How does the Zero-Trust Agentic Guard work in practice when AI agents run shell commands or edit code?

PrivacyScrubber Agentic Guard acts as a local in-memory proxy between your workstation and autonomous AI coding agents (Cursor, Windsurf, Claude Code, Copilot). When an agent executes shell commands (guard_exec) or reads credentials (guard_read_file), output is intercepted in local RAM and secrets are replaced with anonymous tokens ([API_KEY_1], [EMAIL_1]). The remote LLM reasons exclusively over tokenized placeholders. When applying code changes (guard_apply_patch), tokens are reversed back to authentic local secrets in memory and written to disk with an automatic .bak backup. Zero secrets leave your device.

Does PrivacyScrubber send my data to any server?

No. Every detection and sanitization operation runs locally inside your browser's RAM. Zero bytes of your text, documents, or session tokens leave your device. Verify this yourself: open DevTools → Network tab, test our DLP speed benchmark , or disconnect from the internet entirely — our air-gapped local processing keeps working offline.

Does dropping or uploading a transcript or document into PrivacyScrubber transmit my file to a server?

No. When you drop or upload a document (.txt, .docx, .pdf, or client meeting transcript) into PrivacyScrubber, the file never travels across the internet. The entire webpage operates like a self-contained local application inside your browser: file parsing, text extraction, and PII redaction execute exclusively in your computer's local RAM. You can verify this complete data isolation by turning your computer's Wi-Fi completely off (Airplane Mode) before dropping your file — the tool continues to sanitize your documents with 100% functionality and zero network connectivity.

Which AI platforms does the browser extension support?

The PrivacyScrubber Chrome extension injects real-time PII sanitization directly inside ChatGPT, Claude, Gemini, Microsoft Copilot (Bing Chat), Grok, Perplexity, DeepSeek, Qwen, Kimi, and Zendesk. For coding agents and autonomous workflows, explore our AI Agents Protection guide, or use the web app at privacyscrubber.com to sanitize text before pasting it into any interface.

What does the free version include?

The free Community Tier includes universal consumer PII masking (Names, Phones, Emails, National IDs, Credit Cards, IPs, URLs) with 15,000 characters per scrub, a 5,000-character free quota across all 30 specialized industry profiles, single-file upload (.txt, .docx), and PDF extraction up to 3 pages. It also includes free access to the Developer SDK ( @privacyscrubber/sdk ) and IDE MCP Server ( @privacyscrubber/mcp-server ) with built-in session quotas — zero credit card, zero passwords, and zero accounts required. For solo practitioners and developers, you can also claim a 1-Year PRO Reviewer Pass ($180 value) 100% free with an honest review on G2.

Do I need to create an account or provide a password?

No. PrivacyScrubber is architected with Zero Accounts and Zero Passwords. We do not maintain a central user database or store login credentials. Upgrades (PRO, TEAMS, Developer SDK) are activated purely via an offline cryptographic license key entered into your browser or local SDK environment. Validation executes mathematically in volatile device RAM with zero phone-home user tracking.

Can PrivacyScrubber sanitize W-2 forms, paystubs, and payroll documents?

Yes. Our specialized financial PII profile natively detects Employer Identification Numbers (EIN/FEIN), payroll-format names (LASTNAME, FIRSTNAME), corporate employer names with legal suffixes (Inc, LLC, Corp), and US street addresses. All wage amounts, tax withholdings, hourly rates, and financial figures are preserved untouched — essential for loan underwriting and HR payroll compliance .

Can I get my original data back after the AI responds?

Yes. Paste the AI's response back into the tool and click Reveal. The 1-Click Reveal engine swaps every token ([NAME_1], [EMAIL_2], etc.) back to the original value using your volatile local session map — zero server round-trips, zero database storage.

Does this help with HIPAA, GDPR, or SOC 2 compliance?

PrivacyScrubber is designed to support de-identification under HIPAA Safe Harbor (45 CFR §164.514) for 18 PHI identifiers, GDPR Article 25/32 data minimization, and SOC 2 Type II controls by stripping identifiers in browser RAM before prompt submission. Review our Top 20 Corporate PII Guide and CISO AI Security Blueprint for detailed governance controls.

