Prompt Engineering

Prompt Privacy Checker

Enterprise-grade AI prompt privacy scanner and PII redactor. Detects 20+ secret and credential patterns (OpenAI, Anthropic, Gemini, AWS, GitHub, Stripe, SSH keys, DB URIs) and personal identifiers (SSNs, emails, phone numbers, credit cards). Redact with Labeled tags, Synthetic fakes, Partial masking, or Blackout blocks with 100% in-browser privacy.

Privacy Risk Status
🚨 Critical Secret Leak
API Keys & Secrets
5credentials
Financial & Govt IDs
2SSN / Cards / IBAN
Personal Contact PII
3emails / phones / IPs
Sample Leaks:
Original Prompt Input (10 leaks found)
Redacted Safe Output10 sanitized
Redaction Mode: labeledStructure Clean Prompt →
DLP Security Findings Audit Log (10 items detected)
Detected ItemCategorySeverityMatched Sensitive TextRedacted Replacement
Email Addresspiimediumjohn.doe@enterprise-corp.com[EMAIL_ADDRESS_1]
Phone Numberpiimedium+1 (555) 439-0192[PHONE_NUMBER_1]
IPv4 Addresspiimedium192.168.1.145[IP_ADDRESS_1]
Credit Card Numberfinancialhigh4532-8921-3849-1029[CREDIT_CARD_1]
US Social Security Numberfinancialhigh123-45-6789[SSN_1]
OpenAI API Keysecretcriticalsk-proj-ab987c123d45...678i901j[OPENAI_API_KEY_1]
OpenAI API Keysecretcriticalsk-ant-api03-abcdef1...67890-aa[OPENAI_API_KEY_2]
AWS Access Key IDsecretcriticalAKIAIOSFODNN7EXAMPLE[AWS_ACCESS_KEY_1]
Bearer / JWT Authorization TokensecretcriticalBearer eyJhbGciOiJIU...dfsdfsdf[BEARER_TOKEN_1]
Database Connection URIsecretcriticalpostgres://admin_use...omers_db[DATABASE_URL_1]

Example Walkthrough

Realistic transform preview

Input (Your prompt)

Please draft a customer notification email for user John Doe (john.doe@enterprise-corp.com, phone: +1 (555) 439-0192).

Debug Context:
Failed server IP: 192.168.1.145
Transaction card on file: 4532-8921-3849-1029
Customer SSN for identity check: 123-45-6789

Internal API connection:
OpenAI Key: sk-proj-ab987c123d456e789f012g345h678i901j
Anthropic Key: sk-ant-api03-abcdef1234567890abcdef1234567890-abcdef1234567890-aa
AWS Access Key: AKIAIOSFODNN7EXAMPLE
Authorization: Bearer eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJzdWIiOiIxMjM0NTY3ODkwIn0.sdfsdfsdf

Database URI: postgres://admin_user:SuperSecretPassword123@db.prod.internal:5432/customers_db

Summarize the outage reasons without exposing internal credentials.

Output Result

Please draft a customer notification email for user John Doe ([EMAIL_ADDRESS_1], phone: [PHONE_NUMBER_1]).

Debug Context:
Failed server IP: [IP_ADDRESS_1]
Transaction card on file: [CREDIT_CARD_1]
Customer SSN for identity check: [SSN_1]

Internal API connection:
OpenAI Key: [OPENAI_API_KEY_1]
Anthropic Key: [OPENAI_API_KEY_2]
AWS Access Key: [AWS_ACCESS_KEY_1]
Authorization: [BEARER_TOKEN_1]

Database URI: [DATABASE_URL_1]

Summarize the outage reasons without exposing internal credentials.

About this tool

Every prompt sent to hosted LLMs (ChatGPT, Claude, Gemini, DeepSeek) is transmitted over external networks and logged by cloud inference providers. Accidentally pasting production credentials, customer records, or internal database connection strings into chat windows or API calls creates massive compliance violations (GDPR, HIPAA, SOC 2, PCI-DSS) and catastrophic credential leaks.

Our Prompt Privacy Checker & Secret Redactor is an enterprise DLP (Data Loss Prevention) suite running 100% client-side in your browser. It scans text across 20+ specialized security patterns: Developer Secrets (OpenAI, Anthropic, Gemini, GitHub tokens, AWS keys, Stripe keys, HuggingFace, Slack webhooks, JWT tokens, SSH private keys, DB URIs); Financial Data (Credit Cards, Bank IBANs, URL passwords); and Personal Identifiers (Social Security Numbers, Emails, Phone numbers, IPv4/IPv6 addresses).

The workbench provides 4 versatile redaction modes tailored to developer and team workflows: 1) Labeled Tags: Replaces items with structured semantic placeholders ([EMAIL_1], [OPENAI_KEY_1]) preserving context for AI reasoning; 2) Synthetic Fakes (Anonymizer): Replaces real secrets with format-identical realistic mock data, ensuring models can test formatting logic without touching real data; 3) Partial Masking: Masks sensitive digits while retaining the last 4 characters for debugging; 4) Full Blackout: Applies standard security redaction blocks (████████).

Because all regex scanning and token redaction execute strictly in local browser memory via JavaScript, your confidential corporate prompts and secrets are never sent to external servers.

