URL

Name: URL
Creator: TestPattern Community
License: https://opensource.org/licenses/MIT

Detects URL patterns.

Type: regex
Engine: universal
Confidence: medium
Confidence justification: Medium confidence: pattern has structural constraints but corroborative keywords are recommended to reduce false positive rates. Added context gating and exclusion rules improve precision and reduce incidental matches.
Detection quality: Partial
Jurisdictions: global
Frameworks: CIS Controls, ISO 27001, NIST CSF, SOC 2
Data categories: network, pii
Scope: wide
Platform compatibility: Purview: Compatible, GCP DLP: Compatible, Macie: Compatible, Zscaler: Compatible, Palo Alto: Compatible, Netskope: Compatible

Pattern

\bhttps?://[^\s<>"{}|\\^`\[\]]+\b

Corroborative evidence keywords

identifier, number, ID, address, age, birthday, citizenship, city, date of birth, DOB, email, ethnicity, fax, first name, full name, gender, given name, last name, maiden name, middle name (+38 more)

Proximity: 300 characters

Should match

https://example.com/path — HTTPS URL
http://api.example.com/v1/data — HTTP API URL
https://sub.domain.co.uk/page?q=1 — URL with query parameters

Should not match

ftp://files.example.com/doc — FTP scheme instead of HTTP/HTTPS
example.com/path — Missing scheme (no http:// or https://)
://example.com — Missing scheme name before ://
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 url 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 English (as the primary international business language), 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.