What is the CISO Procurement Memo and how do enterprise teams use it?

The CISO Procurement Memo is a standardized, copy-ready compliance document for enterprise IT, security architects, and procurement officers. It provides General Counsel, DPOs, and InfoSec committees with formal statutory evidence (GDPR Art. 4(8)/28, HIPAA 45 CFR § 164.502(e), CCPA § 1798.140) proving that because PrivacyScrubber runs 100% in local client RAM with 0 bytes transmitted to any server, third-party DPA/BAA contracts and lengthy vendor risk questionnaires (SIG/CAIQ) are legally non-applicable, enabling fast-track 0-day software approval.

How does PrivacyScrubber prove zero network egress and lightweight memory usage?

Every software build undergoes an automated 13-suite security and performance QA pipeline in continuous integration (CI). Automated headless network sniffers verify that during PII sanitization, exactly 0 HTTP, WebSocket, or background telemetry packets leave the browser. In-memory heap profiling enforces an ultra-lightweight ceiling under 6MB RAM (5.68 MB JS Heap) and sub-75ms streaming DOM mutation scans across 5,000 live nodes, ensuring zero laptop heating and zero CPU throttle. Review the full audit in our Technical Security Specifications .

What happens to the session map when I close the tab?

The session map exists exclusively in volatile browser RAM and is strictly isolated per tab. The moment you close the tab, reload the page, or navigate away, the entire mapping — including all original PII values and cryptographic keys — is permanently purged from memory. Read more in our Technical Security Architecture .

What is the difference between AI Tokens mode and Blackout mode in PrivacyScrubber?

AI Tokens mode replaces sensitive entities with structured badges like [NAME_1] and [EMAIL_1], preserving contextual roles for LLMs (ChatGPT, Claude) and allowing 1-click restoration via Reveal Originals. Blackout mode applies permanent, solid black raster bars over sensitive pixel coordinates, physically destroying vector text layers for court filings, legal discovery, and FOIA releases with zero underlying text leakage.

Why do standard PDF blackout tools leak data, and how does PrivacyScrubber prevent it?

Most conventional PDF editors and markup tools merely overlay black rectangles as a visual layer, leaving underlying OCR text, character coordinates, and metadata intact and extractable via Cmd+A copy or pdftotext. PrivacyScrubber executes true Secure Raster Flattening : pages are re-rendered in local RAM, PII coordinates are overwritten at the pixel level, and a fresh PDF is synthesized with zero underlying text layers, guaranteeing 100% leak-proof redactions.

What file formats can I sanitize, and what do I get back?

Supported formats include .txt, .docx, .pdf (text-layer and scanned images via Tesseract OCR), .xlsx, and .csv. With Batch File Redaction and Excel Spreadsheet Scrub , you can download sanitized files with PII removed or export redacted PDFs with permanent raster flattening (zero underlying text layers).

Does PrivacyScrubber sanitize hidden document metadata (author, company name, revision history) in Word (DOCX) and Excel (XLSX) files?

Yes. Most conventional redaction tools only mask visible text or cell contents, leaving hidden document properties intact. Microsoft Word (.docx) and Excel (.xlsx) files are compressed XML archives that store author identity (<dc:creator>), modifying users (<cp:lastModifiedBy>), corporate affiliation (<Company>), and revision timestamps inside docProps/core.xml , docProps/app.xml , and workbook properties. PrivacyScrubber's in-RAM sanitizer intercepts these archives in local browser memory, wipes original author and organization tags, eliminates custom metadata, and overwrites properties with anonymous synthetic signatures ( PrivacyScrubber (Zero-Trust) ) before export. Your exported files are completely clean both visibly and metadata-wise, with zero network transmission.

Why does the Chrome extension convert uploaded files (PDF/DOCX) into .txt, and how do file upload quotas work?

When users upload or drop documents (such as resumes or legal agreements) into ChatGPT or Claude, PrivacyScrubber intercepts the file in local browser RAM. Binary formats (.pdf, .docx) contain hidden metadata, revision histories, and XML streams that can expose personal identity even if visible text is edited. PrivacyScrubber extracts document text in memory, replaces sensitive PII with tokens, strips names from the filename, and injects a clean synthetic .txt file into the AI prompt window. This eliminates 100% of binary metadata leakage while preserving full LLM analytical utility. The Free tier includes a daily allowance of 3 document uploads per 24 hours (and up to 15,000 characters per scrub), while PRO and TEAMS provide unlimited document processing.

