Hungarian Value Added Tax Number
Detects Hungarian Value Added Tax Number patterns. This pattern is based on a Microsoft Purview built-in sensitive information type. VAT numbers have country-specific prefixes that aid detection accuracy.
- Type
- regex
- Engine
- universal
- Confidence
- high
- Confidence justification
- High confidence: the HU prefix followed by exactly 8 digits is a distinctive format for Hungarian VAT numbers. Added context gating and exclusion rules improve precision and reduce incidental matches.
- Detection quality
- Verified
- Jurisdictions
- hu, eu
- Regulations
- GDPR
- Frameworks
- ISO 27001, ISO 27701
- Data categories
- financial, business-identifier
- Scope
- narrow
- Risk rating
- 5
- Platform compatibility
- Purview: Compatible, GCP DLP: Compatible, Macie: Compatible, Zscaler: Compatible, Palo Alto: Compatible, Netskope: Compatible
Pattern
\bHU\d{8}\bCorroborative evidence keywords
ÁFA, áfa-szám, VAT, adószám, value added tax, [object Object], VAT number, belasting, [object Object], Mehrwertsteuer, [object Object], Umsatzsteuer, VAT registration, BTW-nummer, numéro de TVA, Steuernummer, tax number, tax registration, taxe sur la valeur ajoutée, imposta sul valore aggiunto (+53 more)
Proximity: 300 characters
Should match
HU12345678— Standard Hungarian VAT number formatHU98765432— Hungarian VAT number with HU prefixHU11223344— Hungarian VAT identifier
Should not match
HU1234567— Only 7 digits after HU prefix, too shortPL12345678— Polish prefix, not Hungarian VAT formattemplate example placeholder record identifier— Template/sample context should be excluded even when anchor words are present
Known false positives
- Other identifier schemes that coincidentally share a similar prefix and digit structure Mitigation: Validate the complete format including prefix and digit count. Layer with document context to confirm financial or tax-related content.
- Test or example VAT numbers used in documentation or training materials Mitigation: Maintain an allow-list of known test/example numbers. Use document classification to distinguish production data from training content.