CPF
Detects CPF 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
- boost_regex
- Confidence
- medium
- Confidence justification
- Medium confidence: pattern has structural constraints but corroborative keywords are recommended to reduce false positive rates.
- Detection quality
- Verified
- Jurisdictions
- br
- Regulations
- LGPD
- 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{3}\.?\d{3}\.?\d{3}[-.]?\d{2}\bCorroborative evidence keywords
identifier, number, ID, ID number, identification, ID card, license, permit, registration, certificate
Proximity: 300 characters
Should match
123.456.789-01— Standard CPF format with dots and dash12345678901— CPF without punctuation000.000.000-00— Zero-filled CPF format
Should not match
123.456.789-0— Only 1 check digit instead of 2123.456.789-012— 3 check digits instead of 2123.456.78-01— Only 2 digits in third group instead of 3
Known false positives
- Common words and phrases related to cpf appearing in policy documents, training materials, HR templates, or compliance guidelines without actual personal data. Mitigation: Require corroborative evidence keywords within the proximity window to confirm sensitive data context rather than general discussion.
- In Portuguese (Brazil), 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.