Prevent AI Agent Prompts from Leaking PII into Vector Stores
AI Summary / Key Takeaways
"Secure your autonomous AI agent pipelines (Make.com, Zapier, LangChain) at the input boundary. PrivacyScrubber's zero-trust engine tokenizes sensitive data locally before it enters your RAG vector stores or LLM context windows, preventing permanent PII leakage into agentic memory."
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.
Enterprise-Grade AI Privacy
Add custom redaction rules and priority support with PRO.
Verified by the Enterprise Board
Our multi-persona AI safety team ensures strict compliance and zero-server security at every layer.
"PrivacyScrubber eliminates Shadow AI risk by intercepting PII at the edge. We've mapped this hub to SOC 2 Type II CC6.7 and ISO 27001 A.8.11 masking controls."
"Under GDPR Article 25 (Privacy by Design) and HIPAA Safe Harbor, local anonymization removes the AI provider from the 'Data Processor' chain, negating complex DPA liabilities."
"A single GLBA or PCI-DSS violation costs 100x more than a site-wide license. We provide verifiable ROI through data loss prevention at the prompt level."
The Autonomous Pipeline Privacy Gap
Make/Zapier Webhook Leaks
Automation nodes often pass raw CRM data, customer tickets, or email outputs directly to external AI LLM APIs, exposing sensitive customer PII to cloud vendor logging and storage.
RAG Vector Store Poisoning
Loading un-masked corporate documents, wikis, and transcripts into vector databases for RAG (Retrieval-Augmented Generation) creates permanent, indexed caches of sensitive employee and client data.
Autonomous Secret Exposure
Coding and DevOps agents (Cursor, Claude Code, custom CLI tools) consuming local codebases and config files frequently leak database credentials, architectural secrets, and private API keys to third-party models.
Raw Input: Process customer record Jane Doe (ID: 981-22-3021) at jane@doe.com
Sanitized: Process customer record [NAME_1] (ID: [ID_1]) at [EMAIL_1]
Secure Agent Architecture
Modular, client-side data protection for autonomous AI systems and workflows.
Intercept Payload
Before triggering any AI execution step, capture the raw prompt or text context locally at the orchestration layer.
Local Masking
PrivacyScrubber analyzes the payload inside browser memory, substituting customer identities and secrets with structured tokens.
Secure LLM Call
Submit the anonymized payload to your LLM API. The model processes the logic perfectly without seeing raw identities.
Reverse Scrub
Once the agent responds, swap the tokens back to their original values locally before displaying the output to users.
The Dilemma of Agentic Memory: Persistent Privacy Liabilities
Traditional LLM interactions are ephemeral: a user inputs a query, the model returns an answer, and the session terminates. However, the next paradigm of artificial intelligence relies on autonomous agents. Tools like LangChain, AutoGPT, CrewAI, and n8n pipelines operate in continuous execution loops, maintaining state through SQLite databases, local caches, and vector index databases.
If an agent processes raw CRM strings or customer helpdesk records containing names, emails, account IDs, or financial metrics, those values are cached in intermediate logs and RAG (Retrieval-Augmented Generation) indexes. Once written into multi-step agent histories, removing PII becomes a complex, high-cost database operation. PrivacyScrubber solves this by enforcing Zero-Trust Data Sanitization (ZTDS) directly at the boundary of agent ingestion.
The Zero-Trust Data Sanitization (ZTDS) Blueprint
PrivacyScrubber acts as an offline, local validation gateway. Instead of passing unredacted database queries or user logs to your automation pipeline, you route inputs through our client-side Javascript engine. All personal identifiers are mapped to deterministic tokens, such as [NAME_1] or [EMAIL_1].
Because this mapping is stored exclusively in transient browser RAM (scoped strictly to the active tab), no cloud database is used. The external AI model processes only the logical relationships and context of the prompt:
// Sanitized prompt sent to agentic pipeline:
"Summarize the request from [NAME_1] ([EMAIL_1]) regarding order number [ID_1] and draft a response."
When the model completes the task, the output is returned to the client browser, and the Reverse Scrub (Reveal) utility re-injects the original records locally. The third-party LLM performs the reasoning, but the customer's identity remains completely secure on the local network.
Securing Model Context Protocol (MCP) & IDE Agents
Developers adopting tools like Claude Desktop, Cursor, Bolt, or Claude Code often connect them directly to their local databases and file structures via the Model Context Protocol (MCP). While this unlocks powerful automation capabilities, it opens a direct exfiltration vector. A coding agent asked to "debug database queries" can retrieve real production tables containing usernames, active API keys, and corporate secrets and transmit them back to model servers.
By running PrivacyScrubber's local engine, developers can sanitize logs and queries pre-flight. Sensitive keys, path structures, and user accounts are masked locally, ensuring developers can use Cursor and Claude Desktop safely without violating corporate governance rules.
