> ## Documentation Index
> Fetch the complete documentation index at: https://docs.flexorch.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Masking

> Replace detected PII with placeholders using mask().

## Overview

`mask()` takes text and a list of PII findings, and returns the text with each finding replaced according to your chosen strategy.

***

## Basic usage

<CodeGroup>
  ```python Python theme={null}
  from flexorch_audit import detect_pii, mask

  text = "Email us at hello@example.com or call +49 30 1234567."

  findings = detect_pii(text)
  masked = mask(text, findings)

  print(masked)
  # Email us at [MASKED_EMAIL] or call [MASKED_PHONE_DE].
  ```

  ```javascript JavaScript theme={null}
  import { detectPii, mask } from '@flexorch/audit';

  const text = 'Email us at hello@example.com or call +49 30 1234567.';

  const findings = detectPii(text);
  const masked = mask(text, findings);

  console.log(masked);
  // Email us at [MASKED_EMAIL] or call [MASKED_PHONE_DE].
  ```
</CodeGroup>

***

## Strategies

| Strategy           | Example output     | Use case                    |
| ------------------ | ------------------ | --------------------------- |
| `redact` (default) | `[MASKED_EMAIL]`   | Production datasets         |
| `replace`          | `user@example.com` | Synthetic plausible data    |
| `token`            | `<EMAIL_1>`        | Structure-preserving NLP    |
| `hash`             | `a3f2b19c...`      | Deterministic anonymization |

<CodeGroup>
  ```python Python theme={null}
  masked = mask(text, findings, strategy="token")
  # Email us at <EMAIL_1> or call <PHONE_DE_1>.
  ```

  ```javascript JavaScript theme={null}
  const masked = mask(text, findings, { strategy: 'token' });
  ```
</CodeGroup>

***

## One-liner

Use `redact_for_llm()` to detect and mask in a single call — optimized for LLM input preparation:

<CodeGroup>
  ```python Python theme={null}
  from flexorch_audit import redact_for_llm

  clean_text, summary = redact_for_llm(text)
  print(clean_text)
  print(summary)  # {"count": 2, "types": ["email", "phone_de"]}
  ```

  ```javascript JavaScript theme={null}
  import { redactForLlm } from '@flexorch/audit';

  const { text: cleanText, summary } = await redactForLlm(text);
  ```
</CodeGroup>

See [redact\_for\_llm](/open-source/redact-for-llm) for full details.