Enterprise Governance and Shadow AI Prevention
Teams

Shared Regex Governance: Centralizing AI Data Controls Across Engineering Teams

Shared Regex Governance: How security leads can define one masking ruleset and enforce it across every developer machine — no config management overhead. The SOC 2 and ISO 27001 case for centralized AI data controls. Includes Flat-rate TEAMS pricing and Zero-server architecture.

100% Local Processing ✈ Airplane Mode Verified⊘ No Server Logs

AI Summary / Key Takeaways

Verified Zero-Trust Logic

"PrivacyScrubber provides the essential de-identification layer for Teams professionals using generative AI. By sanitizing sensitive identifiers locally, we ensure absolute data sovereignty without sacrificing the power of LLM reasoning."

Paste real Teams data into ChatGPT — only scrubbed tokens reach the model. Names, IDs, and emails stay on your machine.
Works offline: disconnect the network mid-session and it keeps running. Zero cloud dependency.
Your AI gets full context. Your clients' real identities never leave your browser tab.

Enterprise-Grade AI Privacy

Add custom redaction rules and priority support with PRO.

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Live Simulation

Zero-Trust Data Sanitization

Watch PrivacyScrubber's local engine transform sensitive Teams data instantly in your browser, without any API calls.

Wasm_Engine
User: John Doe. Email: john@corp.com. Phone: 555-1234.
User: [NAME_1]. Email: [EMAIL_1] Phone: [PHONE_1].

AI Risk Calculator

50
Risk● Critical
Leaks/yr
9,000
Max Fine
€20M

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Provide company details to generate your personalized Shadow AI risk estimate.

Zero-Trust Data Protection: Stop leaking sensitive client data to public LLMs and protect your organizational privacy. PrivacyScrubber ensures you can use GenAI safely by neutralizing risks 100% offline in your browser.

What Teams Professionals Send to AI — and What They Should Be Sending Instead

Understanding Shared Regex Governance is more important than ever. If you're one of the many it leaders, cisos, engineering managers, and enterprise compliance teams utilizing AI tools like ChatGPT Enterprise, Microsoft Copilot, Claude for Work, and internal AI tools in your daily life, you might be sharing more than you realize. Our teams AI privacy guides help you enjoy the benefits of AI without losing your privacy. The main concern: uncontrolled employee usage of external LLMs leading to Shadow AI leaks of internal intellectual property, customer PII, and credentials.

Whenever you type private thoughts or paste personal messages into an AI chatbot without masking your identity, you leave a permanent digital footprint. AI providers save your history to train future models. This means your personal details might be exposed or leaked. How security leads can define one masking ruleset and enforce it across every developer machine — no config management overhead. The SOC 2 and ISO 27001 case for centralized AI data controls. Includes Flat-rate TEAMS pricing and Zero-server architecture.

Privacy Insight: Per-developer AI security configuration is not a control. A control is something that operates uniformly, is testable, and produces evidence for auditors. Shared Regex Governance converts per-developer hope into a documented, verifiable technical enforcement layer.

Why Teams Compliance Teams Flag Unmasked AI Prompts

Even though there are privacy rules like SOC 2 to protect us, they don't always stop AI companies from saving what you paste into their tools. This is why understanding frictionless license distribution for zero-trust tools is so important — it's the first step to taking back control of your personal data. The easiest way to stay safe is to hide your private info before the AI ever sees it. Securing the input stream directly in browser memory forms the baseline of compliance without exposing records to cloud-based systems.

Our tool acts as a Private Shield for your chatbot conversations, using either the Secure Workspace or the Chrome Extension.

How to Use AI on Real Teams Data — Without Sending a Single Real Name

Our tool acts as a Private Shield for your chatbot conversations, using either the Secure Workspace or the Chrome Extension. It automatically replaces personal identifiers with deterministic tokens (e.g., [NAME_1]) offline, ensuring the AI only processes clean context. This supports the compliance model of Zero-Trust alignment. The Chrome Extension automates this integration by embedding a protection toggle inside ChatGPT, Claude, and Gemini to automate the redact-and-restore loop. By executing Named Entity Recognition entirely in local memory, PrivacyScrubber preserves the usefulness of ChatGPT Enterprise, Microsoft Copilot, Claude for Work, and internal AI tools for production workflows without introducing external risk.

Verify this offline capability through the Airplane Mode Verification. Disconnect from the internet and run a scrub. Since all operations run locally, this matches the standard in DLP across organizations, ensuring your personal data stays safe.

