Zero-Trust Security Analysis for AI Vulnerabilities
Security

Mapping OWASP Top 10 for LLMs to Browser-Level Data Sanitization Controls

Discover how local PII masking and pre-prompt sanitization directly mitigate key OWASP LLM vulnerabilities, including Sensitive Data Disclosure and Prompt Injection. Includes Flat-rate TEAMS pricing and Zero-server architecture.

Ilya Sibiryakov
Ilya SibiryakovPrivacy Expert

Last updated: · 3 min read

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 Security professionals using generative AI. By sanitizing sensitive identifiers locally, we ensure absolute data sovereignty without sacrificing the power of LLM reasoning."

Paste real Security 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 Security data instantly in your browser, without any API calls.

Automated Detection Classes:
User / Server IP AddressesAWS_KEYINTERNAL_HOSTNAMEMAC_ADDRESSVULN_ID
100% Client-Side Execution
Wasm_Engine
SIEM ALERT > Src IP: 192.168.12.44 → Dst: siem.internal.corp User: d.novak@corp.com | AWS Key: AKIA4X9M2PLRT887NNZZ CVE: CVE-2026-44821 | Severity: CRITICAL
SIEM ALERT > Src IP: [IP_1] → Dst: [HOSTNAME_1] User: [EMAIL_1] | AWS Key: [API_KEY_1] CVE: [CVE_1] | Severity: CRITICAL

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The Zero-Trust Imperative: Prevent shadow AI data leaks by enforcing a zero-trust, client-side redaction perimeter. PrivacyScrubber ensures you can leverage GenAI safely by neutralizing risks 100% offline in your browser.

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

Managing "Mapping OWASP Top 10 for LLMs to Browser-Level Data Sanitization Controls" is a major technical objective for CISOs, security analysts, penetration testers, and GRC professionals. As the adoption of ChatGPT for report writing, AI-assisted SIEM analysis, and security audit tools increases, the risk of corporate data exfiltration to external datasets grows. Our security AI privacy guides details how to secure the security perimeter during this transition. The main threat is submitting security architecture details, vulnerability scan results, client infrastructure data, and incident timelines to third-party AI.

When employees submit customer records for "OWASP Top 10 LLM" tasks on cloud-based LLMs, they create unmonitored data trails. Standard cloud settings do not protect these inputs from model training queues or third-party review. For CISOs, security analysts, penetration testers, and GRC professionals, the primary point of failure is sending raw prompt text. Discover how local PII masking and pre-prompt sanitization directly mitigate key OWASP LLM vulnerabilities, including Sensitive Data Disclosure and Prompt Injection. Includes Flat-rate TEAMS pricing and Zero-server architecture.

Privacy Insight: Traditional network firewalls cannot parse LLM prompts for semantic context. Mitigating OWASP LLM02 (Sensitive Data Disclosure) requires a local, client-side cryptographic buffer that anonymizes data before it crosses the network.
For foundational strategies and policies, refer to the security AI privacy guides.

Why Security Compliance Teams Flag Unmasked AI Prompts

Regulatory oversight for the security sector is explicit: ISO 27001 Annex A controls (A.8.2, A.8.11), SOC 2 Type II, NIST Cybersecurity Framework, and FCA/DORA compliance. However, technical compliance lags behind AI adoption curves. Navigating the data exposure surface often overlaps with what is responsible for most of the recent pii data breaches? — identifying how unstructured data becomes a permanent liability in model weights. To achieve verifiable security, you must eliminate the PII before it reaches the cloud. Resolving safety requirements for OWASP Top 10 LLM operations is only possible by sanitizing data before it reaches external providers. To understand similar challenges in related domains, review our analysis on what is responsible for most of the recent pii data breaches?.

With local Zero-Trust Data Sanitization, PrivacyScrubber intercepts data in the browser through our Secure Workspace or the PrivacyScrubber Chrome Extension.

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

With local Zero-Trust Data Sanitization, PrivacyScrubber intercepts data in the browser through our Secure Workspace or the PrivacyScrubber Chrome Extension. The Named Entity Recognition (NER) system replaces personal data markers with standardized tokens (such as [NAME_1]) in local memory. This design conforms with the standards in LLM DLP for enterprise, ensuring that cloud platforms only analyze sanitized text. The Chrome Extension automates this workflow by adding a quick protect toggle inside ChatGPT, Claude, and Gemini for instant inline sanitization and detokenization. Running Named Entity Recognition locally ensures that teams can continue leveraging ChatGPT for report writing, AI-assisted SIEM analysis, and security audit tools for "OWASP Top 10 LLM" queries without any third-party data collection. This zero-trust architecture is also highly relevant for teams navigating LLM DLP for enterprise.