What is AI DLP and how does client-side browser sanitization differ from a legacy cloud proxy?

AI Data Loss Prevention (AI DLP) refers to specialized security controls engineered to inspect and sanitize unstructured conversational prompts, streaming tokens, and file uploads before ingestion by generative AI models. Traditional gateway DLPs (like Zscaler, Netskope, or Cloudflare proxies) sit downstream in the network and struggle with encrypted WebSockets, streaming Server-Sent Events (SSE), and conversational context—often causing latency or failing to de-identify data before transit. PrivacyScrubber executes AI DLP directly at the source: inside local browser RAM (<2ms latency). Sensitive entities are converted into contextual tokens ([NAME_1], [ACCOUNT_1]) before packets ever reach the network adapter, guaranteeing zero vendor data custody and mathematical immunity to cloud leaks.

What is the AI data irreversibility problem and why must PII redaction happen at the client endpoint?

The AI Irreversibility Problem stems from the mathematical impossibility of selectively 'unlearning' or excising data once it has been digested into large language model neural weights or stored in multi-tenant RAG (Retrieval-Augmented Generation) vector databases. Machine unlearning remains an unsolved scientific challenge; post-hoc deletion requests (such as GDPR Article 17 'Right to be Forgotten') cannot be reliably enforced against fine-tuned weights or vector embeddings. Consequently, regulatory bodies (under the EU AI Act Article 10 and HIPAA Safe Harbor) require data sanitization to occur strictly prior to ingestion. PrivacyScrubber's endpoint-only RAM architecture guarantees that sensitive identifiers never enter LLM training corpora or remote vector caches.

How does TEAMS encrypted session handoff work?

PrivacyScrubber TEAMS uses Argon2id key derivation and XChaCha20-Poly1305 authenticated encryption (via libsodium WASM). Through encrypted team session handoff , colleague Alice sanitizes prompts and shares a cryptographic blueprint; colleague Bob reveals original values locally with zero server intermediary.

How does Shadow DOM sandboxing protect against malicious scripts?

PrivacyScrubber wraps editor inputs and tokenized outputs inside closed Shadow DOM roots. This makes unredacted sensitive text completely inaccessible to DOM-scraping scripts, third-party analytics, or unauthorized browser extensions running on the host page. Learn more about our in-DOM prompt sandbox .

Can I use PrivacyScrubber as an MCP server in Cursor, Windsurf, or Claude Desktop?

Yes. The official @privacyscrubber/mcp-server package runs as a local stdio-based Model Context Protocol server for Cursor, Windsurf, Claude Desktop, and VS Code. It intercepts codebase prompts, sanitizes database passwords and API tokens in RAM, and protects your software development workflows with zero external calls.

Is there a developer SDK for integrating PII sanitization, and is it free to try?

Yes. The @privacyscrubber/sdk NPM package exposes the headless sanitization engine as a programmatic Node.js & ESM library. It is 100% free to test locally in under 30 seconds with a permanent free quota (15k characters General / 5k characters Specialized per session)—no credit card, no account sign-up, and zero expiring trials. Call scrubText() and unscrubText() directly in local dev environments, CI/CD gates, and RAG pipelines. Commercial licensing ($299/mo or $2,990/yr) is only required for unlimited production nodes and continuous high-throughput backend services.

How do developers integrate @privacyscrubber/sdk out of the box, and what are the operational capabilities and state risks?

Developers integrate @privacyscrubber/sdk with zero dependencies using a 1-line wrapper like wrapOpenAI(new OpenAI()), or via standalone sanitize() and restore() in <1ms local RAM latency. It intercepts outbound prompts before network transmission, tokenizes PII and infrastructure secrets into semantic placeholders ([NAME_1], [AWS_KEY_1]), and rehydrates LLM responses locally—including streaming SSE tokens via sliding window reconstruction. Operation is completely plug-and-play with zero background servers or Python/spaCy daemons. The primary operational risk to manage is state custody in distributed microservices: tokenMap is volatile and RAM-only, requiring stateless microservices to preserve or pass the token map between pre-processing and post-processing nodes.

