia-examples/
β”œβ”€β”€ examples/                # Integration Examples - Production patterns
β”‚   β”œβ”€β”€ README.md           # Integration examples documentation
β”‚   β”œβ”€β”€ curl/               # cURL examples
β”‚   β”œβ”€β”€ python/             # Python client examples
β”‚   β”œβ”€β”€ typescript/         # TypeScript examples
β”‚   └── node/               # Node.js examples
β”‚
β”œβ”€β”€ evaluation/              # Audio Trust Harness - Research framework
β”‚   β”œβ”€β”€ README.md           # Evaluation framework documentation
β”‚   β”œβ”€β”€ src/                # Source code
β”‚   β”œβ”€β”€ tests/              # Test suite
β”‚   └── config/             # Configuration files
β”‚
└── documentation/           # Shared documentation
    β”œβ”€β”€ GETTING_STARTED.md  # Quick start guide
    └── ...

Quick Start

New to Sonotheia? Start with the Golden Path Demo above for a complete workflow in minutes.

First time setup? See Launch & Onboarding Guide for cross-platform setup instructions (Windows & macOS).

Looking for detailed guides? See documentation/START_HERE.md

For Production Integration

If you want to integrate Sono Platform into your application:

# Python example
cd examples/python
pip install -r requirements.txt
export SONOTHEIA_API_KEY=your_key
python main.py audio.wav

# TypeScript example
cd examples/typescript
npm install && npm run build
export SONOTHEIA_API_KEY=your_key
node dist/index.js audio.wav

πŸ“– Integration Examples Guide

For Evaluation & Research

If you want to stress-test acoustic indicators and evaluate robustness:

cd evaluation
python -m venv venv && source venv/bin/activate
pip install -e ".[dev]"
python -m audio_trust_harness run --audio test.wav --out audit.jsonl

πŸ“– Evaluation Framework Guide


Components

Integration Examples (examples/)

Sonotheia Examples - Production-ready integration examples for the Sonotheia API.

Key Features:

  • Multi-language support (cURL, Python, TypeScript, Node.js)
  • Production patterns (retry logic, rate limiting, circuit breakers)
  • Evaluation tools and testing harnesses
  • Comprehensive documentation

Use Cases:

  • Voice-based multi-factor authentication (MFA)
  • Synthetic speech detection
  • Suspicious Activity Report (SAR) generation
  • Production integration patterns

πŸ“– Full Documentation


Evaluation Framework (evaluation/)

Audio Trust Harness - A research and evaluation framework for testing acoustic indicator robustness under adversarial perturbations.

Key Features:

  • Stress-test indicators with controlled transformations
  • Measure stability across perturbations
  • Generate deferral signals for human review
  • Produce complete audit trails

Use Cases:

  • Research & evaluation of new indicators
  • Validation of indicator stability
  • Quality assurance for content moderation
  • Indicator development and benchmarking

πŸ“– Full Documentation


Architecture

Both components showcase different aspects of the Sono Platform:

β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
β”‚              Sono Platform (Production)                 β”‚
β”‚  https://github.com/doronpers/sono-platform            β”‚
β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜
                        β–²
                        β”‚
        β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”΄β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
        β”‚                                 β”‚
β”Œβ”€β”€β”€β”€β”€β”€β”€β–Όβ”€β”€β”€β”€β”€β”€β”€β”€β”            β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β–Όβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
β”‚  Integration   β”‚            β”‚   Evaluation        β”‚
β”‚  Examples       β”‚            β”‚   Framework        β”‚
β”‚                 β”‚            β”‚                     β”‚
β”‚ β€’ API clients   β”‚            β”‚ β€’ Stress-test       β”‚
β”‚ β€’ MFA workflows β”‚            β”‚ β€’ Robustness        β”‚
β”‚ β€’ SAR generationβ”‚            β”‚ β€’ Validation        β”‚
β”‚ β€’ Production    β”‚            β”‚ β€’ Research          β”‚
β”‚   patterns      β”‚            β”‚                     β”‚
β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜            β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜

Documentation

Getting Started

Guides

Reference


Contributing

We welcome contributions. Please see:


License

This repository is licensed under the MIT License - see the LICENSE file for details.

Note: This license applies to the showcase code and documentation. Access to the Sono Platform service requires separate authorization.


How This Repository Reflects Sonotheia's Approach

This repository embodies Sonotheia's core philosophy: attackers optimize for what sounds convincing, not what is physically or system-consistent. Sounding real is not the same as being physically or system-consistent. Our goal is measurably safer decisionsβ€”fewer exceptions, fewer bypasses, fewer successful fraud events.

The examples and evaluation framework here demonstrate how to:

  • Use acoustic indicators as signals within broader security workflows
  • Apply confidence bounds and reason codes appropriately
  • Leverage deferral mechanisms as a control mechanism
  • Avoid prohibited uses (e.g., treating signals as identity proofs)

This aligns with Sonotheia's commitment to transparency, proper interpretation, and measurable security outcomes rather than perfect detection claims.


Related Resources


Support


Built with ❀️ for secure voice authentication and fraud mitigation

Integration Examples β€’ Evaluation Framework β€’ Documentation β€’ Contributing β€’ License

About

Integration examples and documentation for Sonotheia voice fraud detection API - deepfake detection, MFA, and SAR generation.

Topics

Resources

License

Contributing

Security policy

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Contributors 5