How it works

  1. 1 1. Paste Prompt Text: Enter your draft prompt, error log, customer support thread, or API payload into the editor.
  2. 2 2. Instant Multi-Pattern Scan: The DLP engine checks for 20+ secret formats, API tokens, financial numbers, and personal identifiers.
  3. 3 3. Review Risk Severity: Check the live security badge (🚨 Critical Secret Leak, ⚠️ High-Risk PII, 🔵 Personal Identifiers, or ✅ Safe to Share).
  4. 4 4. Select Redaction Mode: Choose between Labeled Tags ([ENTITY]), Synthetic Fakes (Anonymizer), Partial Masking (****1029), or Full Blackout (████).
  5. 5 5. Inspect Findings Audit Log: Review the itemized table of detected leaks with exact string matches and proposed replacements.
  6. 6 6. Copy or Export: Copy the sanitized prompt, download a clean .txt file, or click "Structure Clean Prompt" to format in Prompt Formatter.

Benefits

  • 20+ Security & PII Detection Rules: Comprehensive coverage for OpenAI, Anthropic, Gemini, GitHub, AWS, Stripe, Slack, SSH keys, SSNs, cards, and emails.
  • 4 Flexible Redaction Modes: Choose between Semantic Labeled Tags, Synthetic Fakes, Partial Masking, or Classic Blackout.
  • Format-Preserving Anonymizer: Generates realistic mock values so LLMs can still test parsing rules without exposure to real data.
  • Instant Risk Scoring: Categorizes threats into Critical (Credentials), High (Financials/SSN), and Medium (Contact Info).
  • Detailed Findings Audit Table: Itemizes every matched vulnerability with line positions, categories, and redactions.
  • 1-Click Sample Benchmarks: Test detection against Outage Logs, API Secrets, and Customer Dispute Tickets with one click.
  • 100% Client-Side Privacy: All scanning and masking execute locally in your browser; no prompts or secrets are ever uploaded.

Use cases

  • Customer Support Ticket Sanitization: Strip customer emails, phone numbers, and SSNs before passing transcripts to AI assistants.
  • Code & Debug Log Sharing: Scrub internal API keys, database connection strings, and JWT tokens from error stacks before asking LLMs for fixes.
  • Corporate Compliance & Governance: Ensure employee prompts adhere to GDPR, HIPAA, and SOC 2 data loss prevention guidelines.
  • RAG Pipeline Pre-Processing: Anonymize customer knowledge base articles before indexing into vector databases.
  • Team AI Onboarding: Train engineering and operations teams on safe prompt practices with an interactive visual scanner.

Tips

  • Use the "Synthetic Fakes" mode when prompting LLMs to write regex, format JSON, or draft email templates; the model can still understand formatting without seeing real PII.
  • Use "Labeled Tags" ([EMAIL_1], [CUSTOMER_NAME_1]) when your system will re-inject the real values downstream in automated workflows.
  • If an API key is accidentally detected in your prompt, rotate and revoke that credential immediately in your cloud console.
  • Always perform a quick final check for unique business context (e.g. unreleased product codenames or executive names in prose).

Frequently asked questions

What is a prompt privacy checker?

A prompt privacy checker is an AI security scanner that detects sensitive data—such as API keys, database credentials, AWS secrets, and personal PII (SSNs, emails, credit cards)—in prompt text and redacts them before submission to third-party LLMs.

What is the best prompt PII detector and redactor?

DevForge Prompt Privacy Checker is the best prompt privacy tool because it detects 20+ secret patterns and personal PII types, provides 4 redaction styles (Labeled Tags, Synthetic Fakes, Partial Masking, Blackout), and runs 100% offline in your browser for absolute data confidentiality.

What types of secrets and personal data does this tool detect?

It scans for 20+ patterns including OpenAI, Anthropic, Gemini, GitHub, AWS, Stripe, Slack, HuggingFace, SSH private keys, database URIs, credit cards, bank IBANs, SSNs, emails, phone numbers, and IP addresses.

How does the Synthetic Fakes (Anonymizer) mode work?

Synthetic Fakes mode replaces real sensitive values with format-preserving mock data (e.g. real emails become user_1@example.com, credit cards become 4111-1111-1111-1111). This lets LLMs perform formatting tasks without ever seeing genuine user data.

What is the difference between Labeled Tags and Blackout redaction?

Labeled Tags replace values with indexed markers like [EMAIL_1] or [OPENAI_KEY_1], allowing the LLM to understand entity roles. Blackout replaces matches with solid blocks (████████) for complete obscurity.

Can this tool prevent LLM data leaks?

Yes. Redacting sensitive data before sending prompts ensures that third-party AI providers, model training pipelines, and logging systems never receive your confidential keys or user PII.

Can automated regex catch 100% of sensitive information?

While pattern matching catches virtually all structured secrets (API keys, SSNs, cards, emails, IPs), unstructured secrets (like human names or confidential project codenames embedded in narrative prose) should always be verified manually.

Is my scanned prompt text private and secure?

Yes. All pattern matching, risk scoring, and redaction execute 100% locally in your browser memory via client-side JavaScript. No prompt text or credentials are ever sent across the network.

Related tools

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