How do I mask SQL schema before sending to AI?

Paste your SQL or schema into the AI Schema Masker. The tool replaces table and column names with deterministic placeholders (e.g. T_001, C_001). Send the masked version to ChatGPT or any AI. Use the mapping to convert AI-generated SQL back to your real identifiers.

Does the AI Schema Masker send my database structure to a server?

No. All processing is client-side. Your SQL and schemas never leave your browser. No account or upload is required.

What is SQL schema masking for AI?

SQL schema masking replaces real table and column names with anonymous placeholders before you paste code or schema into an AI. This lets you get help without exposing your real database structure. You can restore AI output to your names using a mapping.

Can ChatGPT see my real table names?

Yes. When you paste SQL into ChatGPT, the model and OpenAI see every identifier—table names, column names, and aliases. To hide them, mask your SQL first with a client-side tool so only placeholders (e.g. T_001, C_001) are sent. Then restore AI output using the mapping.

Does OpenAI store the SQL I paste?

OpenAI may retain inputs for abuse detection and product improvement. Their policy states that API data is not used to train models by default, but pasting raw SQL still exposes your schema. Mask identifiers before sending so no real table or column names leave your control.

How do I mask SQL before sending to AI?

Use a client-side SQL schema masker: paste your SQL, run the masker to replace table and column names with placeholders (e.g. T_001, C_001), then paste the masked version into ChatGPT or any AI. Keep the mapping to restore AI-generated SQL to your real identifiers.

What is SQL identifier masking?

SQL identifier masking replaces real table names, column names, and aliases with anonymous placeholders (e.g. T_001, C_001) so you can share SQL with AI or others without exposing your database structure. A mapping lets you reverse the process and restore original names.

Is this tool safe for enterprise use?

Yes. The AI Schema Masker runs entirely in your browser—no SQL or schema is sent to any server. That makes it suitable for teams under GDPR, HIPAA, or PCI-DSS who need to use AI for SQL without exposing real identifiers or PII.

Schema IP (Intellectual Property) refers to the proprietary database design that reflects your business logic, naming conventions, and data relationships. Exposing your schema to AI providers reveals your architecture to a third party. Masking protects this IP while still allowing AI assistance with SQL logic.

SQL Schema Masker for AI — Mask Before ChatGPT, Restore After

Hide table and column names before sending to ChatGPT. Tables → T_001, columns → C_001. Fully reversible, 100% in your browser. No data ever leaves your device.

Keep mapping in tab

World's firstclient-side DITE-based SQL masker

100% Data Security—nothing sent to servers

Client-side only—runs entirely in your browser

Mask raw SQL

Paste SQL → mask identifiers → send to AI → paste AI reply → restore original names

Paste SQL→Mask→Send to AI→Restore

Mask:Identifiers(tables, columns, aliases — always on)

String values(IN clause, WHERE conditions)

Numeric values(dates, counts, thresholds)

Original input

Masked output

Original inputSQL · CTE · JSON · up to 5 MB

Masked outputCopy and send to AI

Masked query will appear here

Restore AI response

Paste the AI's reply → click Restore → copy the original SQL back

Load mapping

Paste AI reply (with T_000001, C_000001, etc.)

APaste AI replywith T_000001, C_000001…

Restored SQLoriginal names recovered

Secure AI Prompt Compiler

Schema + instruction → AI-safe prompt. No raw SQL; you define tables and columns, then restore the AI's SQL here.

Tables & columns

Table JOINs (how tables connect)

Instruction (business logic)

Generated prompt (copy and send to AI)

Restore AI response (use case 2)

Paste the AI's SQL reply from the prompt you sent above

Load mapping

100% data security, client-side only. The DITE engine (lexer → contextual extraction → deterministic mapping → token-based transform) runs entirely in your browser; no data leaves your device. Web Worker keeps the UI responsive for large inputs. Your SQL and schemas stay private.

What Is an AI Schema Masker?

An AI Schema Masker replaces real table names, column names, and SQL identifiers with anonymous placeholders before you paste a schema or query into an AI tool. When you paste raw SQL into ChatGPT, OpenAI servers see your actual database structure — including table names that can reveal your product domain, naming conventions, and data relationships. Masking first means only placeholders like T_001 and C_001 are ever sent; your real identifiers stay in your browser.

