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🛡️ PRIVACY-SAFE SYNTHETIC DATA

Data Masking

Obfuscate sensitive fields using custom character masking. Redact credit card numbers, passwords, and identifiers while maintaining the shape of your records.

Instructions: Upload a file or paste your dataset, choose default strategies as character mask, review identified fields, and export your masked file.
Step 1 — Input Dataset
🔐 Privacy Compliance

All compliance audit processing runs locally in-memory. Data is never persisted on servers, satisfying strict GDPR, HIPAA, and DPDP mandates.

🔐

PII field audit results will appear here

Paste raw entries or upload files on the left, then click Detect PII Fields to run automated compliance checks.

🔐 Compliance Standards
Conforms to GDPR, HIPAA, and Indian DPDP audit standards automatically.
🎭 Multiple Strategies
Mask elements, insert fake entries, or swap values with placeholder tags.
📦 Export Formats
Download your anonymized dataset as clean CSV, JSON, or Excel sheets.
01

Select Dataset

Paste your tabular datasets or drop CSV/JSON files onto the dashboard.

02

Define Columns

The AI parses tables and columns to locate credentials, addresses, and ID cards.

03

Mask & Save

Export files with characters redacted (e.g., `4111 XXXX XXXX 1111`) safely.

Why Use Data Masking?

Preserve Layout Shapes: Keeps data formats recognizable for testing logic while obscuring values.
Compliance Audit Safety: Mask credit card records and national identifiers before storing logs.
Custom Obfuscation: Retain first/last letters (e.g. J*** D**) or fully hide values per column rules.
In-Memory Redaction: Calculations run locally. No information values are ever saved on servers.

Frequently Asked Questions

Is character masking reversible?

No. Once characters are overwritten (e.g., replaced with *), the process is mathematically one-way and cannot be decrypted.

Can I mask JSON objects?

Yes, you can paste nested JSON structures and configure masking properties on specific key paths.

Does faking work alongside masking?

Yes, you can choose to mask credit cards while faking phone numbers in the same dataset.