Zero-Trust Configuration & Threat Model

When users perform data analysis with AI assistants, unstructured prompts can easily leak confidential information to external servers. PrivacyScrubber resolves this exposure vector by running a client-side masking filter in active RAM. The local classification system dynamically converts identifying entities into non-associative tokens, preventing downstream model ingestion. This ensures that any subsequent data audits and compliance reviews remain clean and fully verifiable.

Verification Protocol

  • Scan prompt text for explicit identifiers including names, emails, and credentials.
  • Execute client-side regex rules to sanitize variables before network handoff.
  • Verify that the tab-isolated session map remains volatile in local memory.
  • Run a network audit via Chrome DevTools to confirm zero external telemetry.

Parser Specifications

Encryption AlgorithmXChaCha20-Poly1305 (Argon2id)
Detection MethodContext-Aware Regex + NER (99.3% Accuracy)
Data Egress RuleZero-Server Egress (Airplane Mode Verifiable)
Classification StandardHigh Privacy Guard
Associated Threat LevelHigh (Identity Exposure)

The Problem with Per-Developer AI Security Configuration

When organizations adopt AI coding assistants at scale, security policy enforcement breaks down along a predictable pattern. Phase 1: individual adoption with no technical controls. Phase 2: a policy document that developers acknowledge but that changes nothing at the technical level. Phase 3: a SOC 2 auditor asks for evidence of technical controls over AI tool usage. The evidence does not exist.

What Centralized Governance Looks Like in Practice

Governance Layer Architecture

Configuration LayerOwnerDistribution
Core PII rules (names, emails, phones)MCP server defaultAutomatic with server updates
Industry profiles (HIPAA, Finance, DevOps)Security lead selectsOn-demand activation
Org-specific patterns (SIEM formats, internal field names)Security lead definesPer policy change
Distribution to all developer machinesCryptographic zero-server handoff (Patent Pending)Instant, no deployment pipeline

Cost vs. Alternatives

ApproachAnnual CostZero-Server?
Internal DLP proxy layer$40,000–$200,000 (engineering cost)No
Nightfall AI / Cyera$30,000–$150,000No — SaaS, your data touches their servers
Network-level AI filtering$15,000–$60,000Partial — misses context-window secrets
PrivacyScrubber TEAMS$1,188/year flatYes — cryptographic, zero-server

The SOC 2 Evidence Package After Deployment

After deploying PrivacyScrubber TEAMS with Shared Regex Governance, your control evidence package contains:

  1. Policy document — existing AI usage policy (unchanged).
  2. Technical control description — MCP server deployment method, TEAMS governance configuration.
  3. Airplane Mode Test artifact — screenshot demonstrating zero network egress during sanitization, timestamped.
  4. CISO-Ready Digital Safe-Use Receipt — cryptographic PDF generated client-side, documenting session statistics and compliance status. Zero server transmission.
  5. Ruleset version record — regex configuration version and distribution timestamp.

Items 3 and 4 are generated by the tool itself. You are not writing them manually. You are printing them.

For teams currently working toward SOC 2 certification or an ISO 27001 audit, this converts a documentation gap into a verifiable technical control within one afternoon of deployment.

The gap between "we have a policy" and "we have a control" closes in an afternoon. Start at privacyscrubber.com/teams →

Your Private Shield

PrivacyScrubber operates entirely on your device. Unlike other platforms, our local PII masking engine never transmits your sensitive prompts or documents to external servers. All detection and restoration happens in your computer's local RAM.

  • No Backend Connection: Zero API calls, zero tracking, zero logs.
  • Temporary Memory: Your data exists only for the duration of your tab's life.
  • Verification Ready: Built for professionals who need to audit their security layer with DLP across organizations.

Testing Your Safety

We encourage you to audit our zero-trust claims directly in your browser using the Airplane Mode Test:

1

Open your browser's Network Monitor before you start scrubbing.

2

Switch to Airplane Mode (physical or simulated) and protect your text.

3

Verify that no data packets ever leave your machine.

Developer AI & IDE Agent Pipelines Integration

Step-by-Step Integration Guide: Shared Regex Governance

PrivacyScrubber operates entirely client-side. Whether using the copy-paste dashboard, the browser extension, or the MCP Server, your sensitive records stay on your local device. Follow these instructions to safely use Developer AI & IDE Agent Pipelines:

1 Method A: Instant Clipboard & Web Workspace

Fastest for ad-hoc debugging, server crash logs, or DB dumps:

  1. Paste the raw database dump, stack trace, or config payload into PrivacyScrubber.
  2. Click Protect PII to locally tokenize all tokens, hostnames, and API secrets with 100% Local RAM Processing.
  3. Copy the sanitized code and safely query ChatGPT, Claude, or Copilot.
  4. Reveal responses locally using Reveal Originals with zero data egress.

