Cod Numeric Personal
Detects Cod Numeric Personal 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, ro
- 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[1-8]\d{12}\bCorroborative evidence keywords
CNP, cod numeric personal, personal code, ID number, identification, ID card, license, permit, registration, certificate, field, column, row, entry, record, value, form, register, database, extract (+19 more)
Proximity: 300 characters
Should match
1750101123456— Romanian CNP (male, born 1975)2880512567890— Romanian CNP (female, born 1988)5920303456789— Romanian CNP (male, born 1992 - foreign)
Should not match
0750101123456— Invalid first digit (0)9750101123456— Invalid first digit (9)template example placeholder record identifier— Template/sample context should be excluded even when anchor words are present
Known false positives
- The first-digit constraint (1-8) and 13-digit length provide good structural validation, but long numeric strings may appear in other contexts. Mitigation: Validate embedded date (digits 2-7) and require corroborative evidence keywords for higher confidence.
- 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.