Regulatory Compliance & Enterprise Governance
Deploying commercial AI agents without sanitization exposes organizations to significant compliance risks:
- GDPR Article 25 (Privacy by Design): Requires organizations to implement data minimization controls. Masking PII before it enters external models ensures that raw identities are never processed, removing the AI provider from the 'Data Processor' chain and eliminating DPA liabilities.
- SOC 2 Type II CC6.7: Enforces strict transmission security controls. Edge-based, zero-server tokenization ensures that unmasked confidential customer records are never in transit to external networks.
- HIPAA Safe Harbor Alignment: Automatically removes the 18 specific identifiers required for healthcare text sanitization, allowing support teams to summarize clinical details safely.
Protocol: The 5-Step Airplane Mode Audit
Do not take our word for it. Trust the physical rules of network isolation. Run this step-by-step audit to confirm that no data is transmitted during your scrubbing workflows.
Initialize Platform: Open PrivacyScrubber.com in your web browser.
Sever Network Connection: Disable your WiFi connection or turn on Airplane Mode. The local engine remains fully operational.
Scrub Payload: Paste a text payload containing sensitive PII and click "Protect PII".
Audit Network Requests: Press F12, open the 'Network' tab, and verify that zero requests were made to external servers.
Verify Transient Memory: Close or refresh the tab. All session mappings are instantly cleared from local RAM.
AI Agents & RAG Vector Profile: Detection Coverage
Privacy-by-Design ruleset for LangChain, AutoGPT, and RAG vector store developers. Prevents persistent indexing of PII in vector databases or agent memory logs.
Top 6 AI Agents Sensitive Entity Types Detected & Scrubbed
RAG Vector Store Key
Agent User Identifier
Context Session Token
Orchestration System Rules
Injected Vector PII Data
Retrieved Document Ref
Continuous Detection Engine Expansion & Custom Regex Sovereignty
The 6 entity types above represent the core detection baseline for AI Agents. Our zero-trust engine detects hundreds of additional data classes and is continuously updated with new heuristic patterns, shadow AI leak vectors, and custom regulatory rulesets. Need proprietary database IDs or internal project codenames masked? PRO and TEAMS users can define unlimited custom regular expressions running 100% locally in browser RAM.
How the PrivacyScrubber Engine Solves This
Interactive Tool Controls for AI Agents. Hover for specs.
Local MCP Prompt Gateway
Connect the PrivacyScrubber MCP Server to Cursor and Claude Desktop to sanitize agent prompts in RAM before external LLM dispatch.
- Engine WASM-Accelerated
- Privacy 100% Local RAM
- Security Zero-Server Leak
Pre-Flight Vector Sanitization
Tokenize sensitive entity strings before they enter LangChain, AutoGPT, or RAG vector stores, preventing permanent vector database contamination.
- Engine WASM-Accelerated
- Privacy 100% Local RAM
- Security Zero-Server Leak
Deterministic Reverse Scrub
Once the autonomous agent resolves the task, restore original identities locally on your machine with 1-click Reveal.
- Engine WASM-Accelerated
- Privacy 100% Local RAM
- Security Zero-Server Leak
AI Agents Compliance Library
Step-by-step redaction workflows for AI Agents environments.
Claude Desktop Local PII Sanitization
Secure your Claude Desktop workflows. Intercept and sanitize sensitive prompts locally before they reach Anthropic servers, ensuring zero-trust compliance. Includes Flat-rate TEAMS pricing and Zero-server architecture.
Zero-Trust Data Sanitization for Model Context Protocol (MCP) Workflows
Secure Claude Desktop, Cursor, and custom AI agents using Model Context Protocol (MCP). Sanitize sensitive file paths, logs, and database queries locally before model transmission. Includes Flat-rate TEAMS pricing and Zero-server architecture.
Secure AI Agent Memory
AI agents that retain memory can accumulate PII. PrivacyScrubber provides local client-side tokenization to secure agentic memory without cloud data exposure. Includes Flat-rate TEAMS pricing and Zero-server architecture.
Agentic AI Data Leak Prevention
Multi-step AI agent workflows compound PII exposure risk. Protect data at each input stage with client-side tokenization that preserves semantic context. Includes Flat-rate TEAMS pricing and Zero-server architecture.
RAG Privacy
Retrieval-augmented generation (RAG) indexes your documents. Protect PII before it enters the vector store. Includes Flat-rate TEAMS pricing and Zero-server architecture.
Zero-Trust AI Data Pipelines
Design AI data pipelines that never expose raw PII. PrivacyScrubber provides local client-side sanitization as a pipeline stage to ensure full compliance. Includes Flat-rate TEAMS pricing and Zero-server architecture.
LLM Fine-Tuning Privacy
Fine-tuning LLMs on private data requires de-identification. How to scrub training datasets locally. Includes Flat-rate TEAMS pricing and Zero-server architecture.
Self-Hosted Agent Systems PII Protection
Even self-hosted or open-source AI agent systems require strict PII protection to prevent lateral data movement and internal exposure. Includes Flat-rate TEAMS pricing and Zero-server architecture.
