{"categories":[{"label":"Security","url":"https://skillfed.io/packages/category/security"}],"enrichment":{"capability":"Detects personally identifiable information (PII) entities in text using regex, named entity recognition, and language models, with support for custom recognizers and multiple LLM providers.","skillfed_tags":["pii-detection","privacy-compliance","nlp"],"use_cases":["Scan customer support tickets or chat logs to identify and redact PII before storage or sharing.","Validate data pipelines to ensure sensitive information is not leaked in logs or exported datasets.","Build privacy-compliance workflows that detect PII in documents before they are processed or archived.","Extend with custom recognizers to detect domain-specific sensitive data (e.g., medical record numbers, financial account identifiers).","Deploy locally via Ollama for on-premise PII detection without sending text to external APIs."],"what_it_does":"Presidio Analyzer is a Python service that scans unstructured text to find and identify personally identifiable information (PII) such as phone numbers, email addresses, and other sensitive data. It comes with a set of predefined recognizers that use regex, spaCy-based named entity recognition, and other detection logic to identify PII entities. The package can be extended with custom recognizers for domain-specific or specialized PII types.\n\nThe analyzer supports both traditional pattern-based detection and modern language model-based approaches. For LLM-based detection, it integrates with Ollama (for local, privacy-preserving deployments) and Azure OpenAI (for cloud-based detection). The core engine loads a spaCy NLP model by default and orchestrates multiple recognizers to produce a comprehensive analysis of detected entities in a given text.","worth_installing":"Yes. Presidio Analyzer is actively maintained, has no known vulnerabilities, uses a permissive MIT license, and offers low-friction installation. It solves a concrete privacy problem with both out-of-the-box recognizers and extensibility for custom needs. The choice between pattern-based and LLM-based detection gives flexibility for different accuracy and privacy trade-offs."},"id":"presidio-analyzer","links":{"html":"https://skillfed.io/packages/presidio-analyzer","md":"https://skillfed.io/packages/presidio-analyzer.md","pypi":"https://pypi.org/project/presidio-analyzer/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-07-22","license_spdx":"MIT","license_treatment":"permissive","name":"presidio-analyzer","python_support":"supports_current","summary":"Presidio Analyzer package"},"popularity":{"monthly_downloads":6771284,"position":1852,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"2.2.364"}