Open-source reference implementations for AI-enabled payment security, blockchain fraud detection, and AML/CFT compliance reasoning.

Synthetic fraud graph generator for benchmarking graph-based fraud detection models in financial services.

API for OpenSanctions with support for entity search and bulk matching of data collections. Supports Reconciliation API spec.

Template for getting started with automated ML Ops on Azure Machine Learning

Data model and processing tools for investigative entity graphs. Used by OpenSanctions, OpenAleph and dozens of other fincrime tools.

Burp Suite Extension for LLM Prompt Injection Testing

GitHub Action that allows you to deploy machine learning models in Azure Machine Learning.

GitHub Action that allows you to submit a run to your Azure Machine Learning Workspace.

GitHub Action that allows you to create or connect to your Azure Machine Learning Workspace.

[Usenix Security '25] Robustifying ML-powered Network Classifiers with PANTS

GitHub Action that allows you to attach, create and scale Azure Machine Learning compute resources.

GitHub Action that allows you to register models to your Azure Machine Learning Workspace.

Tensorflow implementation for the ECCV20 paper "Improving Adversarial Robustness by Enforcing Local and Global Compactness"

OFAC List for blockchains

A Multi-Agent RAG platform using Vector DBs and AI models to accurately answer AML/CFT compliance queries.

The Python SDK for interacting with the Yoti Platform

We use machine learning and graph algorithms to analyze the attributes of TRON addresses with the goal of assisting in the tracking of illicit funds.

This repo demonstrates a bank’s transaction clearing process, utilizing generative AI for real-time fraud detection and AML compliance, enhancing the detection of evolving fraudulent techniques.

Privacy-first institutional asset tokenization designed to automate regulatory compliance and auditing while preserving strong client confidentiality.

Azure Machine Learning - MLOps Python SDKv2