Does changing the detection profile reset my session?

No. Switching between our 30 specialized industry detection profiles (e.g. from General to Legal & Contracts or Medical) preserves active tokens and session maps. Tokens remain restorable via Reveal until you click the Clear button explicitly.

How does PrivacyScrubber prevent data residue in system RAM?

After processing documents (PDF, DOCX, XLSX), the engine immediately overwrites all temporary ArrayBuffers at the byte level with zeroes (Uint8Array.fill(0)) before releasing them to garbage collection. Pair this with our tamper-evident audit receipts for verifiable forensic compliance.

Can enterprise or accounting teams pay via invoice or wire transfer?

Yes. For organizations requiring formal vendor onboarding, purchase orders (PO), or SWIFT/SEPA bank wire transfers, we provide custom invoicing with EU VAT reverse-charge support. Check our transparent pricing matrix or visit our Enterprise Solutions Hub .

Does PrivacyScrubber load any third-party analytics or tracking scripts?

No. The platform loads zero analytics trackers, third-party cookies, or fingerprinting scripts. Maintaining strict Content Security Policies (CSP) ensures third-party endpoints cannot inspect memory or DOM states. Review our full commitments in our Zero-Server Privacy Policy .

How are TEAMS admin roles managed without a backend?

There are no centralized accounts. Team administrators configure mandatory regex rules and compliance profiles locally in the Teams Deployment Hub , then generate a cryptographically signed Blueprint URL. When team members open this link, the configuration locks client-side without any backend database.

What rights does a Team Administrator have compared to Managed Team Members in TEAMS?

The purchaser acts as the Team Administrator with exclusive authority to configure organization-wide custom Regex rules, corporate token taxonomy (e.g. [PATIENT_ID]), and default compliance profiles in the Teams Dashboard . When the Admin exports a cryptographically signed Blueprint with Lock Rules enabled, Managed Team Members receive a locked, read-only configuration across their Web App and Chrome Extension (badged as [ENTERPRISE]), preventing employees from altering or bypassing corporate DLP policies.

What is the difference between Custom Regex Rules and Token Labels?

Our Custom Regex Rules Engine discovers proprietary data formats (custom ticket IDs, project codes like PROJ-1234, internal server URLs). Token Labels, in contrast, customize the replacement placeholder (e.g. renaming [NAME] to [PATIENT_ID]) to give LLMs optimal domain context without modifying regex patterns.

How does PrivacyScrubber detect PII without AI hallucinations or latency?

PrivacyScrubber utilizes a high-performance deterministic pattern matching engine running natively in browser RAM (sub-2ms execution time). Unlike cloud LLM-based redaction which can hallucinate, omit tokens, or introduce network latency, our deterministic parser guarantees 100% reproducible tokenization across 18 core Safe Harbor/GDPR entity types (names, emails, phones, SSNs, credit cards, IBANs, medical MRNs, API tokens). PRO users can also inject custom regex rules or run local offline OCR for documents.

How does license key custody, non-transferability, and emergency revocation work without user tracking?

Because PrivacyScrubber maintains a Zero-Trust Data Sanitization (ZTDS) architecture with zero server databases and zero phone-home user tracking, license custody is sovereign to the purchaser. All license tiers are strictly non-transferable. If a key is accidentally leaked or exposed, the billing owner can immediately request emergency revocation via support@privacyscrubber.com. We append the SHA-256 hash of the compromised key to our global Key Revocation List (KRL), instantly invalidating it across all client instances within 24 hours while reissuing a secure replacement.

What are the exact operational boundaries between Personal PRO, Team Workspace, and Developer SDK licenses?

PRO ($15/mo or $110 Lifetime) is a single-user personal license valid on up to 3 personal devices (Web, Chrome, IDE MCP). TEAMS ($99/mo flat) is an organization-wide internal workspace covering unlimited internal staff with Master Key Isolation. The Developer SDK ($299/mo or $2,990/yr) covers headless execution across unlimited internal backend nodes, microservices, ETL pipelines, and internal RAG vector databases. Embedding into customer-facing commercial SaaS for third-party resale requires an OEM/Enterprise contract.