We support this architecture with the Airplane Mode Standard. Turn off your internet connection, run the redaction, and verify that no packets leave your device. This satisfies the safety rules in PII MCP Server deployment for corporate data protection. See how this methodology translates to other sectors in our guide on PII MCP Server deployment.

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.

Zero-Trust Configuration & Threat Model

Deploying local data controls for OWASP Top 10 LLM is critical when routing inputs to external platforms like ChatGPT for report writing, AI-assisted SIEM analysis, and security audit tools. To safeguard user context, PrivacyScrubber isolates individual records by tokenizing key 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 11ms. This allows team members to run complex queries involving OWASP LLM02 while satisfying strict internal data security requirements.

Verification Protocol

  • Parse unstructured records for key data points concerning OWASP LLM02.
  • Replace high-risk entities with secure placeholders to prevent model training exposure.
  • Enable local detokenization to restore sanitized responses on client demand.
  • Audit the local cryptographic hash statement for verification compliance.

Parser Specifications

Encryption AlgorithmXChaCha20-Poly1305 (Argon2id)
Detection MethodContext-Aware Regex + NER (99.2% Accuracy)
Data Egress RuleZero-Server Egress (Airplane Mode Verifiable)
Classification StandardStandard Privacy Guard
Associated Threat LevelMedium (Metadata Leak)

Mitigating the OWASP Top 10 for LLMs at the Edge

The OWASP Top 10 for Large Language Models highlights the most critical security vulnerabilities faced by enterprises adopting generative AI. While developers focus on securing their API endpoints, the largest vulnerability remains the human element: employees pasting corporate secrets directly into third-party interfaces.

How Local Sanitization Solves Core Vulnerabilities

LLM02: Sensitive Data Disclosure

This occurs when private customer data, PHI, or proprietary code is fed into LLMs, potentially appearing in future training runs or logs. **Solution:** Zero-Trust Data Sanitization (ZTDS) replaces these elements with deterministic tokens (e.g., [EMAIL_1]), making disclosure technically impossible.

LLM06: Sensitive Data Exposure in RAG

Retrieval-Augmented Generation (RAG) databases index enterprise documents. If these documents contain PII, any user can query the LLM to extract them. **Solution:** Sanitize files at the ingestion layer using local scripts to strip PII before documents enter the vector database, satisfying AUP policies and enabling PII sanitizers.

LLM01: Prompt Injection (Indirect)

When an LLM parses external files containing malicious instructions, it can execute them. By stripping out executable entities, script tags, and custom macros at the browser level prior to sending the prompt, you reduce the injection surface.

Instant Simulation

Mapping OWASP Top 10 for LLMs to Browser-Level Data Sanitization Controls Sanitizer

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 > Summarize this file regarding OWASP Top 10 LLM. Author: Jane Miller (jane.miller@company.com), phone: 555-0182. Location: 123 Maple Street.
PROMPT INPUT > Summarize this file regarding OWASP Top 10 LLM. Author: [NAME_1] ([EMAIL_1]), phone: [PHONE_1]. Location: [ADDRESS_1].

Security Detection Profile

Our zero-trust engine is pre-hardened for Security workflows, automatically identifying and tokenizing the following parameters 100% locally.

IP_ADDRESS
Active Protection
AWS_KEY
Active Protection
INTERNAL_HOSTNAME
Active Protection
MAC_ADDRESS
Active Protection
VULN_ID
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 deployment.

Hardware-Level Verification

We encourage you to audit our zero-trust claims for OWASP Top 10 LLM 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.

ChatGPT & Enterprise LLMs Integration

How to Protect Data for Mapping OWASP Top 10 for LLMs to Browser-Level Data Sanitization Controls

PrivacyScrubber operates entirely client-side. Whether using the copy-paste dashboard or the browser extension, your sensitive records stay on your local device. Follow these instructions to safely use ChatGPT & Enterprise LLMs:

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

Best for manual prompt sanitization without installing plugins:

  1. Open the PrivacyScrubber Web App dashboard in your browser.
  2. Paste the raw prompt or text containing sensitive details of Mapping OWASP Top 10 for LLMs to Browser-Level Data Sanitization Controls.
  3. Click Protect PII. Sensitive data is instantly swapped for secure placeholders (e.g., [NAME_1]).
  4. Submit the sanitized prompt to ChatGPT & Enterprise LLMs.
  5. Paste the AI's answer into the Reveal Originals box to instantly restore the original values.

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

For automated, inline de-identification within chat interfaces:

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

Local Redaction & Risk Matrix for Security

Detection EntityToken PlaceholderRisk LevelSecurity 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
Security Hub

LLM Data Loss Prevention for Security Teams

Read the full guide →
Verifiable Workflow

From Raw Security Data to Clean AI Prompt — 3 Steps, 30 Seconds, Zero Server Hops

Open PrivacyScrubber or the Chrome Extension. Paste your real Mapping OWASP Top 10 for LLMs to Browser-Level Data Sanitization Controls text. What reaches ChatGPT looks like this: [NAME_1][EMAIL_1]. Your original data stays local the entire time.

