anonym.legal

By · Last updated 2026-04-07

73% of AI-generated apps miss PII handling

Vibe Coding Safety: Prevent PII Leaks in AI-Generated Code

Cursor, Windsurf, and Claude Desktop ship production code at speed — but without PII guardrails. Anonymize sensitive data before it reaches your AI IDE and strip it from generated code automatically.

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73%
of AI-generated apps skip PII handling
8,000+
MCP servers exposed publicly
9.3
CVSS — LangChain CVE-2026-22708
CVE
CVE-2026-22708 — Cursor IDE

Why Vibe Coding Creates PII Risk

Vibe coding speeds up development. But AI IDEs like Cursor and Windsurf pull in your entire codebase. That includes any real data in tests, fixtures, or prompts. PII then slips silently into model context, training fine-tunes, logs, and generated output.

Documented risks in AI-assisted development:

  • CVE-2026-22708 (Cursor IDE): Credential and PII data in open files transmitted to model context without filtering. CVSS 8.1.
  • LangChain CVE-2026-22708: CVSS 9.3 — prompt injection via RAG documents injects PII into unintended model outputs and logs.
  • 8,000+ exposed MCP servers: Public MCP server scans reveal thousands processing raw PII without sanitization, violating GDPR and HIPAA.

Four Ways to Protect Your Vibe Coding Workflow

Choose the integration that fits your stack — or combine them for full-stack PII coverage.

MCP Server

Anonymize prompts transparently in Claude Desktop, Cursor, and any MCP-compatible IDE. PII is replaced before reaching the model; responses are de-anonymized automatically.

Learn more

REST API

Integrate PII anonymization directly into your CI/CD pipeline, test fixture generators, or code review bots via a single API call.

Learn more

Chrome Extension

Protect browser-based AI IDEs and code assistants. Anonymizes text before it is sent from the browser — zero configuration required.

Learn more

Desktop App

Batch-process code files, test fixtures, and datasets locally before sharing with AI tools. Works offline with zero data leaving your machine.

Learn more

Built for Developer Workflows

Native IDE Integration

MCP Server connects directly to Cursor, Windsurf, Claude Desktop, and VS Code. No middleware, no proxies — just transparent PII anonymization in your existing workflow.

285+ Entity Types

Detect names, emails, API keys, credentials, SSNs, IBANs, and 285+ other PII types across 48 languages — including code-embedded secrets and hardcoded test data.

Reversible Anonymization

Replace PII with consistent placeholders (e.g. [PERSON_1], [EMAIL_1]) so AI-generated code stays functional. De-anonymize the output in one step to restore real values.

Zero-Knowledge Architecture

Your encryption keys never leave your device. anonym.legal cannot read your original data. CSPRNG-backed key generation with AES-256-GCM encryption.

GDPR-aligned · HIPAA Safe-Harbor De-Identification

EU data residency. Anonymization meets GDPR Article 4(1) definition. Audit-ready reports for DPA inquiries; HIPAA Safe-Harbor de-identification recognizers (Customer responsibility for HIPAA compliance — separate BAA required for PHI processing).

Audit Logs

Every anonymization event is logged — entity types detected, timestamps, and session IDs — for compliance audits and incident response.

Set Up in Under 5 Minutes

1

Create a free account

Sign up at anonym.legal — free tier includes 200 tokens/month, all 285+ entity types, and full MCP Server access on the Pro plan.

2

Add the MCP Server to your IDE

Add the anonym-legal MCP Server config to your claude_desktop_config.json or Cursor settings. One JSON block — no binary installation.

3

Anonymize before every AI prompt

The MCP Server intercepts prompts containing PII and replaces entities with consistent placeholders before the model sees them. Fully transparent.

4

De-anonymize AI output

Paste the AI-generated code into the de-anonymize endpoint (or Chrome Extension) to restore original values. Your real data never touched the model.

Related Resources

Tutorial

Use Claude & ChatGPT Without Leaking PII

Step-by-step MCP Server setup guide for Claude Desktop, Cursor, and VS Code — with example configs and verification steps.

Blog Article

Cursor & Claude: Protecting Developer Credentials

How to prevent credential and PII leakage when using Cursor IDE with Claude — covering CVE disclosures and mitigations.

Blog Article

Why Enterprises Ban AI Coding Tools (And How MCP Fixes It)

The security case for MCP-based PII anonymization as an enterprise alternative to blanket AI tool bans.

Code Faster. Leak Nothing.

Start protecting your AI coding workflow today — free tier, no credit card required. MCP Server, REST API, Chrome Extension, and Desktop App included.

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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.

Related reading

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.