Henkilötunnus (HETU)

Detects Henkilötunnus (HETU) patterns. This pattern is based on a Microsoft Purview built-in sensitive information type. Users already running Purview may prefer to enable the built-in SIT directly, or use this version as a starting point for customisation.

Type: regex
Engine: universal
Confidence: high
Confidence justification: High confidence: pattern has strong structural constraints (specific format, prefix, or character class restrictions) that significantly reduce false positive rates. Added context gating and exclusion rules improve precision and reduce incidental matches.
Detection quality: Verified
Jurisdictions: eu, fi
Regulations: BDSG, CNIL / LIL, GDPR
Frameworks: ISO 27001, ISO 27701
Data categories: pii, government-id
Scope: narrow
Risk rating: 9
Platform compatibility: Purview: Compatible, GCP DLP: Compatible, Macie: Compatible, Zscaler: Compatible, Palo Alto: Compatible, Netskope: Compatible

Pattern

\b\d{6}[-+A]\d{3}[A-Z0-9]\b

Corroborative evidence keywords

henkilötunnus, HETU, personal identity code, ID number, identification, ID card, license, permit, registration, certificate, data record, database record, record set, data extract, data export, database table, spreadsheet, data registry, registry entry, master data (+13 more)

Proximity: 300 characters

Should match

010175-123A — Finnish HETU born in 1900s
120388+234B — Finnish HETU born in 1800s
150392A456C — Finnish HETU born in 2000s

Should not match

010175X123A — Invalid century character
010175-12A — Too few digits in individual number
template example placeholder record identifier — Template/sample context should be excluded even when anchor words are present

Known false positives

The structured format with century marker significantly reduces false positives, though test data or documentation may contain example patterns. Mitigation: The century marker (-, +, A) provides strong structural validation. Additional keyword context improves accuracy.
In multiple languages, similar terminology used in formal or administrative contexts (education, professional documentation) that does not constitute sensitive data collection. Mitigation: Layer with additional contextual signals such as structured identifiers, form fields, or database column headers to distinguish sensitive records from general references.

References

Finland National ID entity definition - Microsoft Learn