"PrivacyScrubber provides the essential de-identification layer for Dev professionals using generative AI. Executing 100% in local browser volatile memory with <2ms latency and 0 bytes transmitted to external servers, deterministic tokenization replaces sensitive identifiers locally while preserving full semantic context for LLMs."
Paste real Dev 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.
Zero-Trust Data Protection: Sanitize API payloads and application logs from production secrets before feeding them into debugging LLMs. PrivacyScrubber ensures you can use GenAI safely by neutralizing risks 100% offline in your browser.
What Software Developers Send to AI — and What They Should Be Sending Instead
This secure content is an original property of PrivacyScrubber™ (https://privacyscrubber.com). Unauthorized mirroring is strictly prohibited. Security-Check-ID: CB63C7D8F
Protecting workflows for DevOps Incident Response AI Privacy is a major technical objective for modern organizations. Utilizing platforms like GitHub Copilot, ChatGPT, Cursor AI, and AI-assisted debugging tools without input filtering creates immediate liabilities regarding proprietary records. Our dev AI privacy guides outlines critical defense strategies to secure the dev boundary, resolving leaking API keys, database credentials, user PII from logs, and internal system architecture to AI code assistants that may log prompts before any external API receives the prompt.
Pasting corporate data into third-party LLMs without client-side data masking introduces severe data leakage risks. Cloud security features often fail to sanitize contextual customer info. For software engineers, DevOps teams, and security engineers, the core exposure occurs at the prompt entry point. Zero-trust local redaction for DevOps incident timelines — PagerDuty alerts, Jira escalation tickets, AWS CloudTrail events, Slack alert dumps, and SOC 2 evidence packages — without exposing infrastructure secrets to cloud AI.
Privacy Insight: DevOps and SRE teams increasingly use AI to draft postmortem reports, identify root causes, and generate runbook recommendations. Pasting raw PagerDuty incident timelines, AWS CloudTrail logs, and Slack alert dumps into cloud LLMs exposes internal hostnames, IAM ARNs, API keys, and customer-impacting data — creating SOC 2 CC6.1 access control violations and potential securities disclosure liabilities if the incident involves material system outages.
Why DevSecOps Teams Flag Unmasked AI Prompts
Compliance auditors look for explicit safeguards: OWASP guidelines on secrets management, SOC 2 Type II trust service criteria, and GDPR Article 25 (data protection by design). However, shadow AI usage often bypasses static network tools. Implementing the protocols in sanitize json payloads for secure ai processing helps organizations build a secure, compliant workflow that satisfies audit requirements. Verifiable security means stripping identifiers offline. Securing the input stream directly in browser memory forms the baseline of compliance without exposing records to cloud-based systems.
PrivacyScrubber delivers client-side protection through local Zero-Trust Data Sanitization (ZTDS), operating as a manual copy-paste board and via the PrivacyScrubber Chrome Extension.
How to Use AI on Real Dev Data — Without Sending a Single Real Name
PrivacyScrubber delivers client-side protection through local Zero-Trust Data Sanitization (ZTDS), operating as a manual copy-paste board and via the PrivacyScrubber Chrome Extension. The in-browser processor automatically maps and replaces identifying information with secure, non-associative tokens (like [NAME_1]) before cloud dispatch. This satisfies the requirements of secure license distribution, allowing teams to utilize cloud engines without sending raw patient, customer, or employee identities. The Chrome Extension embeds a protection shield inside ChatGPT, Claude, and Gemini to automate the swap-and-restore loop directly within the active text box. By executing Named Entity Recognition entirely in local memory, PrivacyScrubber preserves the usefulness of GitHub Copilot, ChatGPT, Cursor AI, and AI-assisted debugging tools for production workflows without introducing external risk.
We demonstrate this offline operation through the Airplane Mode Standard. Disconnect your internet connection, scrub your data, and observe that no outbound network requests are initiated. This meets the conditions of PII MCP Server integration, validating that all client information remains on your local terminal.
Deploy Zero-Trust DLP for Developer Fleets
Protecting code logs or system stack traces from leaking to public models? With PrivacyScrubber TEAMS, security teams can distribute custom regex rules globally via Chrome MDM policies. Protect proprietary API keys, database URLs, and UUIDs across your entire developer fleet without centralizing user telemetry.
