Anonymize CCPA right-to-correct request records for compliance documentation – CCPA/HIPAA-compliant de-identification per Cal. Civ. Code §1798.106

CCPA §1798.106, added by the 2023 CPRA amendments, gives California consumers the right to correct inaccurate personal information. Correction-request records contain both the inaccurate data asserted by the consumer and the corrected version, creating dual personal-data exposure. anonym.legal pseudonymizes these records for safe review by privacy counsel and compliance teams.

When this applies

Apply this workflow when correction-request records are needed for internal audits, outside-counsel review, or analytics on correction-request volumes and categories without exposing the individual consumer's identity or the specific data correction made.

  1. Upload the correction-request record or batch to anonym.legal.
  2. The engine identifies the consumer's submitted identifying information — name, email, account number — used to authenticate the request.
  3. The 'inaccurate' data field and the 'corrected' data field asserted by the consumer are both pseudonymized where they contain personal information.
  4. The data category (e.g., mailing address, date of birth, financial account detail) is retained as a structural classification field for analytics.
  5. Business-unit processing notes and correction-confirmation timestamps are preserved as audit content.
  6. A reversible mapping key is encrypted and stored with US data residency.
  7. The pseudonymized records are exported for auditor or counsel review.

What you provide

  • Correction-request submissions in PDF, DOCX, or structured format
  • Any accompanying identity-verification correspondence
  • Data-category classification if available from the privacy-management platform

Limitations & cautions

  • anonym.legal does not assess whether the correction was substantively accurate or legally required; that determination requires attorney review.
  • The §1798.106 right to correct applies only to inaccurate personal information; the tool does not evaluate whether the consumer's factual assertion of inaccuracy was correct.
  • This CPRA-added right became effective January 1, 2023; requests predating that effective date may reflect different legal obligations.
  • Records containing both personal information and trade-secret business data should be reviewed by counsel before processing.

FAQ

Is the right to correct distinct from the right to delete under CCPA/CPRA?

Yes. §1798.106 (right to correct) and §1798.105 (right to delete) are separate statutory rights. A consumer who wants inaccurate data corrected exercises §1798.106; a consumer who wants data removed entirely exercises §1798.105. Each generates separate request records that this workflow can process individually or as a batch.

Can the pseudonymized correction record show what data category was corrected without revealing the specific personal information?

Yes. The workflow is configurable to retain the data-category label (e.g., 'postal address') while pseudonymizing the actual address values submitted by the consumer, giving auditors category-level analytics without personal-data exposure.

Does this workflow apply to employee data correction requests as well as consumer requests?

CPRA extended CCPA rights to employees and job applicants effective January 1, 2023. The same pseudonymization workflow applies to employment-context correction requests, with the employment relationship noted as a structural metadata field.

Consumer Privacy

About this page

We update this page when our platform or the law changes.

Read our founder note for how we work.

Each change shows up in the timestamp at the top.

We follow these rules

  • GDPR (EU 2016/679).
  • ISO/IEC 27001:2022.
  • NIS2 (EU 2022/2555).
  • HIPAA safe harbor under 45 CFR § 164.514(b)(2).

Our promise

We do not sell your data.

We do not train models on your text.

We store your files in Germany.

You can delete your account at any time.

You own your work.

Where we run

Our servers live in Falkenstein, Germany.

We use Hetzner. They hold ISO 27001 certification.

All data stays in the EU.

Backups run every day.

Need help?

Email support@anonym.legal.

We reply within one business day.

How we test

We run a full check suite on every release.

Each surface gets its own sweep script and report.

Human reviewers spot-check the output each week.

We track recall and precision on a labelled set.

Bad runs block the deploy.

What we never do

  • We never sell your information to third parties.
  • We never train models on what you upload.
  • We never keep your work after you delete it.
  • We never share keys with any outside firm.
  • We never run ads inside the product.

Plans in plain words

We sell credits, not seats.

One credit covers one short job.

Long jobs use a few credits each.

You can top up at any time.

Unused credits roll over each month.

Read the plans page for current rates.

Who built this

A small team of engineers and lawyers built this.

We ship from Europe and work in the open.

Our founder note spells out why we started.

Where to start

How the parts fit

A browser add-on cleans text inside Chrome.

A Word plug-in handles drafts in Office.

A small desktop tool works on whole folders.

An agent protocol link feeds large models safely.

All four share one core engine and one rule set.

Words from our team

We started this work after a lunch about cookies.

One friend kept getting odd ads on her phone.

We asked why a court file leaked through a draft.

We sketched the first build on a napkin that week.

By month three we had a tiny demo for a friend.

She used it on her first case the next day.

Common questions we hear

Can the tool read scanned PDFs? Yes, with OCR.

Does it work on long files? Yes, in small chunks.

Can I roll my own rule set? Yes, save it as a preset.

Does it run offline? The desktop build runs offline.

Do you keep my files? No, the cloud build wipes after each run.

Will it learn from my work? No, we never train on inputs.

A short tour of the workflow

Upload a file or paste a snippet of prose.

Pick the entities you want gone from the draft.

Choose a method: replace, mask, hash, encrypt, or redact.

Press run and watch the side panel show each hit.

Skim the result and tweak any rule that misfired.

Save the cleaned file or send it to a teammate.