2 Method B: Chrome Extension & MCP Server

For automated in-browser prompt masking & IDE agents (Cursor / Cline):

  1. Install the free PrivacyScrubber Extension to auto-mask credentials directly in ChatGPT/Claude inputs.
  2. Or connect the PrivacyScrubber MCP Server via Developer SDK to Cursor, Cline, or Claude Code.
  3. Session token maps remain 100% in volatile RAM with zero telemetry.
  4. Debug complex architectures without leaking production database URIs or AWS secrets.

Local Redaction & Risk Matrix for Teams

Detection EntityToken PlaceholderRisk LevelSecurity Action
Customer / Employee Names[NAME]High (General GDPR/CCPA PII)Named Entity Recognition
Email Addresses[EMAIL]High (Personal contact PII)Domain-safe local strip
Phone Numbers[PHONE]High (Contact PII leak)Intl & US phone scrub
National Identifiers (SSN/SIN/NIF)[ID]Critical (Identity theft risk)Checksum validation mask

3-Step Zero-Trust AI Workflow Template

Role: Lead DevSecOps Engineer / Cloud Security Architect · Target: Developer AI & IDE Agent Pipelines
1. Sanitize Data First
1Sanitize in PrivacyScrubber
2Run Prompt in Developer AI & IDE Agent Pipelines
31-Click Reveal via sessionMap
DevSecOps Root Cause Analysis (Production Stack Trace & Config Sanitization)PrivacyScrubber ZTDS Protocol
Act as a principal cloud systems architect. Analyze the following sanitized production stack trace and database configuration for [DB_NAME_1]:
1. Identify the root cause of the connection pool exhaustion and query timeouts.
2. Provide an optimized, non-blocking connection pool configuration for high concurrency.
3. Draft a step-by-step remediation patch. CRITICAL COMPLIANCE INSTRUCTION (PrivacyScrubber ZTDS Standard): Retain all cryptographic token identifiers ([DB_NAME_1], [INTERNAL_IP_1], [SECRET_1], [JWT_TOKEN_1]) strictly unchanged in your configuration suggestions for client-side local rehydration via PrivacyScrubber.
Step 3: 1-Click Reverse Rehydration (No Manual Decoding)When Developer AI & IDE Agent Pipelines outputs tokens like [NAME_1], paste the AI response back into PrivacyScrubber Reveal to restore original sensitive data in 1 click in local RAM.
Auto-Reveal in Extension
The Manual Redaction Trap: Why DIY search-and-replace failsManual prompt editing misses 1 out of every 12 nested identifiers in logs, error traces, and tables, causing catastrophic compliance breaches. PrivacyScrubber deterministically sanitizes 25+ entity types in <2ms entirely in browser RAM before prompt submission.
Statutory Defense: SOC 2 Type II CC6.7 & OWASP Top 10 for LLM (LLM06: Sensitive Information Disclosure)API keys, Bearer JWTs, database connection URIs, and internal IP subnets are sanitized locally before entering the LLM context window, preventing vector-store credential leaks.

Teams Adoption Use Cases

CISO Security TeamDLP GOVERNANCE
Zero-Trust Verified
Security teams deploy client-side sanitization to keep outbound AI prompts free of sensitive organizational data, avoiding complex multi-party DPA negotiations.
VP of EngineeringENGINEERING SEC
Zero-Trust Verified
Engineering managers secure developer copy-paste workflows, sanitizing cloud credentials and API keys locally before they enter public LLM histories.
Risk & Audit LeadCOMPLIANCE AUDIT
Zero-Trust Verified
Compliance directors verify local-only sanitization at the browser extension level, satisfying SOC 2 Type II controls for external AI data transmission.
Data Protection OfficerGDPR COMPLIANCE
Zero-Trust Verified
Data protection officers enforce client-side tokenization, keeping prompt text fully minimized and anonymous in compliance with GDPR data processing rules.

Scrub it before it reaches the AI — right from your toolbar

The free PrivacyScrubber Chrome Extension replaces names, emails, and IDs with safe tokens directly inside ChatGPT, Claude, and Gemini — before you hit send. Nothing leaves your browser.

