Presidio
Detect and anonymize PII in text, images, and structured data - through redaction, masking, replacement, encryption, and synthetic surrogates.
Data Privacy Stack
Open, transparent tools for private data handling
- PII detection
- Redaction
- De-identification
- Multi-language
- Open source
Our mission is to democratize privacy technology - putting open, transparent tools for protecting sensitive data within everyone's reach, and strengthening the privacy and security of individuals and organizations alike.
The Data Privacy Stack is a community-led home for open, transparent tools that help engineers handle private data responsibly - starting with Presidio for PII detection and anonymization, with room to grow.
Guiding principles
Open
Permissively licensed, community-driven, and developed in the open.
Transparent
Clear about what's detected, how, and why - no black boxes.
Composable
Independent building blocks you can adopt one piece at a time.
Projects
More coming
The stack is growing. Want to propose or contribute a project? Get involved →
Runs where you work
From a Python import to Docker and Kubernetes - drop the stack into the tools and pipelines you already use.
Governance
The Data Privacy Stack follows a Minimum Viable Governance (MVG) model - a lightweight, two-tier structure that puts clear, consensus-based governance in place without heavyweight overhead.
Technical Steering Committee
At the organization level, the TSC sets overall direction and coordinates across projects - technical roadmap, maintainer appointments, and governance policy.
Project Maintainers
Each project is run by its maintainers through a lightweight, consensus-based process - reviewing contributions and keeping the project secure, maintained, and modern.
The authoritative governance documents - charter, code of conduct, steering committee, and per-project governance - live in the MVG repository.
Blog
News, releases, and notes from the community.
- The Presidio Project Joins Data Privacy Stack Presidio begins its next chapter under Data Privacy Stack, an independent, community-driven organization for private data handling.
- Evaluating PII Detection Models: A Field Guide Why a single accuracy number can be misleading when you choose a PII detection model - and how to evaluate one properly.
- Welcome to the Data Privacy Stack A community home for open, transparent tools for private data handling.
Community
Contributions of all sizes are welcome - code, documentation, bug reports, feature ideas, and reviews. Development happens in the open across the Data Privacy Stack organization.
Report or request
Open an issue in the relevant project repository to report a bug or request a feature.
Contribute code
Pick up an open issue or propose a change. Presidio is developed at
data-privacy-stack/presidio; see its
CONTRIBUTING.md.
Shape the direction
Join the discussion, share use cases, and help set the roadmap under open governance.