In-Browser CSV Data Profiling & Sensitive Data Analyzer

The In-Browser CSV Data Profiling & Sensitive Data Analyzer provides data engineers, privacy analysts, and researchers with an instant structural and privacy audit of CSV datasets. Files are processed entirely inside browser memory using the HTML5 FileReader API, guaranteeing that proprietary or sensitive datasets never touch external servers.

The tool computes comprehensive column-level statistics—including null counts, cardinality, inferred data types, and value distributions—while simultaneously scanning column contents for unmasked PII, PCI, and sensitive identifiers.

Naïve regex pattern matching often produces false positives when scanning large datasets for credit card numbers (Primary Account Numbers, or PANs). A 16-digit number might simply be a tracking ID, transaction reference, or serial number rather than an actual credit card.

To achieve high-fidelity detection, professional data profiling engines use two-phase validation: First, regex filters isolate 13-to-19 digit candidates matching major Issuer Identification Number (IIN) prefixes (Visa 4, Mastercard 51-55/22-27, Amex 34/37). Second, the candidate is validated against the Luhn Modulus 10 checksum algorithm. Only numbers that satisfy both structural IIN patterns and the mathematical Luhn checksum are flagged as confirmed payment card exposures.