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4. PII detection and redaction

Redact on the way in, restore on the way out, log neither.

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Send the minimum personal data a task requires. A practical pattern is tokenised redaction: replace entities with placeholders before the model call and restore them afterwards, so the model never sees raw identifiers but the user still gets a natural answer.

ts
function redact(text: string) {
  const map = new Map<string, string>();
  let i = 0;
  const out = text
    .replace(/[\w.+-]+@[\w-]+\.[\w.]+/g, (m) => tok("EMAIL", m))
    .replace(/\b(?:\d[ -]?){13,16}\b/g, (m) => tok("CARD", m))
    .replace(/\b0x[a-fA-F0-9]{40}\b/g, (m) => tok("ADDR", m));
  function tok(kind: string, value: string) {
    const t = `[${kind}_${i++}]`;
    map.set(t, value);
    return t;
  }
  return { text: out, restore: (s: string) => [...map].reduce((a, [t, v]) => a.split(t).join(v), s) };
}

Regexes catch structured identifiers; names and addresses need an NER model. Also: disable provider training on your data, set retention to the minimum, exclude prompt bodies from application logs, and keep a deletion path for stored memories.

Exercise: add redaction to a support-ticket summariser and confirm from the request log that no raw email address or card number ever leaves your service.

How to study this topic

1. Read the explanation once end to end, skipping the code.
2. Re-read the code snippets and say out loud what each line does.
3. Answer the quiz without scrolling back — that is the real check.
4. Read every explanation, even for the answers you got right.

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Check your understanding

1. What does tokenised redaction achieve?
The model never sees raw identifiers while answers stay naturalIt compresses promptsIt removes the need for consentIt speeds up inference
2. Which PII needs more than regex detection?
Person names and street addressesEmail addressesCredit card numbersEthereum addresses

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