License and royalty agreements

Identifies documents containing references to license and royalty agreements in Australian contexts. This information type is classified as personally identifiable information under applicable data protection regulations.

Type: regex
Engine: boost_regex
Confidence: medium
Confidence justification: identifier/document-structure anchored regex with constrained context replaces phrase-only detection. Added context gating and exclusion rules improve precision and reduce incidental matches.
Detection quality: Mixed
Jurisdictions: global
Regulations: AML/CTF Act (Cth), IPA 2009 (Qld), NDB Scheme (Cth), Privacy Act 1988 (Cth)
Frameworks: ISO 27001, ISO 27701
Data categories: pii
Scope: wide
Platform compatibility: Purview: Compatible, GCP DLP: Compatible, Macie: Compatible, Zscaler: Compatible, Palo Alto: Degraded, Netskope: Unsupported

Pattern

(?is)\b(?:license\s+and\s+royalty\s+agreements|license\s+agreement|royalty\s+agreement|licensing\s+terms|royalty\s+rate|intellectual\s+property|licensing\s+fee|royalty\s+payment|license\s+grant|permitted\s+use|exclusive\s+license)\b

Corroborative evidence keywords

license and royalty agreements, license, royalty, agreements, corporate, legal, governance, drivers licence, driver licence, drivers license, driver license, DL, licence number, license number, field, column, row, entry, record, value (+23 more)

Proximity: 300 characters

Should match

license and royalty agreements — Primary topic phrase match
license agreement — Case-insensitive topic phrase match
royalty agreement — Alternative topic phrase match
licensing terms — Additional topic phrase match

Should not match

unrelated generic text without domain phrases — No relevant topic phrases present
placeholder value 12345 — Random text should not match topic-specific regex
license report — Generic word pair from old broad template should not match

Known false positives

Common words and phrases related to license and royalty agreements 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 Australian 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.