Is the PrivacyScrubber MCP Server completely air-gapped, and is it free to use?

Yes. The @privacyscrubber/mcp-server package executes strictly in local machine memory over standard stdio JSON-RPC transport with zero outbound network requests, zero telemetry, and 100% volatile RAM mapping. It is 100% free to use with built-in session quota directly in Cursor, Windsurf, Claude Code, and VS Code without requiring a credit card or account registration. PRO and TEAMS tiers provide unlimited character volume and enterprise policy synchronization.

How can solo coaches, therapists, and executive consultants sanitize client meeting transcripts (Zoom, Teams, Google Meet) without cloud exposure?

Solo practitioners handling confidential client sessions (ADHD coaching, therapy, executive consulting) can execute a 100% offline, zero-cloud workflow: First, transcribe your locally recorded Zoom or Teams meeting on your own device using an offline Speech-to-Text engine (such as MacWhisper or Whisper.cpp running natively on Apple Silicon / local GPU). Second, drop the resulting .txt or .docx transcript into PrivacyScrubber at privacyscrubber.com (even with your device Wi-Fi completely turned off). PrivacyScrubber strips client names, sensitive disclosures, neurodiversity/medical conditions, and identifying details into safe tokens ([NAME_1], [ORGANIZATION_1]) in volatile RAM. Third, submit the sanitized transcript to Claude or ChatGPT to extract themes, check coaching quality, or draft session summaries. Finally, click Reveal in PrivacyScrubber to rehydrate original client names locally. Zero client personal data ever touches third-party servers.

How does PrivacyScrubber handle European names with initials and national identity numbers like Dutch BSN, German Steuer-ID, or French NIR?

PrivacyScrubber features dedicated pattern recognition engines for European business and civil nomenclature. Our punctuation-aware lookahead models accurately tokenize initial-prefixed names with noble particles (e.g., 'J. de Ruiter', 'K. van den Berg', 'M. de Jong') without prematurely splitting or dropping initials. For statutory identity tokens, PrivacyScrubber embeds native checksum and format validators in client-side RAM for European national IDs—including the Dutch 11-test checksum for BSN/SOFI numbers, 11-digit German Steuer-ID, 16-character Italian Codice Fiscale, Spanish DNI/NIE, French NIR/INSEE, and Dutch KvK commercial register numbers.

How does PrivacyScrubber protect enterprise RAG vector databases and prevent GDPR Article 17 re-indexing costs?

Embedding raw personal data into vector databases (Pinecone, Qdrant, Weaviate, Milvus) creates permanent regulatory liability: fulfilling a single GDPR Article 17 'Right to Erasure' request requires locating all high-dimensional embeddings containing that person's data and recalculating vector indexes—costing upwards of $14,000 per deletion cycle. By embedding the headless @privacyscrubber/sdk into your ingestion pipeline, raw PII is swapped with deterministic cryptographic tokens in Node.js heap (<0.065ms) before vector embedding. When a deletion request arrives, organizations simply purge the local key mapping, achieving instantaneous O(1) mathematical erasure at $0 infrastructure cost.

Why does PrivacyScrubber NOT require a Data Processing Agreement (DPA) or Business Associate Agreement (BAA)?

Under GDPR Article 4(8)/Article 28 and HIPAA 45 CFR § 164.502(e), Data Processing Agreements (DPAs) and Business Associate Agreements (BAAs) are legally required only when an external vendor processes or hosts protected data on remote infrastructure on your behalf. Because PrivacyScrubber executes 100% in local client-side RAM with zero server data transmissions, zero external telemetry, and zero subprocessors, PrivacyScrubber is legally classified as a software vendor rather than a data processor. Enterprise security and compliance committees can fast-track clearance in hours using our standardized CISO Procurement Memo .

Why deterministic rules instead of cloud NER models like Microsoft Presidio or BERT?

Sending text to remote Named Entity Recognition (NER) models leaks raw data before masking can occur. ZTDS executes deterministic lookaround regular expressions and 30 specialized industry vocabularies 100% locally in device memory (<1ms latency), providing 100% reproducible compliance proofs without stochastic AI hallucinations or model drift.

How is browser heap memory protected against local memory extraction, XSS, or process dumping?