The masking is deterministic and reversible: the same identifier always maps to the same placeholder, so you can paste the AI's response back and restore your real names in one click. This makes it practical for GDPR, HIPAA, and PCI-DSS teams who need AI assistance for SQL work without violating data handling policies.

How it works

Mask Schemas in Seconds

Paste your SQL or schema

Paste raw SQL, a CREATE TABLE statement, or build a schema from tables and columns using the schema builder.

Mask identifiers

Click Mask. Every table name becomes T_001, every column name becomes C_001 — deterministically, so the same name always maps to the same token.

Send masked version to AI

Copy the masked SQL and paste it into ChatGPT, Claude, or any AI. Only placeholders are sent — your real schema stays in your browser.

Restore AI output

Paste the AI's response into the Restore section. The mapping replaces every placeholder back to your real table and column names.

Use cases

When Developers Mask Schemas

🤖

AI Pair Programming

Get SQL help from AI without exposing your production schema. Mask identifiers, get the query, restore real names.

💬

ChatGPT & Claude Queries

Ask AI to write or optimize SQL. Send the masked schema so the model has context without seeing your real table names.

🔍

Code Review With AI

Share SQL for review without leaking your database naming conventions or proprietary schema structure.

🗄️

SQL Generation

Describe your schema to AI using masked identifiers. AI generates correct SQL; you restore real names from the mapping.

🔗

API Design

Discuss API data models and database backing with AI safely — mask the schema before describing your architecture.

📄

Documentation

Generate schema documentation with AI assistance. Mask identifiers in examples so you can share docs publicly without exposing real names.

FAQ

1What gets masked — and what stays visible?

Table names and column names are replaced with T_001, C_001 style placeholders. SQL keywords (SELECT, FROM, WHERE, JOIN, etc.), operators, and numeric literals are left unchanged so the AI can still understand the query structure.

2Is the masking reversible?

Yes. The tool uses deterministic masking: the same identifier always produces the same placeholder. The mapping is available in-page and can be downloaded as a JSON file. Paste the AI's SQL response into the Restore section and apply the mapping to get your real identifiers back.

3Does it work for both SQL and JSON schemas?

Yes. You can paste raw SQL statements or use the schema builder to describe tables and columns in JSON-like form. Both modes mask identifiers before generating the prompt you send to AI.

4Is this tool compliant with GDPR, HIPAA, and PCI-DSS?

The tool runs 100% in your browser — no SQL, schema, or mapping is ever uploaded to any server. That means no third-party data exposure from the masking step itself, which helps teams meet compliance requirements when using AI for database work.

5Can teams share masking mappings?

Yes. Download the mapping as a JSON file and share it with teammates. Anyone with the file can restore AI-generated SQL to the real identifier names, enabling team workflows where one person masks, one uses AI, and another restores.

6Why mask my schema before using AI?

Pasting raw SQL into ChatGPT exposes your real table and column names to the AI provider. Masking replaces identifiers with anonymous tokens so the AI helps with query logic without seeing your real schema or business domain.

7How does the schema masker work?

The masker replaces table names with T_001, T_002 and column names with C_001, C_002 using deterministic mapping. Send the masked SQL to AI, then use the mapping to restore original names in the AI response.

8Can I use masked schemas with GitHub Copilot?

Yes. Paste masked SQL into your Copilot prompt. Copilot generates SQL using placeholder names. Paste the result into the Restore section to swap all placeholders back to your real identifiers.

9How do I restore original names after AI generates SQL?

Paste the AI-generated SQL into the Restore section. The tool applies the saved mapping and replaces every T_001, C_001 placeholder with the original table or column name.

10Does it support stored procedures?

The masker works at the SQL text level and can mask table and column references inside stored procedure bodies. Test on a small procedure first to verify output before masking production code.

11Is my schema data sent to any server?

No. All processing happens in your browser. Your SQL, schema, and mapping never leave your device. You can verify by checking network requests in browser DevTools — no outbound requests are made.

12What is schema IP?

Schema IP (Intellectual Property) is your proprietary database design that reveals your business logic and naming conventions. Masking protects this IP while still allowing AI assistance with SQL query logic.

13Can I mask multiple schemas at once?

Yes. Paste SQL referencing tables from multiple schemas. The masker maintains a consistent mapping across all tables, so cross-schema JOINs are masked consistently and can be restored from the same mapping file.

Learn more

Developer Guides

📖AI Privacy in JSON APIs 📖Masking PII in Production 📖Safe AI Prompt Engineering 📖JSON Schema for AI Tools

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