Fingerprint Quality Score (NIST NFIQ) Regex for JavaScript
/^(?:100|[1-9][0-9]?|0)$/What this pattern does
This page provides a lightweight, single-purpose regular expression for matching fingerprint quality score (nist nfiq), ported and verified for JavaScript. Identity and credential patterns need both correctness and safety, since they're frequent targets for adversarial input. The snippet below is ready to drop into your JavaScript project — whether you're validating in an Express middleware, a Next.js API route, or a client-side form.
Javascript Implementation
// Fingerprint Quality Score (NIST NFIQ)
// ReDoS-safe | RegexVault — Identity & PII > Biometric & Physical
const fingerprintQualityScoreNistNfiqRegex = /^(?:100|[1-9][0-9]?|0)$/;
function validateFingerprintQualityScoreNistNfiq(input: string): boolean {
return fingerprintQualityScoreNistNfiqRegex.test(input);
}
// Example
console.log(validateFingerprintQualityScoreNistNfiq("0")); // trueTest Cases
Matches (Valid) | Rejects (Invalid) |
|---|---|
0 | 101 |
1 | -1 |
50 | 50.5 |
99 | abc |
100 | — |
When to use this pattern
This pattern is drawn from the Identity & PII > Biometric & Physical category and carries a ReDoS-safe certification. That matters for JavaScript developers because especially critical in long-running Node.js event loops where a ReDoS vulnerability can block the entire process. RegexVault audits patterns against known backtracking attack vectors, ensuring you have the necessary context before using this regex in a high-stakes production environment.
Common Pitfalls
Any system storing fingerprint quality scores is almost certainly also storing fingerprint images or templates — both are the highest sensitivity biometric data. Biometric data often triggers sector-specific laws (e.g., Illinois BIPA).
Technical Notes
NFIQ2 (NIST Fingerprint Image Quality 2) scores fingerprint images 0-100, where 100 is best quality and 0 is unusable. Used in biometric enrollment systems, e-passport readers, and border control. Fingerprint data is biometric data — highest sensitivity classification.
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