Passport

Detects Passport 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

low

Confidence justification

Low confidence: generic pattern format that may match unrelated data. Corroborative evidence keywords are essential for reliable detection. Context label evidence plus explicit template/example exclusion improves precision for high-risk identifiers. Added context gating and exclusion rules improve precision and reduce incidental matches.

Detection quality

Partial

Jurisdictions

uk

Regulations

UK GDPR, Data Protection Act 2018 (UK)

Frameworks

ISO 27001, ISO 27701

Data categories

pii, government-id

Scope

wide

Risk rating

8

Platform compatibility

Purview: Compatible, GCP DLP: Compatible, Macie: Compatible, Zscaler: Compatible, Palo Alto: Compatible, Netskope: Compatible

Pattern

\b\d{9}\b

Corroborative evidence keywords

passport, passport number, travel document, australian passport, 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 (+14 more)

Proximity: 300 characters

Should match

• 123456789 — UK passport number (9 digits)
• 987654321 — Alternate UK passport number
• 501234567 — Mid-range UK passport number

Should not match

• 12345678 — Only 8 digits instead of 9
• 1234567890 — 10 digits instead of 9
• 12345678A — Contains a letter instead of all digits
• sample template placeholder number 1234-5678 — Template/sample context with a hyphenated near-miss (no contiguous 9-digit run) — structurally rejected
• template example placeholder record identifier — Template/sample context should be excluded even when anchor words are present

Known false positives

• Common words and phrases related to passport 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 British English, 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.
• High-frequency pattern matches in large document corpora due to broad regex anchors. Expected match rate is significantly higher than specific identifier patterns. Mitigation: Tune confidence thresholds for bulk scanning. Consider using this pattern primarily as a pre-filter with secondary validation.

References

• U.S./U.K. passport number entity definition - Microsoft Learn

Collections

• European National IDs