# text.anonymize

Regex-based PII anonymization for plain text. Detects and
replaces personally-identifiable patterns with stable tokens
of the shape `⟦TYPE_N⟧`, and emits a JSON report describing
every redaction so a downstream verify step can audit
completeness.

## Capability

- `text.anonymize@0.1.0`

## Inputs

| Name           | Type | Description                                            |
| -------------- | ---- | ------------------------------------------------------ |
| `text`         | text | UTF-8 string to redact.                                |
| `custom_terms` | text | Optional. Newline-separated list of extra bare terms to redact whole-word (case-insensitive). |

## Outputs

| Name         | Type | Description                                                                                  |
| ------------ | ---- | -------------------------------------------------------------------------------------------- |
| `anonymized` | text | The input text with PII replaced by `⟦TYPE_N⟧` tokens.                                       |
| `report`     | json | `{ redactions: [{ type, token, original, offset }…], counts: { TYPE: n, … } }`.              |

## Categories detected

| Type            | Pattern                                                                |
| --------------- | ---------------------------------------------------------------------- |
| `EMAIL`         | RFC-5321-ish `local@domain`, IDN domains OK.                           |
| `PHONE`         | International (`+49 …`) or German national (`030 …`, `0151-…`) shape.  |
| `IBAN`          | Word-bounded `[A-Z]{2}\d{2}[A-Z0-9]{11,30}`. Structural only — checksum deliberately not computed. |
| `BIC`           | Word-bounded uppercase alnum, 8 or 11 chars.                           |
| `IPV4`          | Four 0..255 octets, dot-separated.                                     |
| `GERMAN_TAX_ID` | 11 consecutive digits, word-bounded.                                   |
| `CUSTOM`        | Every line of `custom_terms` matched whole-word, case-insensitive.     |

No NER yet. v0.2.0 will add a small ONNX model for name /
organisation detection once we have a benchmarked candidate.

## Permissions

None. Pure-Rust, regex-only, in-WASM. No filesystem, no network,
no LLM call.

## Example flow

```yaml
name: redact-case-file
inputs:
  document: bytes
steps:
  - id: extract
    use: text.extract@^0
    with:
      document: $inputs.document
  - id: redact
    use: text.anonymize@^0
    with:
      text: $extract.extracted.pages[*].text
      custom_terms: |
        Mustermann
        Musterfrau
outputs:
  redacted: $redact.anonymized
  audit_report: $redact.report
```

## Build

```bash
cargo build --release --target wasm32-wasip2
# Output: target/wasm32-wasip2/release/text_anonymize.wasm
```