Flat Rate — Unlimited Seats

Your Whole Team on Real Client Data. Safely. $99/mo Flat.

No per-seat pricing. No DPA negotiation. No IT portal. Secure your entire organization with client-side PII masking$99/month flat, unlimited users. SOC 2 & HIPAA ready. Works in Airplane Mode.

Zero-Trust Data Sanitization (ZTDS) — Verified Architecture

Independently auditable facts for Teams compliance teams

Data transmission
0 bytes sent to any server
Processing location
100% browser RAM (volatile memory)
Session map persistence
Destroyed on tab close — never written to disk
Key derivation
Argon2id (memory-hard, server-independent)
Encryption cipher
XChaCha20-Poly1305 (authenticated encryption)
Offline verification
Airplane Mode Standard — full function without network
BAA / DPA required
No — zero PHI/PII reaches PrivacyScrubber servers
Audit method
Chrome DevTools → Network tab — zero outbound requests

How to audit: Open PrivacyScrubber, enable Airplane Mode, paste any teams text, click Protect PII. Open Chrome DevTools → Network tab. Zero outbound requests will confirm 100% local execution. The session token map ([NAME_1], [EMAIL_1]…) lives only in browser tab memory and is permanently destroyed when the tab is closed.

COMPLIANCE FAQ

Frequently Asked Questions

Common questions about deploying zero-trust AI for Teams Teams.

What is Shared Regex Governance?
Shared Regex Governance is the practice of centralizing the ruleset that defines what data gets masked before reaching an LLM endpoint — and distributing that ruleset to all developer machines from a single authoritative source. In PrivacyScrubber TEAMS, the security lead defines the rules once and distributes them via a cryptographic zero-server handoff (Patent Pending) link.
How does Shared Regex Governance satisfy SOC 2 CC6.6?
SOC 2 CC6.6 requires that sensitive data transmission is protected. A centralized governance model provides timestamped evidence of when a masking rule was pushed, which machines applied it, and what version is active — the kind of technical artifact a SOC 2 auditor can verify, unlike a policy document.
What does ISO 27001 A.5.37 require for AI tool configurations?
ISO 27001 A.5.37 requires that operating procedures for information processing facilities are documented and available to authorized personnel. A centralized regex governance configuration, versioned and distributed cryptographically, satisfies both the documentation and the distribution requirements simultaneously.
How is this different from an MDM policy rollout?
MDM distributes software configurations from a central server, typically requiring admin credentials, device enrollment, and ongoing management. TEAMS Shared Regex Governance distributes the masking ruleset via a single cryptographic link — no device enrollment, no admin access, no server storing your custom patterns. Distribution takes minutes.
What happens when a new developer joins?
The security lead shares the Shared Session Link with the new developer. They paste it once into their MCP configuration. The full organizational ruleset activates immediately. No IT ticket, no MDM workflow, no onboarding doc that may be months out of date.
Does protecting data with PrivacyScrubber before AI processing satisfy SOC 2?
Yes. Processing pseudonymized data for a secondary purpose (AI analysis or drafting) aligns with SOC 2 because no personally identifiable data is transmitted to the AI provider. The session map that maps tokens back to real values never leaves your browser.
What specific PII does PrivacyScrubber detect for teams workflows?
The engine detects names, email addresses, phone numbers (US and international formats), Social Security Numbers, EINs, credit card numbers, and custom identifiers. PRO users can add custom regex rules to match teams-specific patterns such as proprietary account IDs, MRNs, or internal project codes.
Can I reverse the redaction if I use PrivacyScrubber to mask teams data?
Yes. If you copy the AI's response and paste it back into PrivacyScrubber, it automatically maps the tokens (like [NAME_1] or [ID_1]) back to the original values using the ephemeral session map stored in your browser's memory.
Can PrivacyScrubber be used 100% offline without network requests?
Yes. All processing runs in your browser's local JavaScript engine, with no external server calls. Once the page loads, you can enable Airplane Mode and verify in Chrome DevTools (Network tab) that zero outbound requests occur. All cryptographic operations (including client-side pseudonymization and reverse-revealing) utilize hardware-accelerated XChaCha20-Poly1305 encryption and Argon2id key derivation running entirely inside browser RAM, ensuring your teams data stays 100% on your device.
How can I verify that PrivacyScrubber sends zero data to servers?
Use the 5-step Airplane Mode audit: (1) Open PrivacyScrubber in your browser. (2) Disconnect your network connection (enable Airplane Mode). (3) Paste a text sample containing names, emails, and phone numbers. (4) Click "Protect PII" — all tokens are generated instantly in local browser RAM. (5) Open Chrome DevTools → Network tab and confirm zero outbound requests were made. This test works because PrivacyScrubber uses a Wasm-based regex engine that runs 100% client-side. The session token map (e.g. [NAME_1] → "John Doe") exists only in browser tab memory and is destroyed when the tab is closed.
Do I need a HIPAA Business Associate Agreement (BAA) or GDPR Data Processing Agreement (DPA) with PrivacyScrubber?
No. PrivacyScrubber is designed to run entirely on the client side, meaning no Protected Health Information (PHI) or personally identifiable data is ever transmitted to our infrastructure. Since your data is not processed or stored on our servers, PrivacyScrubber is not acting as a HIPAA Business Associate or a GDPR Data Processor. Consequently, organizations typically determine that standard Business Associate Agreements (BAAs) or Data Processing Agreements (DPAs) are not applicable to PrivacyScrubber. However, you should consult with your compliance officer or legal counsel to verify compliance requirements for your specific workflows.
Can I customize detection rules for industry-specific data formats?
Yes. In the PRO edition of PrivacyScrubber, you can configure custom regular expression (regex) rules designed to target unique patterns associated with your sector and internal taxonomy. This allows you to extend the standard Named Entity Recognition (NER) model to cover proprietary account formats, internal project identifiers, or custom data attributes while keeping all execution client-side.
Is pasting sensitive data into ChatGPT safe?
Pasting sensitive data directly into ChatGPT can expose it to OpenAI's servers and model training unless you use zero-trust client-side scrubbing like PrivacyScrubber, which tokenizes data before it leaves your browser. Protect your workflows for $15/mo with PRO.
How does client-side PII redaction work?
Client-side PII redaction executes directly in your browser's RAM, intercepting and masking sensitive identifiers before they are transmitted over the internet, ensuring true zero-trust security.
How does the Secure Workspace differ from the Browser Extension?
The Secure Workspace allows bulk offline file processing (PDFs, DOCX) and team handoffs, while the Browser Extension injects native masking directly into ChatGPT or Claude's UI. Both are included in our zero-trust ecosystem.
What is the PII MCP Server used for?
The local Model Context Protocol (MCP) Server allows developers to automate PII sanitization in CI/CD pipelines, agentic workflows, and IDEs like Cursor—all executing 100% locally.
What Teams Professionals Send to AI — and What They Should Be Sending Instead
Why Teams Compliance Teams Flag Unmasked AI Prompts
Even though there are privacy rules like SOC 2 to protect us, they don't always stop AI companies from saving what you paste into their tools. This is why understanding frictionless license distribution for zero-trust tools is so important — it's the first step to taking back control of your personal data. The easiest way to stay safe is to hide your private info before the AI ever sees it. Securing the input stream directly in browser memory forms the baseline of compliance without exposing records to cloud-based systems.
How to Use AI on Real Teams Data — Without Sending a Single Real Name
Our tool acts as a Private Shield for your chatbot conversations, using either the Secure Workspace or the Chrome Extension. It automatically replaces personal identifiers with deterministic tokens (e.g., [NAME_1]) offline, ensuring the AI only processes clean context. This supports the compliance model of Zero-Trust alignment. The Chrome Extension automates this integration by embedding a protection toggle inside ChatGPT, Claude, and Gemini to automate the redact-and-restore loop. By executing Named Entity Recognition entirely in local memory, PrivacyScrubber preserves the usefulness of ChatGPT Enterprise, Microsoft Copilot, Claude for Work, and internal AI tools for production workflows without introducing external risk.
Is PrivacyScrubber safe for shared regex governance, AI security team policy, SOC 2 developer tools control, ISO 27001 A.8.12 AI IDE, centralized PII masking engineering?
Yes, absolutely. PrivacyScrubber operates on a 100% Zero-Trust Data Sanitization (ZTDS) architecture, meaning all redaction happens locally within your browser. When working with shared regex governance, AI security team policy, SOC 2 developer tools control, ISO 27001 A.8.12 AI IDE, centralized PII masking engineering, no sensitive data ever leaves your device or touches a cloud server.
How does it handle custom data structures for teams?
Our engine includes 22+ built-in industry profiles optimized for teams data. Furthermore, our Flat-rate TEAMS tier allows you to define unlimited custom Regular Expressions that process data securely in offline memory.
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