Make and Zapier AI Privacy
Make (Integromat) and Zapier pass real customer data through AI steps. Here is how to protect PII before each AI action in your workflow. Includes Flat-rate TEAMS pricing and Zero-server architecture.
n8n AI Workflow Privacy
n8n lets you build powerful AI automations — but each node that touches real data is a PII leak point. Here is how to protect at every stage. Includes Flat-rate TEAMS pricing and Zero-server architecture.
Model Context Protocol (MCP) AI Security
Model Context Protocol (MCP) allows AI agents to read your local files. Ensure 100% PII redaction and local sanitization before Claude or Cursor reads your logs. Includes Flat-rate TEAMS pricing and Zero-server architecture.
Local LLM Privacy vs Cloud Sanitization
Is running a local LLM like Ollama the only way to protect PII? Learn how Zero-Trust Data Sanitization lets you use ChatGPT safely without heavy GPUs. Includes Flat-rate TEAMS pricing and Zero-server architecture.
Desktop AI Agents Privacy
Desktop AI agents like Cursor, Bolt, and Claude Desktop read your entire filesystem. Implement strict PII sanitization to prevent sensitive data from reaching AI servers. Includes Flat-rate TEAMS pricing and Zero-server architecture.
Cursor AI Source Code Leak
Every Cursor session sends active file context to an LLM endpoint. Discover exactly what data is transmitted — API keys, .env files, SIEM log parsers — and how a Zero-Trust MCP layer stops it. Includes Flat-rate TEAMS pricing and Zero-server architecture.
Claude Code Privacy
Anthropic's Claude Code runs directly in your developer terminal with shell access. Learn how to configure local PII MCP Server data masking to prevent logs, credentials, and codebases from leaking to Anthropic servers. Includes Flat-rate TEAMS pricing and Zero-server architecture.
Securing Cline and Roo Code
Learn how to configure the local PrivacyScrubber MCP server in Cline (formerly Claude Dev) and Roo Code to sanitize customer PII, secrets, and database tables locally inside VS Code. Includes Flat-rate TEAMS pricing and Zero-server architecture.
Salesforce Agentforce Compliance
Enterprise CISOs are concerned about Salesforce Agentforce extracting CRM data. Learn how a Zero-Trust middleware protects PII before it reaches autonomous agents. Includes Flat-rate TEAMS pricing and Zero-server architecture.
Aider AI Privacy & MCP
Learn how to configure the local PrivacyScrubber MCP server with Aider to sanitize customer PII, secrets, and credentials before terminal agent tasks are executed. Includes Flat-rate TEAMS pricing and Zero-server architecture.
LangChain & LlamaIndex PII Redaction Middleware for TypeScript & Node.js
Implement zero-trust PII redaction middleware for LangChain and LlamaIndex agents. Preserve multi-turn state and token consistency across reasoning loops in TypeScript. Includes Flat-rate TEAMS pricing and Zero-server architecture.
Sanitizing PII in LLM Observability Traces
Prevent secondary data breaches by automatically redacting PII, secrets, and database credentials from LLM observability traces, LangSmith dashboards, and Langfuse logs. Includes Flat-rate TEAMS pricing and Zero-server architecture.
Compare Edition Features
From individual use to corporate rollout, choose the level of control your organization requires.
| Core Capabilities |
Free
Web Only
|
PRO
$15/mo or $110 Lifetime
|
TEAMS
$99/mo
|
ENTERPRISE
Custom Tier
|
|---|---|---|---|---|
| 100% Local Processing (Airplane Mode) | ||||
| Text Paste & Single File Docs | Max 5k chars | UNLIMITED | UNLIMITED | UNLIMITED |
| Batch Processing & Background OCR | — | |||
| Custom Regex & Specific Redaction Rules | — | |||
| Chrome Extension Native App | — | |||
| Silent Corporate Deployment (MDM) | — | — | ||
| Policy Control Center & Enforcement | — | — | ||
| On-Premise Source Code License | — | — | — | |
| 100% Air-Gapped Operation | — | — | — | |
| Dedicated GRC Support | — | — | — | |
| Try Free | Details | Deploy TEAMS | Enterprise Hub |
Agents Technical Compliance Library
Deep architectural mapping of Zero-Trust Data Sanitization (ZTDS) controls to industry-specific regulatory standards.
Zero-Trust Verification Signature
The above technical controls are enforced deterministically by the PrivacyScrubber Local Engine. All redaction cycles generate zero server-side telemetry, satisfying global data residency requirements for Agents institutions.
Frequently Asked Questions
Common questions about deploying zero-trust AI for AI Agents Teams.
Why do AI Agents need local PII sanitization?
Can the AI understand the intent if the data is masked?
How does 1-click Reveal work?
Zero-Trust Sanitization Verified
100% GDPR, HIPAA & CCPA compliant. All PII processing occurs locally in browser RAM.