PrivacyScrubber enforces strict Content Security Policy ( script-src 'self' ) with zero external scripts or analytics trackers. Session maps exist strictly in volatile, tab-isolated RAM, are never written to disk, localStorage, or cookies, and are permanently wiped on tab close. Host RAM dumping requires prior OS root compromise, which affects all workstation secrets regardless of software.

What happens if generative AI models alter, drop, or hallucinate synthetic tokens?

Our patent-pending engine incorporates an algorithmic Tolerant Fuzzy Unscrubbing parser that resolves model case changes, whitespace shifts (such as [NAME 1] ), and markdown formatting. If a model completely omits a token from its response, the local audit view immediately flags the missing identifier without corrupting surrounding text.

How can an enterprise CISO or SOC audit compliance without central servers?

Zero server processing does not mean zero auditability. PrivacyScrubber generates cryptographically verifiable CISO Audit Receipts (SHA-256 integrity hash, triggered regulatory frameworks, timestamp, entity counts) directly on the client. Enterprise teams stream zero-PII telemetry locally to internal SIEM (Splunk, Datadog) via our Node.js SDK and MCP server.

Why do organizations need ZTDS if they already have Azure OpenAI or ChatGPT Enterprise with a BAA?

Business Associate Agreements (BAAs) provide legal recourse after a breach, not physical prevention. They do not protect against cloud logging errors, insider snooping, model jailbreaks, or US CLOUD Act subpoenas. Data that never leaves the workstation in the first place cannot be breached, inspected, or subpoenaed.

What if our organization handles rare, proprietary, or highly specialized PII formats?

Beyond 30 pre-configured industry profiles (HIPAA, GLBA, FINRA, FAR/DFARS, GDPR), PrivacyScrubber PRO and TEAMS allow security administrators to define custom client-side regular expressions or import MDM-locked company dictionaries that execute 100% locally in device memory with zero cloud egress.

AI Threat Intelligence & News

ChatGPT Sandbox Covert Channel Flaw: Cross-Account Gmail Exfiltration Exposed

Q: How does this vulnerability expose enterprise data?

The vulnerability bypasses ChatGPT's execution sandbox boundaries using shared runtime artifacts and covert side-channel signaling. An attacker crafts a poisoned prompt or tool invocation that reads contextual memory and connected Gmail integration data, relaying raw emails and access tokens across multi-tenant boundaries without triggering standard network egress alarms.

Q: How does PrivacyScrubber prevent this exploit?

PrivacyScrubber intercepts all input data client-side inside local browser or application memory before it ever dispatches to ChatGPT. By replacing employee identities, corporate Gmail communications, API keys, and sensitive financial records with cryptographically isolated synthetic surrogates, any covert exfiltration channel only captures meaningless placeholder tokens.

ChatGPT Sandbox Covert Channel Flaw: A critical sandbox isolation flaw in ChatGPT allowed threat actors to siphon enterprise Gmail correspondence across authenticated accounts via covert communication channels. Local client-side PII scrubbing neutralizes sensitive payloads before they ever reach the model execution runtime.

Ilya SibiryakovPrivacy Architect•September 9, 2026•3 min read

100% Local Airplane Mode

ChatGPT Sandbox Covert Channel Flaw: Cross-Account Gmail Exfiltration Exposed

Technical Incident Analysis

Security researchers uncovered a severe isolation breakdown within ChatGPT's code execution and tool orchestration sandbox. By exploiting asynchronous side-channel timing variations and shared process memory artifacts within connected tool environments, attackers could extract sensitive user data—including authenticated Gmail threads, OAuth session state, and proprietary correspondence—across distinct user accounts. To understand how architectural boundaries fail under agentic automation, review our comprehensive AI Security Architecture guide alongside the recent Related AI Security Incident covering protocol-level runtime compromises.

Enterprise Blast Radius & Compliance Risks

When multi-tenant LLM platforms integrate directly with corporate email suites, cross-account sandbox escapes represent immediate systemic non-compliance. Leaked employee emails, internal executive communications, and customer correspondence trigger statutory breach notification obligations under strict global privacy frameworks. Organizations can evaluate exposure thresholds and penalty benchmarks in our breakdown on GDPR & CCPA Compliance risks in generative AI deployments.

