Anonymize video viewing and rental records for litigation support under VPPA – CCPA/HIPAA-compliant de-identification per 18 USC §2710

The Video Privacy Protection Act, 18 USC §2710, prohibits the disclosure of personally identifiable video rental or viewing records without consumer consent. These records linking individual identities to specific titles and viewing histories are highly sensitive. anonym.legal pseudonymizes viewing-record datasets so counsel can assess disclosure scope, prepare litigation responses, and conduct content-analytics without exposing viewer identities.

When this applies

Apply this workflow when video viewing or rental records must be reviewed by outside counsel, shared with a litigation-support vendor, or analyzed for content patterns in a VPPA compliance review or class-action defense.

  1. Export viewing or rental records from your video platform in CSV, JSON, or structured database format.
  2. Upload the records to anonym.legal; the engine identifies the subscriber or patron identifier linked to each viewing event.
  3. Viewer identifiers — account ID, name, email, device ID — are replaced with consistent pseudonyms across all viewing events.
  4. Video title identifiers, viewing timestamps, and playback duration are retained as structural content for content-analytics and litigation-scope assessment.
  5. Third-party analytics identifiers embedded in the records are pseudonymized to prevent cross-platform linkage.
  6. A reversible mapping key is encrypted and stored with US data residency.
  7. Pseudonymized viewing records are exported for outside-counsel review, litigation-support analysis, or VPPA compliance audit.

What you provide

  • Video viewing or rental records in CSV, JSON, or structured database export format
  • Third-party analytics mapping files identifying embedded tracking identifiers
  • Date range and content categories for the records to be processed

Limitations & cautions

  • anonym.legal does not assess whether a proposed disclosure of viewing records constitutes a VPPA violation; that determination requires legal counsel.
  • The VPPA's definition of 'personally identifiable information' has been interpreted differently by courts; counsel must evaluate whether the records fall within the statute's scope.
  • Pseudonymizing records does not authorize their disclosure; any sharing of viewing records must be evaluated for VPPA consent requirements before disclosure.
  • Class-action VPPA litigation often involves data from multiple platforms; records from different systems must be processed separately to avoid cross-platform identifier conflicts.

FAQ

Does VPPA apply to streaming services, not just physical video rental stores?

Courts have applied VPPA to online streaming platforms, holding that digital viewing records linked to subscriber accounts constitute 'personally identifiable information' under 18 USC §2710. This workflow processes streaming-platform viewing records with the same pseudonymization logic as traditional rental records.

Can pseudonymized viewing records be used in a class-certification analysis?

Yes. Pseudonymized records can provide the statistical basis for class-certification expert analysis — number of viewers affected, categories of titles disclosed, disclosure frequency — without exposing individual viewer identities to litigation-support experts who lack a VPPA consent basis for accessing real records.

What consent is required under VPPA before disclosing viewing records?

VPPA requires informed, written consent from the consumer that is distinct from any other consent form and that specifies the person to whom the records will be disclosed. Consent obtained as part of a general terms-of-service acceptance may not satisfy this requirement. Counsel should evaluate consent adequacy before any disclosure of actual viewing records.

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.