An open-source framework for detecting, redacting, masking, and anonymizing sensitive data (PII) across text, images, and structured data. Supports NLP, pattern matching, and customizable pipelines.

Secure Vault for Customer PII/PHI/PCI/KYC Records

ARX is a comprehensive open source data anonymization tool aiming to provide scalability and usability. It supports various anonymization techniques, methods for analyzing data quality and re-identification risks and it supports well-known privacy models, such as k-anonymity, l-diversity, t-closeness and differential privacy.

Python Data Anonymization & Masking Library For Data Science Tasks

Filter sensitive information from free text before sending it to external services or APIs, such as chatbots and LLMs.

A PHP library to back up, restore and anonymize databases

HideDroid is an Android app that allows the per-app anonymization of collected personal data according to a privacy level chosen by the user.

This repository allows you to anonymize sensitive information in images/videos. The solution is fully compatible with the DL-based training/inference solutions that we already published/will publish for Object Detection and Semantic Segmentation.

Examples scripts that showcase how to use Private AI Text to de-identify, redact, hash, tokenize, mask and synthesize PII in text.

Deidentify people's names and gender specific pronouns

ANJANA is a Python library for anonymizing sensitive data

Maskwise detects, redacts, masks, and anonymizes sensitive data across text, images, and structured data in training datasets for LLM systems. Powered by Microsoft Presidio

Snaplet Documentation

Simple yet powerful tool for identifying and anonymizing personal information in various formats.

Library for identification, anonymization and de-anonymization of PII data

Cinnamon is a modular application designed to offer robust functionalities for data anonymization, synthetization, and evaluation.

🎓🔒 Creating, Analyzing and Testing Differential Privacy Protocols, aiming in Data Protection and Anonymization.

Differentially Private Synthetic Data Generation [DP-SDG] - Experimental Setups & Knowledge Base - WORK IN PROGRESS

Anonymize sensitive data in your datasets.

CSV fuzzer/anonymizer