1

Step 1: Paste Your Real Data

Paste your actual Mapping OWASP Top 10 for LLMs to Browser-Level Data Sanitization Controls text into PrivacyScrubber — or click the shield icon directly inside ChatGPT, Claude, or Gemini. No copy-paste workaround. No second tab. It sits right where you already work.

Automated Detection Classes:
[IP_ADDRESS][AWS_KEY][INTERNAL_HOSTNAME][MAC_ADDRESS][VULN_ID]
2

Step 2: Names Out, Tokens In — Locally

The engine runs inside your browser. Every real name, ID, and email is replaced with a safe token ([NAME_1], [EMAIL_1]) before the prompt is sent. The AI analyzes your actual business logic — but sees zero real identities.

Safety standard:
Airplane Mode Verified (RAM Only)
3

Step 3: Get the AI's Answer Back in Plain Language

Paste the AI's response into Reveal Originals. PrivacyScrubber swaps every token back to the original value — instantly, inside browser RAM. Close the tab and every mapping is gone. Nothing stored, nothing logged, nothing sent.

Privacy Guarantee:
Mapping destroyed 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
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
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.

Zero-Trust Data Sanitization (ZTDS) — Verified Architecture

Independently auditable facts for Security 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 security 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.

Frequently Asked Questions

Does protecting mapping data before AI processing satisfy ISO 27001 Annex A controls (A.8.2?
Yes. Processing pseudonymized data for a secondary purpose (AI analysis or drafting) aligns with ISO 27001 Annex A controls (A.8.2 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 security use cases?
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 security-specific patterns such as OWASP Top 10 LLM.
Can I reverse the redaction if I use PrivacyScrubber to mask security 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 offline for OWASP Top 10?
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 security 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 specifically for OWASP Top 10 LLM PII safety?
Yes. In the PRO edition of PrivacyScrubber, you can configure custom regular expression (regex) rules designed to target unique patterns associated with OWASP Top 10 LLM and other sector-specific nomenclature. 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 Security Professionals Send to AI — and What They Should Be Sending Instead
Why Security Compliance Teams Flag Unmasked AI Prompts
Regulatory oversight for the security sector is explicit: ISO 27001 Annex A controls (A.8.2, A.8.11), SOC 2 Type II, NIST Cybersecurity Framework, and FCA/DORA compliance. However, technical compliance lags behind AI adoption curves. Navigating the data exposure surface often overlaps with what is responsible for most of the recent pii data breaches? — identifying how unstructured data becomes a permanent liability in model weights. To achieve verifiable security, you must eliminate the PII before it reaches the cloud. Resolving safety requirements for OWASP Top 10 LLM operations is only possible by sanitizing data before it reaches external providers. To understand similar challenges in related domains, review our analysis on what is responsible for most of the recent pii data breaches?.
How to Use AI on Real Security Data — Without Sending a Single Real Name
With local Zero-Trust Data Sanitization, PrivacyScrubber intercepts data in the browser through our Secure Workspace or the PrivacyScrubber Chrome Extension. The Named Entity Recognition (NER) system replaces personal data markers with standardized tokens (such as [NAME_1]) in local memory. This design conforms with the standards in LLM DLP for enterprise, ensuring that cloud platforms only analyze sanitized text. The Chrome Extension automates this workflow by adding a quick protect toggle inside ChatGPT, Claude, and Gemini for instant inline sanitization and detokenization. Running Named Entity Recognition locally ensures that teams can continue leveraging ChatGPT for report writing, AI-assisted SIEM analysis, and security audit tools for "OWASP Top 10 LLM" queries without any third-party data collection. This zero-trust architecture is also highly relevant for teams navigating LLM DLP for enterprise.
Is PrivacyScrubber safe for OWASP Top 10 LLM, OWASP LLM02, sensitive data disclosure AI, prompt injection mitigation, browser level AI security?
Yes, absolutely. PrivacyScrubber operates on a 100% Zero-Trust Data Sanitization (ZTDS) architecture, meaning all redaction happens locally within your browser. When working with OWASP Top 10 LLM, OWASP LLM02, sensitive data disclosure AI, prompt injection mitigation, browser level AI security, no sensitive data ever leaves your device or touches a cloud server.
How does it handle custom data structures for security?
Our engine includes 22+ built-in industry profiles optimized for security data. Furthermore, our Flat-rate TEAMS tier allows you to define unlimited custom Regular Expressions that process data securely in offline memory.
Security Hub

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