# Consistent Pseudonym Text Anonymizer

Detect common PII in text and replace repeated entities with stable, auditable pseudonyms without sending the text to a model.

> Canonical page: https://elysiatools.com/en/tools/consistent-pseudonym-text-anonymizer

- **Category:** Text Processing

- **Keywords:** text anonymization, pseudonymization, PII, consistent replacement, privacy, redaction, stable mapping

## Overview

Consistent Pseudonym Text Anonymizer detects selected common PII in pasted text and replaces repeated entities with stable labels, synthetic placeholders, or deterministic hashes. It returns anonymized text and JSON details such as the unique entity count.

## Inputs

- **Text Content** (textarea): Paste text or logs containing repeated entities...
- **Entity Types** (select)
- **Replacement Mode** (select)
- **Include Mapping** (checkbox)
- **Mapping Seed** (text): Optional deterministic seed

## When to use

- Anonymize logs, notes, or text containing repeated email addresses, phone numbers, IP addresses, or other supported identifiers.
- Share sanitized text while preserving consistency for the same entity throughout the content.
- Create repeatable pseudonyms with a mapping seed when deterministic replacements are needed.

## How it works

- Paste text containing the entities you want to anonymize into Text Content.
- Select one or more entity types, such as email addresses, phone numbers, IPv4 addresses, API keys, or names after name labels.
- Choose Stable Labels, Synthetic Placeholders, or Deterministic Hashes as the replacement mode.
- Optionally include the entity mapping and provide a mapping seed for deterministic results, then receive the anonymized text as JSON.

## Use cases

- Sanitizing application logs before sharing them with a support or engineering team.
- Preparing privacy-conscious datasets or text samples while preserving repeated-entity relationships.
- Replacing contact details and identifiers in test documents with stable labels or hashes.

## Frequently asked questions

### What types of information can the tool detect?

It can detect email addresses, phone numbers, IPv4 addresses, credit card numbers, API keys and tokens, national ID cards, passport numbers, and names after name labels.

### Are repeated entities replaced consistently?

Yes. The same detected entity receives the same pseudonym throughout the text.

### Which replacement modes are available?

You can use stable labels, synthetic placeholders, or deterministic hashes.

### Can I receive the replacement mapping?

Yes. Enable Include Mapping to request the mapping in the JSON result.

### What does the Mapping Seed do?

The optional seed supports deterministic pseudonym generation, so the same input settings can produce repeatable replacements.

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## Samples

- [Text with Emoji Samples](https://elysiatools.com/en/samples/text-with-emoji-samples): Mixed language text containing various Unicode emojis for testing emoji extraction
- [Text with Sensitive Data Samples](https://elysiatools.com/en/samples/text-with-sensitive-data-samples): Text containing various types of sensitive data for testing data masking (phones, emails, ID cards, bank cards)
- [Chinese-English Mixed Text Samples](https://elysiatools.com/en/samples/text-chinese-english-mixed-samples): Sample text files with mixed Chinese and English content for testing automatic spacing tools
- [Text Case Format Samples](https://elysiatools.com/en/samples/text-case-formats): Examples of different text case formats: camelCase, snake_case, kebab-case, PascalCase, and more