presidio README

The project's README from github.com/data-privacy-stack/presidio. As one markdown file: README.md.

Presidio - Data Protection and De-identification SDK

:mega: Presidio is moving to a new home! Read more here :mega:

Context aware, pluggable and customizable PII de-identification service for text and images.


Build Status MIT license Release OpenSSF Best Practices PyPI pyversions Discord

Component Downloads Coverage
Presidio Analyzer Pypi Downloads Coverage
Presidio Anonymizer Pypi Downloads Coverage
Presidio Image-Redactor Pypi Downloads Coverage
Presidio Structured Pypi Downloads Coverage

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.

Presidio demo gif


:blue_book: Full documentation

:mega: Project transition update

:question: Frequently Asked Questions

:thought_balloon: Demo

:flight_departure: Examples


Goals

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
  2. Using Docker
  3. From source
  4. Migrating from V1 to V2

Running Presidio

  1. Getting started
  2. Setting up a development environment
  3. PII de-identification in text
  4. PII de-identification in images
  5. Usage samples and example deployments

Support

Contributing

For details on contributing to this repository, see the contributing guide.

This project has adopted the Contributor Covenant Code of Conduct.

Contributors

presidio (data-privacy-stack/presidio)

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11.4K ·GitHub
这是什么?一个开源框架(SDK),用于在文本、图片和结构化数据中检测并去除敏感信息(PII)——比如姓名、信用卡号、社保号、电话号码——支持删除、打码和匿名化处理。
Presidio 是导入代码里用的库,还是需要部署的服务?两者都是:它以 Python 包的形式提供,可以直接导入自己的代码使用;同样的组件也可以用 Docker 容器或 Kubernetes 来运行。
怎么把它加到我的项目里?可以用 pip 安装这些 Python 包,也可以运行官方提供的 Docker 镜像,或者从源码构建;文档里有 Getting started 入门指南,文本和图片的去标识化都有覆盖。
我需要自己准备机器学习模型吗,还是开箱就能用?检测由预置的或自定义的识别器(recognizer)完成:包括 NER(spaCy、Transformers)、正则表达式、基于规则的逻辑和校验和。也可以接入外部的 PII 检测模型。
它能保证把所有敏感数据都找出来吗?不能——它依靠自动检测,无法保证找出全部敏感信息;作者建议在使用它的同时,配合其他系统和防护措施。
开箱就能检测哪些内容?预置的识别器覆盖姓名、地点、信用卡号、社保号、美国电话号码、比特币钱包、金融数据等;还可以添加自定义识别器,来检测特定领域的实体。
这个项目由哪些部分组成?四个模块:Analyzer(找出 PII)、Anonymizer(在文本中删除或打码)、Image Redactor(处理普通图片和 DICOM 医学影像)以及 Presidio Structured(处理结构化数据)。
除了英文,还支持其他语言吗?支持——识别器结合多种语言的相关上下文,使用 NER、正则表达式和基于规则的逻辑,所以检测并不局限于英文。
Presidio 这个名字是什么意思?它来自拉丁语 praesidium,意思是保护或驻防,呼应了它守护敏感数据的目标。
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