Anonymize S-1 or S-3 registration statement drafts for underwriter review – CCPA/HIPAA-compliant de-identification per 15 USC §77e

Securities Act §77e prohibits the sale of securities without an effective registration statement. S-1 and S-3 registration drafts identify named selling shareholders, founding executives, and major counterparties alongside sensitive financial and business data. anonym.legal pseudonymizes those personal data fields so draft registration statements can be reviewed by underwriters and counsel during the prefiling review without premature disclosure of named selling-shareholder identities.

When this applies

Apply this workflow when draft S-1, S-3, or other Securities Act registration statements are circulated to underwriters, investor-relations advisers, or non-legal internal teams for review where the specific named individuals are not required by the reviewer.

  1. Upload the draft registration statement — including all parts and prospectus sections — to anonym.legal in PDF or DOCX format.
  2. The engine identifies named founding shareholders, selling shareholders, directors, officers, and key personnel disclosed in the registration statement.
  3. Each named individual and associated entity is pseudonymized consistently across all sections, including the cover page, prospectus summary, risk factors, use of proceeds, selling shareholders table, and management section.
  4. Financial data, business description, and industry discussion are retained as structural content.
  5. Exhibit references and legal opinions are processed with consistent pseudonym assignments for named parties.
  6. The reversible mapping is stored encrypted for re-identification when the registration statement is filed with the SEC.
  7. The pseudonymized draft is exported for underwriter and counsel review.

What you provide

  • Draft S-1 or S-3 registration statement in PDF or DOCX format
  • Selling-shareholder schedules and lock-up agreement templates
  • Any concurrent filing documents (e.g., Form S-8) for cross-document consistency

Limitations & cautions

  • anonym.legal does not assess whether the registration statement satisfies Securities Act §77e requirements or whether any exemption from registration applies; those determinations require securities counsel.
  • The Securities Act §77k civil-liability provisions apply to material misstatements in the registration statement; pseudonymization is a review tool only and does not affect the issuer's liability for the filed document.
  • Highly specific selling-shareholder transaction descriptions may retain indirect identifiability even after name pseudonymization.
  • The tool does not prepare or submit SEC filings; all filed documents must contain actual names as required.

FAQ

Can this workflow pseudonymize the selling-shareholder table for secondary offering reviews?

Yes. The selling-shareholders table identifying individuals by name, shares offered, shares retained, and beneficial ownership percentage is processed at the individual level with consistent pseudonym assignments.

Will underwriting terms and pricing information be preserved for underwriter review?

Yes. Underwriting discount tables, overallotment option terms, and price-range data are structural content and are preserved in plain text; only named individual references are pseudonymized.

Is this workflow suitable for SPAC registration statements and de-SPAC transaction filings?

Yes. The workflow applies to S-4 and proxy/prospectus documents used in de-SPAC transactions. Named sponsor entities, founder shareholders, and target-company officers are pseudonymized consistently across the complex multi-part filing.

Securities & Corporate Disclosure

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.