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data-privacy-stack/presidio · source
Snapshot 0 · 2026-11-04T12:47:25Z · Python · MIT
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b553970feb389eaa4cb4a09362ee1a5825e4844a63ea2a2d729c6fca18a140e0GitHub description at capture
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.
README at capture
# Presidio - Data Protection and De-identification SDK ## :mega: Presidio has moved to a new home! [Read more here](docs/project_transition.md) :mega: **Context aware, pluggable and customizable PII de-identification service for text and images.** --- [](https://github.com/data-privacy-stack/presidio/actions/workflows/ci.yml) [](http://opensource.org/licenses/MIT)  [](https://www.bestpractices.dev/projects/6076) [](https://pypi.python.org/pypi/presidio-analyzer/) [](https://discord.gg/MewtBGFquB) | Component | Downloads | Coverage | |-----------|-----------|----------| | Presidio Analyzer | [](https://pypi.python.org/pypi/presidio-analyzer/) | [](https://github.com/data-privacy-stack/presidio/tree/coverage-data-presidio-analyzer) | | Presidio Anonymizer | [](https://pypi.python.org/pypi/presidio-anonymizer/) | [](https://github.com/data-privacy-stack/presidio/tree/coverage-data-presidio-anonymizer) | | Presidio Image-Redactor | [](https://pypi.python.org/pypi/presidio-image-redactor/) | [](https://github.com/data-privacy-stack/presidio/tree/coverage-data-presidio-image-redactor) | | Presidio Structured | [](https://pypi.python.org/pypi/presidio-structured/) | [](https://github.com/data-privacy-stack/presidio/tree/coverage-data-presidio-structured) | ## What is Presidio Presidio _(Origin from Latin praesidium ‘protection, garrison’)_ helps to ensure sensitive data is properly managed and governed. It provides fast **_identification_** and **_anonymization_** modules for private entities in text such as credit card numbers, names, locations, social security numbers, bitcoin wallets, US phone numbers, financial data and more.  --- ### :blue_book: [Full documentation](https://data-privacy-stack.github.io/presidio) ### :mega: [Project transition update](docs/project_transition.md) ### :question: [Frequently Asked Questions](docs/faq.md) ### :thought_balloon: [Demo](https://huggingface.co/spaces/presidio/presidio_demo) ### :flight_departure: [Examples](https://data-privacy-stack.github.io/presidio/samples/) --- ### Goals - Allow organizations to preserve privacy in a simpler way by democratizing de-identification technologies and introducing transparency in decisions. - Embrace extensibility and customizability to a specific business need. - Facilitate both fully automated and semi-automated PII de-identification flows on multiple platforms. ### Main features 1. **Predefined** or **custom PII recognizers** leveraging _Named Entity Recognition_, _regular expressions_, _rule based logic_ and _checksum_ with relevant context in multiple languages. 2. Options for connecting to external PII detection models. 3. Multiple usage options, **from Python or PySpark workloads through Docker to Kubernetes**. 4. **Customizability** in PII identification and de-identification. 5. Module for **redacting PII text in images** (standard image types and DICOM medical images). :warning: Presidio can help identify sensitive/PII data in un/structured text. However, because it is using automated detection mechanisms, there is no guarantee that Presidio will find all sensitive information. Consequently, additional systems and protections should be employed. ## Installing Presidio 1. [Using pip](https://data-privacy-stack.github.io/presidio/installation/#using-pip) 2. [Using Docker](https://data-privacy-stack.github.io/presidio/installation/#using-docker) 3. [From source](https://data-privacy-stack.github.io/presidio/installation/#install-from-source) 4. [Migrating from V1 to V2](./docs/presidio_V2.md) ## Running Presidio 1. [Getting started](https://data-privacy-stack.github.io/presidio/getting_started) 2. [Setting up a development environment](https://data-privacy-stack.github.io/presidio/development) 3. [PII de-identification in text](https://data-privacy-stack.github.io/presidio/text_anonymization) 4. [PII de-identification in images](https://data-privacy-stack.github.io/presidio/image-redactor) 5. [Usage samples and example deployments](https://data-privacy-stack.github.io/presidio/samples) --- ## Support - Before you submit an issue, please go over the [documentation](https://data-privacy-stack.github.io/presidio/). - For general discussions, please use the [GitHub repo's discussion board](https://github.com/data-privacy-stack/presidio/discussions). - If you have a usage question, found a bug or have a suggestion for improvement, please file a [GitHub issue](https://github.com/data-privacy-stack/presidio/issues). - For other matters, please email [presidio@dataprivacystack.org](mailto:presidio@dataprivacystack.org). ## Contributing For details on contributing to this repository, see the [contributing guide](CONTRIBUTING.md). This project has adopted the [Contributor Covenant Code of Conduct](CODE_OF_CONDUCT.md). ## Contributors <!-- ALL-CONTRIBUTORS-LIST:START - Do not remove or modify this section --> <!-- prettier-ignore-start --> <!-- markdownlint-disable --> <!-- markdownlint-restore --> <!-- prettier-ignore-end --> <!-- ALL-CONTRIBUTORS-LIST:END --> <a href="https://github.com/data-privacy-stack/presidio/graphs/contributors"> <img src="https://contrib.rocks/image?repo=data-privacy-stack/presidio" /> </a>