Bulk Staff Personal Details Extract

Tabular HRIS, payroll or reporting exports of staff personal details that do not carry TFNs: a CSV, spreadsheet or pipe/tab-delimited header row of HR column labels (employee / staff ID, name, date of birth, home address, position / classification, commencement or termination date, employment status) followed by populated staff rows. Detected from the extract's own structure, so it fires wherever the file lands (code repositories, reporting databases, file shares, test data folders), not only in HR-branded systems.

Type: regex
Engine: boost_regex
Confidence: medium
Confidence justification: Medium: a header of HR column labels followed by rows that pair an ID with a birth-year date is distinctive of a staff extract, and blank import templates, data dictionaries and org-chart role lists lack either the personal-detail column or populated rows. Some non-HR person extracts (member, student or volunteer lists that use "staff" or "employee" style ID columns) will also match, and extracts whose cells are split onto separate lines by the text extractor lose the header-row structure and fall below 65. The 85/75 tiers are heuristic evidence tiers, not measured accuracy; tests are synthetic extracts.
Jurisdictions: global, au
Regulations: Privacy Act 1988 (Cth), Information Privacy Act 2009 (Qld), NDB Scheme (Cth), Fair Work Regulations 2009 (Cth), GDPR
Frameworks: ISO 27001, ISO 27701, QGISCF
Data categories: pii, employment
Scope: wide
Risk rating: 8
Platform compatibility: Purview: Compatible, GCP DLP: Compatible, Macie: Unsupported, Zscaler: Compatible, Palo Alto: Degraded, Netskope: Unsupported

Pattern

(?i)\b(?:"?(?:(?:employee|staff|emp|payroll)[ _.]?(?:id|no\.?|num(?:ber)?|code)|(?:first|given|last|family|full)[ _]?names?|surname|d\.?o\.?b\.?|date[ _]of[ _]birth|birth[ _]?date|(?:home|residential|postal)[ _]address|address|suburb|postcode|position(?:[ _](?:title|number|no\.?))?|job[ _]title|classification|level|(?:commencement|start|hire|termination|end|cessation)[ _]date|employment[ _](?:status|type)|cost[ _]centre|department|work[ _]unit|gender|mobile|phone|email)"?(?:[ \t]{0,3}[,;|\t][ \t]{0,3}|[ \t]{2,6})){3,24}"?(?:(?:employee|staff|emp|payroll)[ _.]?(?:id|no\.?|num(?:ber)?|code)|(?:first|given|last|family|full)[ _]?names?|surname|d\.?o\.?b\.?|date[ _]of[ _]birth|birth[ _]?date|(?:home|residential|postal)[ _]address|address|suburb|postcode|position(?:[ _](?:title|number|no\.?))?|job[ _]title|classification|level|(?:commencement|start|hire|termination|end|cessation)[ _]date|employment[ _](?:status|type)|cost[ _]centre|department|work[ _]unit|gender|mobile|phone|email)

Corroborative evidence keywords

employee ID, date of birth, home address, commencement date, termination date, employment status, position title, classification

Proximity: 300 characters

Should match

Employee ID,Surname,Given Names,Date of Birth,Home Address,Position Title,Commencement Date,Employment Status E10442,Teston,Riley,14/03/1988,12 Wattle St Toowong QLD 4066,Plant Operator,03/02/2019,Permanent Full-time E10517,Examplar,Jordan,02/11/1979,4/88 Kent Rd Wooloowin QLD 4030,Team Leader Networks,17/08/2015,Permanent Full-time E11203,Staffson,Casey,21/06/1996,7 Ash Ct Logan Central QLD 4114,Graduate Engineer,30/01/2024,Fixed Term — 85 - CSV staff extract with ID, DOB, address, position and commencement columns and three populated rows with birth dates
EMPLID | NAME | Staff No | DOB | Residential Address | Job Title | Hire Date | Cost Centre 2004187 | Teston, Morgan | 2004187 | 1983-07-09 | 21 Ridge Rd Ipswich QLD 4305 | Payroll Officer | 2012-04-16 | CC4410 2004211 | Examplar, Avery | 2004211 | 1991-12-30 | 5 Lake St Cairns QLD 4870 | HR Business Partner | 2020-09-07 | CC4410 — 85 - pipe-delimited HCM export with ISO dates of birth on two rows
Staff ID First Name Last Name DOB Position Start Date Termination Date S40218 Quinn Teston Lecturer 01/03/2021 30/06/2026 — 75 - tab-delimited leaver extract with one populated row (commencement and termination dates, DOB cell empty)
Payroll No;Family Name;Given Name;Postal Address;Classification;Employment Type P77120;Teston;Harper;PO Box 412 Toowoomba QLD 4350;AO5;Permanent Part-time;Commenced 12/05/2017 — 75 - semicolon-delimited extract with one populated row, no date-of-birth values

Should not match

Employee ID,Surname,Given Names,Date of Birth,Home Address,Position Title,Commencement Date,Employment Status ,,,,,,, ,,,,,,, Import template - enter one row per new starter before uploading to the HRIS — Blank HR import template - header with no populated rows (65 discovery at most)
HRIS data dictionary Field name | Data type | Format | Description Employee_ID | Text(8) | E + 5 digits | Unique staff number assigned at hire Date_of_birth | Date | DD/MM/YYYY | Employee's date of birth Home_address | Text(120) | Free text | Residential address Commencement_date | Date | DD/MM/YYYY | First day of service — Data dictionary describing the extract columns
Organisation chart - Networks Division Position Number | Position Title | Classification | Department | Reports To 30012345 | Manager Networks | SO1 | Networks | 30010001 30012346 | Senior Engineer | PO5 | Networks | 30012345 30012347 | Engineer | PO3 | Networks | 30012346 — Org-chart role list with position numbers and classifications but no personal-detail columns
Payroll tax summary 2025-26 Month | Taxable wages | Exempt wages | Payroll tax payable | Due date July | $4,812,300 | $212,000 | $219,400 | 07/08/2025 August | $4,799,150 | $208,500 | $218,700 | 07/09/2025 — Payroll tax summary with monthly totals and no staff rows
The file exported from the HR system contained each employee's ID, name, date of birth, home address, job title and employment dates for about 22,000 current and former staff. — Breach news report describing the columns in prose

Known false positives

Blank HR import templates and onboarding spreadsheets with the header row only. Mitigation: No populated rows, so they stay at 65 discovery; template fixture phrases are excluded.
Data dictionaries, interface specifications and ETL column mappings that list the same column names. Mitigation: Column names appear one per line rather than as a delimited header, and data dictionary / field definition wording is excluded from enforce tiers.
Org charts, position registers and establishment lists (position number, title, classification) with no personal columns. Mitigation: 75 requires a date-of-birth or home-address column label; 85 requires rows with birth-year dates.
Non-staff person extracts (members, students, volunteers, customers) that use staff-style ID and DOB columns. Mitigation: Still personal data; accept, or narrow the ID column label and row regex with the customer's employee ID format.