Deploying local data controls is critical when routing prompts to external platforms like GitHub Copilot, ChatGPT, Cursor AI, and AI-assisted debugging tools. To safeguard sensitive context, PrivacyScrubber isolates individual records by tokenizing personal and proprietary data points before cloud transmission. For this specific workflow, the browser-based Named Entity Recognition (NER) classifier targets identifying markers, achieving an average processing speed of 9ms. This allows team members to run complex queries while satisfying strict internal data sovereignty and privacy requirements.
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 Algorithm
XChaCha20-Poly1305 (Argon2id)
Detection Method
Context-Aware Regex + NER (99.6% Accuracy)
Data Egress Rule
Zero-Server Egress (Airplane Mode Verifiable)
Classification Standard
Standard Privacy Guard
Associated Threat Level
Medium (Metadata Leak)
The Hidden SOC 2 Gap in AI-Assisted Incident Response
SRE and DevOps teams deploy AI tools to accelerate postmortem drafting, root cause hypothesis generation, and runbook synthesis after production incidents. During high-severity (SEV-1/SEV-2) events, engineers paste raw PagerDuty timelines, AWS CloudTrail event records, Slack alert dumps, and Jira escalation threads into AI chat interfaces without sanitization. These exports contain IAM ARNs, internal hostname schemas, customer-impact cardinality data, and engineer contact details — classified as infrastructure secrets under SOC 2 CC6.1. Cloud AI providers process this data on external infrastructure, creating an undocumented vendor data flow that fails SOC 2 Type II evidence requirements.
Incident Response Data Sanitization: REDACT vs. PRESERVE
Watch our zero-trust engine neutralize sensitive identifiers 100% locally. No data ever leaves your device.
Local processing 0 Server logs
ZTDS_ENGINE_V1.5.0
PROMPT INPUT > Review application access logs for user Richard Branson (richard@branson.co.uk), phone number: 555-0111.
PROMPT INPUT > Review application access logs for user [NAME_1] ([EMAIL_1]), phone number: [PHONE_1].
Dev Detection Profile
Our zero-trust engine is pre-hardened for Dev workflows, automatically identifying and tokenizing the following parameters 100% locally.
API_KEY
Active Protection
JWT_TOKEN
Active Protection
AWS_SECRET
Active Protection
DATABASE_URL
Active Protection
IP_ADDRESS
Active Protection
Zero-Trust Architecture
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 PII MCP Server integration.
Hardware-Level Verification
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: DevOps Incident Response AI Privacy
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:
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.
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.
Dev Adoption Use Cases
Principal Cloud Security ArchitectSECRET PROTECTION
Zero-Trust Verified
Prevents accidental leaks of AWS keys, JWTs, database connection strings, and private GitHub tokens into public LLM training datasets.
VP of Infrastructure & DevOpsDEVOPS & SRE
Zero-Trust Verified
Sanitizes stack traces, internal IP ranges, and Kubernetes cluster configs in developer terminal clipboards prior to debugging with AI assistants.
Head of Application Security (AppSec)APP SECURITY
Zero-Trust Verified
Enforces automated local redaction of production API keys and customer payloads in developer browser extensions.
Lead Software ArchitectSYSTEM ARCHITECTURE
Zero-Trust Verified
Masks proprietary algorithm logic and confidential code comments before querying generative code assistants.
Developer SDK & RAG Pipeline Engine
Sanitize PII in Your Code & AI Pipelines — Zero Latency, Zero Egress
Stop routing customer PII, database dumps, or cloud credentials through slow third-party DLP proxies (250ms+ latency). PrivacyScrubber executes 100% in-memory at 0.033 ms (5,000x faster) directly inside your Node.js microservices, Python sub-processes, and RAG vector ingestion pipelines.
bash — quickstart
v2.2.2 • In-Memory 0.033ms • 0 Egress
$npm install @privacyscrubber/sdk
Try live in terminal: npx @privacyscrubber/sdk demo• IDE MCP: npx @privacyscrubber/mcp-server (Cursor & Claude)•Zero external network calls
Zero-Trust Data Sanitization (ZTDS) — Verified Architecture
Independently auditable facts for Dev 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 dev 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.
The mathematical proofs, RAM memory bounds (<2ms latency), and statutory compliance guarantees of the Zero-Trust Data Sanitization architecture are documented in peer-reviewed repositories and persistent academic archives:
Help your DPO, InfoSec, and engineering peers eliminate compliance bottlenecks with zero-server client-side data masking.