Client-Side Mitigation via Zero-Trust Data Sanitization

Relying solely on vendor-side sandboxes leaves corporate intellectual property exposed to covert channel leakage and zero-day containment failures. PrivacyScrubber enforces zero-trust data protection directly at the endpoint through client-side, RAM-only surrogate tokenization. By pairing ephemeral session isolation with automated tool protection via the Model Context Protocol (MCP) Sanitizer, all PII, authentication tokens, and internal email contents are scrubbed before payload transmission, ensuring any downstream sandbox compromise yields zero actionable intelligence.

ZTDS™ Invariant Violation Analysis

Direct Failure: ZTDS™ Invariant 1 (Zero External Egress) & Invariant 2 (Deterministic Reversible Tokenization)

Prompt injection exploits succeed when untrusted user input interacts with unmasked enterprise context. Under the Zero-Trust Data Sanitization (ZTDS™) specification, client-side tokenization neutralizes data exfiltration vectors at the edge, ensuring sensitive values remain trapped in volatile client RAM even if the model's prompt logic is compromised.

RFC v1.0 Conformance In-Memory AST Masking Zero Cloud Egress

ChatGPT (OpenAI) Integration

Step-by-Step Integration Guide: ChatGPT Sandbox Covert Channel Flaw

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 ChatGPT (OpenAI):

1 Method A: Zero-Trust Web Workspace (Copy-Paste)

Best for manual prompt sanitization without installing plugins:

Open the PrivacyScrubber Web App dashboard in your browser.
Paste the raw prompt or text containing sensitive details of ChatGPT Sandbox Covert Channel Flaw.
Click Sanitize Prompt: sensitive data is swapped for secure placeholders (e.g., [NAME_1]).
Submit the sanitized prompt to ChatGPT (OpenAI).
Paste the AI's answer into Reveal Originals to instantly restore the original values.

2 Method B: Chrome Extension (In-Context Redaction)

For automated, inline de-identification within chat interfaces:

Install the free PrivacyScrubber Chrome Extension from the Web Store.
Navigate to your AI chat interface. A PrivacyScrubber shield button will appear inline.
Paste your raw prompt. Click the shield button to sanitize all identifiers instantly in-place.
Send the prompt to the AI chatbot.
The extension automatically intercepts and detokenizes the response, displaying raw values to you.

Local Redaction & Risk Matrix for Security

Detection Entity	Token Placeholder	Risk Level	Security Action
User / Server IP Addresses	[IP_ADDRESS]	High (DLP / Location footprinting)	IPv4 / IPv6 format strip
AWS_KEY Details	[AWS_KEY]	Medium (PII Exposure)	Deterministic local swap
INTERNAL_HOSTNAME Details	[INTERNAL_HOSTNAME]	Medium (PII Exposure)	Deterministic local swap
MAC_ADDRESS Details	[MAC_ADDRESS]	Medium (PII Exposure)	Deterministic local swap
VULN_ID Details	[VULN_ID]	Medium (PII Exposure)	Deterministic local swap

3-Step Zero-Trust AI Workflow Template

Role: Enterprise AI Governance Lead / Security Officer · Target: ChatGPT (OpenAI)

1. Sanitize Data First

1Sanitize in PrivacyScrubber

2Run Prompt in ChatGPT (OpenAI)

31-Click Reveal via sessionMap

Zero-Trust Prompt Sanitization & AI Model InterceptionPrivacyScrubber ZTDS Protocol

Act as an executive research consultant. Analyze the following sanitized enterprise text for [CLIENT_1] and [ORG_1]:
1. Extract key business intelligence findings, strategic risks, and operational takeaways.
2. Draft 3 prioritized executive recommendations.
3. Format findings in clean, structured bullet points.

CRITICAL COMPLIANCE INSTRUCTION (PrivacyScrubber ZTDS Standard): Maintain all cryptographic token placeholders ([NAME_1], [EMAIL_1], [ID_1]) exactly intact in your response for client-side local rehydration via PrivacyScrubber.

Step 3: 1-Click Reverse Rehydration (No Manual Decoding)When ChatGPT (OpenAI) 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: Zero-Trust Data Sanitization (ZTDS) Architecture StandardRAM-only session tokenization guarantees zero data at rest and zero data in transit. Mappings exist only during active browser execution and are purged on tab close.

