data-privacy-stack/presidio
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. observed · 2026-08-28
Health v2 · maintenance only
93/100
- Activity 99
- Release rhythm 82
- Longevity 100
Flags: no_readme
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: 60.5
- age_days: 3043
- days_rel: 42
- days_push: 7
- n_releases_24m: 9
Adoption not part of the score
10644 stars · 1261 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded
Presidio is an open-source Python SDK for detecting, redacting, masking, and anonymizing sensitive data (PII) in text, images, and structured/semi-structured data. It combines NLP-based named entity recognition, regex, rule-based logic, and checksum validation in customizable pipelines, with modules for analysis, anonymization, image redaction, and structured data.
Use cases
- redact PII from customer support transcripts
- anonymize sensitive data in text before sharing with third parties
- mask credit card numbers and SSNs in logs
- remove personally identifiable information from images
- de-identify PHI in healthcare records
- detect PII in structured/tabular datasets
- build GDPR/CCPA data privacy compliance pipelines
When to choose
- you need customizable, self-hosted PII detection and anonymization in Python
- you want to combine NLP models (spaCy, transformers, stanza) with rule-based recognizers
- you need to redact PII from text, images, and structured data with one toolkit
- you want a library/SDK you can embed in pipelines rather than a managed cloud service
When to avoid
- you need a guaranteed complete detection of all sensitive data - automated detection is not exhaustive
- you want a fully managed PII detection service without customization effort
- you need languages or entity types not covered by available recognizers without building custom ones
Facets
library · maturity active
nlp security privacy ocr machine-learning sdk privacy security data-science developer-tools python cross-platform cli pii-detection data-anonymization de-identification data-masking ner spacy transformers image-redaction gdpr-compliance phi natural-language-processing docker kubernetes
4 sources
- homepage: https://presidio.dataprivacystack.org · fetched 2026-08-29 · a7721f700b30
- site_page: https://presidio.dataprivacystack.org/installation · fetched 2026-08-29 · b85e83b7f97c
- registry_pypi: https://pypi.org/pypi/presidio/json · fetched 2026-08-29 · c1eea7a735be
- site_page: https://presidio.dataprivacystack.org/faq · fetched 2026-08-29 · 22e9a17f7bda
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| data-privacy-stack/presidio | main | 93 |
For agents
markdown · JSON · MCP: product_card(name="data-privacy-stack/presidio")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem