Free PII Removal Tool & Offline PII Scanner: 100% Local Zero-Server Redaction
Free PII Removal Tool & Real-Time Local Data Redaction Engine
AI Summary / Key Takeaways
"Free PII removal tool and smart PII scanner. Scan and remove PII online instantly with 100% local browser execution. Redact names, SSNs, credit cards, emails, and credentials without server uploads or DPA bottlenecks."
Enterprise-Grade AI Privacy
Add custom redaction rules and priority support with PRO.
Interactive PII Detection & Sanitization Sandbox
Test real-time client-side RAM tokenization. Choose a specialized preset or paste your own raw prompt to test instant reversible redaction.
The Challenge with AI Data Workflows
Legacy cloud-proxy DLP (Data Loss Prevention) systems and online APIs force you to upload your sensitive data to their servers for inspection. This creates a severe 'Middleman Risk', adds 6-8 weeks of legal BAA/DPA contract reviews, and introduces latency penalties up to 1,500ms for every ChatGPT or Claude prompt.
How It Works
Ingest Content
Paste text or drop documents. The file is held strictly in your browser's volatile RAM and encrypted locally.
Local PII Scanning
The engine runs a client-side NLP parser (compromise.min.js) on the main thread to extract names, while native regular expressions scan for patterns (emails, credit cards) in a background Web Worker.
Token Isolation
Sensitive values are swapped for placeholders, and the originals are encrypted in RAM using the Web Crypto API (AES-GCM-256) with keys that purge instantly when you close the tab.
What Teams Achieve with Local PII Masking
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Supported Formats & Limitations
Supported Formats
System Limitations
- Single text strings > 5MB are chunked automatically to prevent UI blocking
- Requires standard Web API support (TextEncoder, crypto.subtle)
- NLP entity extraction runs single-threaded, optimal for documents under 2,000 pages
Outcome Breakdown: What Happens When Your Team Uses Local PII Masking
When employees copy internal documents, customer support tickets, financial models, or employee records into ChatGPT, Claude, or Gemini, traditional DLP tools block the request or send the entire prompt to a 3rd-party cloud proxy for inspection. That creates a 6-to-8 week security questionnaire bottleneck and introduces a second cloud vendor into your compliance perimeter.
The Zero-Subprocessor Advantage: 0-Day AI Approval
PrivacyScrubber strips personal identifiers locally inside the browser's volatile RAM before the prompt is sent to any AI server. Because zero PII leaves the endpoint, no third-party data processor relationship is formed, eliminating subprocessor risk and procurement bottlenecks for Data Processing Agreements (DPAs) or Business Associate Agreements (BAAs). Your team starts using AI on day 1 with zero compliance debt.
Side-by-Side Comparison: Legacy Cloud Proxy vs. Local Browser Masking
| Evaluation Factor | Legacy Cloud Proxy DLP | PrivacyScrubber Local PII Engine |
|---|---|---|
| Data Path | Traverses proxy vendor cloud & API servers | Stays 100% inside local browser RAM |
| Latency Penalty | +200ms to +1,500ms network round-trip | <1ms local Web Worker execution |
| Legal Procurement | Requires DPA, BAA, and 6-week Vendor Audit | Zero Subprocessor (No Data Processor Relationship) |
| Breach Exposure Risk | $4.88M average enterprise breach exposure | $0 exfiltration payload risk (Tokens only) |
| Pricing Model | $15–$45 per user per month seat fees | $99/mo flat for unlimited team seats |
Architectural Vulnerabilities: Cloud DSPM & DLP Incumbents
| Vendor / Architecture | Core Bottleneck / Vulnerability | Latency & Execution | Data Residency / DPA |
|---|---|---|---|
| Skyflow API Data Privacy Vault | External API dependency (Network hop). Requires sending data to a regional vault. | Moderate (Network dependent) | Requires BAA/DPA. Data leaves local endpoint to regional vault. |
| Nightfall AI Cloud DLP API | Cloud proxy bottleneck. Subject to strict API rate limits (HTTP 429) & volume throttling. | High (API transit + Inspection) | Requires BAA/DPA. Prompts must traverse cloud servers. |
| Cyera API-First DSPM | Scan-only visibility gap. Lacks real-time inline intervention for prompt masking. | N/A (Out-of-band) | Metadata processed externally. Cloud IAM access required. |
| Securiti.ai Graph-Based DSPM | Alert fatigue & orchestration complexity. Heavy API connector integration required. | N/A (Out-of-band) | Metadata processed externally. Deep IAM connector permissions needed. |
| PrivacyScrubber Zero-Trust Local Execution | None. 100% Client-side. Air-gapped execution possible. | <1ms (RAM Execution) | 0 Bytes transmitted. Zero subprocessor risk. |
How Compliance Officers Verify Zero-Trust Execution in 60 Seconds
Security teams should never rely on marketing claims alone. PrivacyScrubber is designed to be fully auditable by your CISO or IT Security Lead using a simple 4-step verification procedure:
- Open Developer Tools: Open Chrome or Edge DevTools (F12), then select the Network tab.
- Activate Offline Mode: Check the Offline checkbox (or enable Airplane Mode on your operating system).
- Execute PII Masking: Paste sensitive text containing names, emails, and phone numbers into PrivacyScrubber and click Scrub.
- Confirm 0 Packets Transmitted: Observe that the scan completes instantly with zero outbound network requests. No payload packets hit the network.
Technical Deep-Dive: Browser-Native Inference
PrivacyScrubber operates by intercepting text at the client level before any API call is made. By using WebAssembly and Web Workers, we move high-performance computing to your local processor.
Secure Workspace Flow
Use our Secure Workspace for one-off document sanitization. Simply paste, scrub, and copy the sanitized output. Your data remains strictly in your tab's volatile RAM.
Browser Extension Flow
Install our extension to scrub inputs directly inside ChatGPT, Claude, or Notion. The extension monitors text fields for PII and masks them in real-time before they leave your browser.
Related Modules
Cross-Platform Extension & Developer Integration
The exact same Zero-Trust NLP+Regex engine powers our Chrome Extension and Developer SDK, ensuring cryptographically identical tokenization across your entire tech stack.
Client-Side Reliability & Audit Verification
Powered by the Zero-Trust Sanitization Engine (ZTDS). All detection, tokenization, and regex evaluation execute 100% inside your local client process boundary — eliminating cloud proxies, intermediate servers, and third-party data retention risks.
Step-by-Step Guide
How to use this feature
Open PrivacyScrubber
Go to privacyscrubber.com — no login, no account required. The tool loads instantly in your browser.
Paste your text
Paste any text containing personal data into the main input field. Works with emails, names, phone numbers, SSNs, credit cards, and more.
Click Scrub
Hit the Scrub button. Detection runs entirely in your browser — watch PII tokens appear color-coded in real time. Zero data leaves your device.
Copy the safe output
Copy the scrubbed text. All PII is replaced with tokens like [NAME_1], [EMAIL_1], [PHONE_1]. Paste safely into ChatGPT, Claude, or Gemini.
Reveal (optional)
Paste the AI response back into PrivacyScrubber and click Reveal to re-hydrate with original values from your local session map.
Frequently Asked Questions
How do I remove PII from text online for free?
Open PrivacyScrubber in any browser, paste your text containing names, emails, phone numbers, or credentials, and click 'Scrub'. The tool immediately detects and removes all sensitive identifiers locally in your browser's RAM, replacing them with synthetic tokens ([NAME_1], [EMAIL_1]). Zero data is ever transmitted to a server.
Why is local browser-based PII removal safer than cloud DLP APIs?
Cloud DLP APIs require transmitting your raw, unencrypted data across the internet to a third-party server to detect PII. This introduces network exposure, requires vendor DPA/BAA contracts, and increases breach risk. PrivacyScrubber runs 100% client-side in browser RAM using WebAssembly and Web Workers — your data never leaves your endpoint.
Can this PII removal tool strip names, emails, and financial data simultaneously?
Yes. PrivacyScrubber employs a hybrid dual-engine architecture: a client-side NLP model (compromise.min.js) contextualizes and extracts full names, while native regular expressions with Luhn algorithm validation instantly catch emails, phone numbers, credit card numbers, SSNs, IP addresses, JWTs, and API credentials in parallel.
How does PII removal work before sending prompts to ChatGPT, Claude, or Gemini?
Before copying a prompt into an AI chat interface, paste the raw text into PrivacyScrubber. The tool tokenizes all confidential entities. You then paste the tokenized text into ChatGPT. When ChatGPT answers with the tokens, you can paste the response back into PrivacyScrubber and click 'Reveal' to re-hydrate the original identifiers locally.
What is the difference between the regex engine and NLP for name detection?
Regex handles deterministic formats: emails (RFC 5321 compliance), phone numbers (E.164 + US local), credit cards (Luhn algorithm validation), SSNs, IPs, JWTs, and AWS keys. NLP handles context-dependent entities like full names, where 'Smith' in 'Dr. Smith prescribed...' is a name but 'Smith' in 'Blacksmith tools' is not. Both run locally in a Web Worker.
What is the token format and can I customize it?
Tokens follow the pattern [TYPE_N] — for example [NAME_1], [EMAIL_2], [PHONE_1]. The type label maps to the entity class. N is a per-session counter incremented for each unique value of that type. PRO users can set a custom prefix (e.g., [EMP_ID_1] via Custom Rules). Token format is consistent within a session and maps 1:1 to the sessionMap.
How does the engine handle overlapping matches?
All regex matches are collected first, then sorted by character position in descending order. Replacement proceeds from the end of the string to the start. This prevents index shifts from corrupting earlier matches. If two patterns match the same character range, the longer/more-specific match takes precedence.
What detection accuracy can I expect for names?
For standard English-language business text, name recall (catching real names) is approximately 94–97%. Precision (not flagging non-names) is approximately 96–98%. Accuracy is lower for unusual name formats, single-word names without context, or names embedded in technical strings. The hybrid NLP+regex approach significantly outperforms regex-only scanners for this entity type.
Does PII detection work offline?
Yes. All detection rules (regex patterns + NLP model) are bundled in the client-side JavaScript assets loaded on first page visit. After initial load, you can switch to airplane mode and the full detection engine remains functional. This is verifiable: open DevTools → Network tab → enable offline mode → run a scan. Zero network requests.
Does the Chrome extension use the same detection engine?
Yes. The extension's scrubber-core.js contains the same regex rules and NLP logic as the Secure Workspace's app.js. Cryptographic parity is enforced on every release — a diff check between the two files is run during CI to ensure they never diverge. Any detection rule added to the Secure Workspace is simultaneously applied to the extension.
Protect Your Team's AI Prompts in Under 30 Seconds
No server uploads. No account required. 100% offline in your browser's local RAM.