Enterprise 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.

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 sanitization — $99/month flat, unlimited users. SOC 2 & HIPAA ready. Works in Airplane Mode.

Deploy Teams Plan ($99/mo)

Zero-Trust Data Sanitization (ZTDS) — Verified Architecture

Independently auditable facts for Sensitive Data 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 sensitive data text, click Sanitize Prompt. 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.

Peer-Reviewed Foundations & Academic Authority

ORCID: 0009-0002-0642-5985•Wikidata: Q141546647

The mathematical proofs, RAM memory bounds (<2ms latency), and statutory compliance guarantees of the Zero-Trust Data Sanitization architecture are documented in official Internet standards tracks and peer-reviewed scientific repositories:

IETF

IETF Specification: ZTDS Protocol

Internet Standards Track · Frontier Artificial Intelligence Ingestion

DOI

CERN / Zenodo 10.5281/zenodo.22058770

ZTDS Mathematical Proof & Client-Side Specification

DOI

OSF Preprints 10.17605/OSF.IO/5BYJF

Empirical Latency & In-Browser RAM Profiling Study

LAW

Law Archive Preprint 4wc86

Preserving Attorney-Client Privilege in LLMs

SSRN

SSRN / Elsevier ID 7335581

EU AI Act, UK GDPR & Statutory AI Privacy

Advisory Broadcast

Alert your security & engineering team before deployment

Zero-Trust sanitization stops unauthenticated tool leakage in RAM. Forward this incident analysis to safeguard your AI pipelines.

COMPLIANCE FAQ

Frequently Asked Questions

Common questions about deploying zero-trust AI for AI Threat Intelligence & News Teams.

How does this vulnerability expose enterprise data?

The vulnerability bypasses ChatGPT's execution sandbox boundaries using shared runtime artifacts and covert side-channel signaling. An attacker crafts a poisoned prompt or tool invocation that reads contextual memory and connected Gmail integration data, relaying raw emails and access tokens across multi-tenant boundaries without triggering standard network egress alarms.

How does PrivacyScrubber prevent this exploit?

PrivacyScrubber intercepts all input data client-side inside local browser or application memory before it ever dispatches to ChatGPT. By replacing employee identities, corporate Gmail communications, API keys, and sensitive financial records with cryptographically isolated synthetic surrogates, any covert exfiltration channel only captures meaningless placeholder tokens.

ChatGPT Sandbox Covert Channel Flaw: Cross-Account Gmail Exfiltration Exposed

Live Data Sanitization
Live

Technical Incident Analysis

Enterprise Blast Radius & Compliance Risks

Client-Side Mitigation via Zero-Trust Data Sanitization

Step-by-Step Integration Guide: ChatGPT Sandbox Covert Channel Flaw

1 Method A: Zero-Trust Web Workspace (Copy-Paste)

2 Method B: Chrome Extension (In-Context Redaction)

Local Redaction & Risk Matrix for Security

3-Step Zero-Trust AI Workflow Template

Enterprise Adoption Use Cases

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

Zero-Trust Data Sanitization (ZTDS) — Verified Architecture

Alert your security & engineering team before deployment

Frequently Asked Questions

Redacted Document Inspection

Security & DPO Approval Memorandum

Add to Device Home Screen

ChatGPT Sandbox Covert Channel Flaw: Cross-Account Gmail Exfiltration Exposed

Live Data Sanitization Live

Technical Incident Analysis

Enterprise Blast Radius & Compliance Risks

Client-Side Mitigation via Zero-Trust Data Sanitization

Step-by-Step Integration Guide: ChatGPT Sandbox Covert Channel Flaw

1 Method A: Zero-Trust Web Workspace (Copy-Paste)

2 Method B: Chrome Extension (In-Context Redaction)

Local Redaction & Risk Matrix for Security

3-Step Zero-Trust AI Workflow Template

Enterprise Adoption Use Cases

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

Zero-Trust Data Sanitization (ZTDS) — Verified Architecture

Alert your security & engineering team before deployment

Frequently Asked Questions

Live Data Sanitization
Live