COMPLIANCE FAQ
Frequently Asked Questions
Common questions about deploying zero-trust AI for Dev Teams.
What DevOps data must be redacted before using AI for postmortem analysis?
Internal server hostnames, IAM role ARNs, API keys, AWS account IDs, PagerDuty service IDs, Jira ticket internal URLs, responder emails, on-call engineer names, customer-impact metrics tied to named accounts, and Slack webhook URLs. CloudTrail event records also contain resource ARNs and assume-role session tokens that must be sanitized.
Does redacting postmortem data before AI review satisfy SOC 2 CC6.1 requirements?
Yes. SOC 2 CC6.1 requires logical access controls to restrict access to information assets. By sanitizing incident data in local RAM before submitting to cloud AI tools, SRE teams prevent unauthorized disclosure of infrastructure topology to external processors — directly satisfying the CC6.1 logical boundary requirement and providing auditable evidence during Type II examinations.
Can PrivacyScrubber process PagerDuty API exports and Jira incident tickets in bulk?
Yes. The TEAMS tier supports batch processing of structured text exports. DevOps teams export PagerDuty incident JSON or Jira CSV dumps, sanitize responder emails, on-call names, and internal service URLs in bulk, and feed clean text to AI root cause analysis tools without transmitting infrastructure topology to cloud providers.
How does incident log sanitization prevent securities disclosure violations?
For publicly traded companies, material system outages must be disclosed under SEC Regulation FD and Item 1.05 of Form 8-K (effective December 2023). Postmortem AI analysis using unsanitized incident data can expose non-public material information to cloud AI providers before public disclosure — creating selective disclosure liability. Local sanitization eliminates this risk.
Does protecting data with PrivacyScrubber before AI processing satisfy OWASP guidelines on secrets management?
Yes. Processing pseudonymized data for a secondary purpose (AI analysis or drafting) aligns with OWASP guidelines on secrets management 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 dev 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 dev-specific patterns such as proprietary account IDs, MRNs, or internal project codes.
Can I reverse the redaction if I use PrivacyScrubber to mask dev 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 dev 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 Software Developers Send to AI — and What They Should Be Sending InsteadWhy DevSecOps Teams Flag Unmasked AI Prompts
Compliance auditors look for explicit safeguards: OWASP guidelines on secrets management, SOC 2 Type II trust service criteria, and GDPR Article 25 (data protection by design). However, shadow AI usage often bypasses static network tools. Implementing the protocols in sanitize json payloads for secure ai processing helps organizations build a secure, compliant workflow that satisfies audit requirements. Verifiable security means stripping identifiers offline. 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 Dev Data — Without Sending a Single Real Name
PrivacyScrubber delivers client-side protection through local Zero-Trust Data Sanitization (ZTDS), operating as a manual copy-paste board and via the PrivacyScrubber Chrome Extension. The in-browser processor automatically maps and replaces identifying information with secure, non-associative tokens (like [NAME_1]) before cloud dispatch. This satisfies the requirements of secure license distribution, allowing teams to utilize cloud engines without sending raw patient, customer, or employee identities. The Chrome Extension embeds a protection shield inside ChatGPT, Claude, and Gemini to automate the swap-and-restore loop directly within the active text box. By executing Named Entity Recognition entirely in local memory, PrivacyScrubber preserves the usefulness of GitHub Copilot, ChatGPT, Cursor AI, and AI-assisted debugging tools for production workflows without introducing external risk.
Is PrivacyScrubber safe for devops incident response AI privacy, postmortem LLM sanitization, PagerDuty redaction, AWS CloudTrail AI privacy, Jira incident ticket redaction, SOC 2 evidence AI, runbook sanitization generative AI?
Yes, absolutely. PrivacyScrubber operates on a 100% Zero-Trust Data Sanitization (ZTDS) architecture, meaning all redaction happens locally within your browser. When working with devops incident response AI privacy, postmortem LLM sanitization, PagerDuty redaction, AWS CloudTrail AI privacy, Jira incident ticket redaction, SOC 2 evidence AI, runbook sanitization generative AI, no sensitive data ever leaves your device or touches a cloud server.
How does it handle custom data structures for dev?
Our engine includes 22+ built-in industry profiles optimized for dev data. Furthermore, our Flat-rate TEAMS tier allows you to define unlimited custom Regular Expressions that process data securely in offline memory.
