Anonymizing Security Agreements for Lender Due-Diligence Review – CCPA/HIPAA-compliant de-identification per UCC §9-203

A security agreement creating a security interest under UCC §9-203 identifies the debtor and secured party by name and address, and may name individual guarantors in attached guarantee provisions. anonym.legal anonymizes those personal identifiers — preserving the collateral description, attachment conditions, and default remedies — so lenders and their counsel can assess the security package without processing unnecessary personal data.

When this applies

This task applies when a security agreement and any related guarantee or intercreditor agreement are shared with co-lenders, rating agencies, or outside counsel who need to evaluate the collateral description, attachment conditions under UCC §9-203, and enforcement rights without direct access to the named parties' personal data.

  1. Upload the security agreement, any guarantee, and any intercreditor agreement to anonym.legal.
  2. The engine identifies named debtors, secured parties, guarantors, and authorized signatories across all documents.
  3. Each individual is anonymized consistently; collateral descriptions, attachment conditions, and default-remedy provisions are preserved.
  4. Filing obligations, perfection steps, and priority rules derived from UCC Article 9 remain in clear text.
  5. A mapping table is generated with US data residency.
  6. Release the anonymized set for lender review; restore originals before filing or execution.

What you provide

  • Security agreement
  • Guarantee or personal guaranty (if applicable)
  • Intercreditor or subordination agreement (if applicable)

Limitations & cautions

  • The tool does not assess whether the security interest has attached or been perfected under UCC §9-203 and §9-308 — obtain qualified legal advice.
  • After-acquired property clauses that reference the debtor by name may require a manual review to confirm correct anonymization.
  • Personal guarantees naming individual guarantors contain sensitive financial data; ensure only authorized reviewers access the mapping table.

FAQ

What conditions must be met for a security interest to attach under UCC §9-203?

Under UCC §9-203, a security interest attaches when value has been given, the debtor has rights in the collateral, and the debtor has authenticated a security agreement describing the collateral. This tool anonymizes the personal data in the security agreement but does not assess attachment — obtain legal advice.

Are after-acquired property clauses anonymized?

After-acquired property clauses are preserved in full. If the clause references the debtor by name rather than by defined term, that name is anonymized. Review the anonymized clause before providing a lien-priority opinion.

Can I process a security agreement governed by the law of a specific state?

Yes. UCC Article 9 has been adopted in substantially uniform form by all US states. The tool anonymizes personal data in the agreement regardless of the governing-state choice-of-law clause.

Commercial Contracts

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.