presidio open source analysis

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.

Project overview

⭐ 6547 · Python · Last activity on GitHub: 2026-01-05

GitHub: https://github.com/microsoft/presidio

Why it matters for engineering teams

Presidio addresses the critical need for detecting and anonymising sensitive data such as personally identifiable information (PII) in text, images, and structured formats. This open source tool for engineering teams is particularly suited to machine learning and AI engineering roles focused on data privacy and compliance. It offers a production ready solution with mature support for NLP, pattern matching, and customisable pipelines, making it reliable for real-world applications. However, it may not be the right choice for teams requiring extensive out-of-the-box support for less common data types or those looking for a fully managed service rather than a self hosted option for data anonymisation.

When to use this project

Presidio is a strong choice when teams need a flexible, self hosted option for anonymising sensitive data across multiple formats with customisable detection pipelines. Teams should consider alternatives if they require a turnkey SaaS solution or need specialised support for niche data types beyond text and images.

Team fit and typical use cases

Machine learning and AI engineers benefit most from Presidio by integrating it into data pipelines to ensure privacy compliance before model training or deployment. It is commonly used in products handling sensitive customer data, such as healthcare or finance applications, where automated data masking and redaction are essential. This production ready solution helps teams maintain data privacy without sacrificing control over their data processing workflows.

Best suited for

Topics and ecosystem

anonymization data-anonymization data-masking data-obfuscation data-privacy data-redaction de-identification guardrails image-redactor named-entity-recognition nlp personally-identifiable-information phi pii pii-detection privacy python sensitive-data spacy transformers

Activity and freshness

Latest commit on GitHub: 2026-01-05. Activity data is based on repeated RepoPi snapshots of the GitHub repository. It gives a quick, factual view of how alive the project is.