Redaction Log De-Identification with anonym.plus

Clear PII from the log itself while each stated reason stays clear.

In simple terms, PII redaction is the on-device process of finding and masking personally identifiable information in a document before it is shared.

Redaction-log de-identification is the removal of personal data from the record that lists each cut and its ground. FRCP 26(b)(5)(A) requires a description of what was withheld and why. anonym.plus keeps that ground on every row while the names go.

When this applies

The log is the audit trail for the pass, so it names Bates ranges, reviewers, and often the very people you removed. A reason field that restates a masked value undoes the cut. An entry too thin to test invites a Rule 37(a) challenge.

How anonym.plus handles it

  1. Load the file into anonym.plus on your device.
  2. It scans the description and basis columns.
  3. The tool flags names and contacts in each entry.
  4. Confirm the flags; keep the stated basis for each cut.
  5. Replace or mask the confirmed PII.
  6. Save the clean record on your device.

What you need to provide

PII entity types detected

Categoryanonym.plus entity typeExample
NamesPERSONredacted-party name → [NAME]
Document IDsPERSONBates ABC-0099 → [DOC_ID]
DatesDATE_TIMEentry date → [DATE]
ContactEMAIL_ADDRESSentry email → [EMAIL]
IdentifiersUS_SSNSSN in basis → [SSN]
NamesPERSONreviewer name → [REVIEWER]

Compliance achieved

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Limitations & cautions

Each entry must still justify its cut. Mask names in the rows, but keep the stated basis, or the file loses its purpose. Confirm that masking does not make two different cuts look identical.

Frequently asked questions

Do the rules require a log for content cuts?

Rule 26(b)(5)(A) is written for privilege claims. Courts and ESI protocols routinely ask for the same detail on content cuts, since the other side cannot test what it cannot see. Check your protocol before you fix the format.

How can the log itself leak?

Its description field explains why a value came out, and the shortest explanation is often the value. Mask the names in each row and describe the category instead.

Does it read spreadsheet versions?

Yes. XLSX and CSV files are supported, plus DOCX and PDF versions.