PublishedISO 9001:2026 published 16 Sept 2026 · 2015 certificates must transition by 30 Sept 2029What changed →
Internal Auditor course (ISO 19011:2026):free until 31 Oct · then $59 for three monthsStart free now →
← Back to Clause Explorer
A.8.11ISO 27001:2022 Annex ANew in 2022

Data masking

ISO/IEC 27002:2022 attributes

Control type
Preventive
Security properties
Confidentiality
Cybersecurity concept
Protect
Operational capability
Information protection
Security domain
Protection

Attribute tags as published in ISO/IEC 27002:2022, compiled from public listings — confirm against your licensed copy.

Plain-language summary

New in 2022: hiding, substituting or pseudonymising sensitive data, especially personal information, so that people and systems that do not need the real values — testers, analysts, support staff, reporting tools — work with masked versions instead.

What the clause is really asking

Organisations copy production data into test environments, analytics tools, spreadsheets and supplier systems all the time, and each copy multiplies the exposure. The control asks you to use data masking where your access control policy, other policies, business needs and legal obligations call for it. Masking covers a family of techniques: hiding part of a value (showing only the last four digits of an account number), substitution with realistic fake values, pseudonymisation (replacing identifiers with tokens that can be reversed only with a separately held key), anonymisation (irreversible), encryption and aggregation. The guidance asks you to weigh how strong the technique must be, whether masked data could be re-identified by combining it with other sources, and who may see unmasked values. Under POPIA, information de-identified so that it cannot be re-identified falls outside the Act, but data that can be linked back to a person remains personal information. The common misunderstanding is that masking is only for developers; in many organisations the larger exposure is report extracts sent to analysts, consultants and BI tools.

What auditors look for

Auditors ask where production data, especially personal information, is copied for testing, development, training, analytics or reporting, and then check what form it takes there. They open a test environment or a BI dataset and ask whether it contains real names, ID numbers, contact or bank details. They ask for the masking rules — which fields, which technique — and who approved them. They check what support and call-centre staff see on screen. Where pseudonymisation is used, they ask where the re-identification key is held and who can use it. The hard question: if your test system were breached tomorrow, would you have to notify the Information Regulator?

Typical evidence

Data masking standard or section of the access control policy; inventory of sensitive data fields and where they are copied; masking rules per environment or dataset; masking configuration in applications, databases or BI tools; approvals for any use of unmasked production data; key management records for pseudonymisation; re-identification risk assessments; test data management procedure.

How to comply — recommendations

List the places where copies of production personal information end up: test and training systems, report extracts, BI datasets, supplier uploads, spreadsheets emailed to consultants. For each, decide whether real values are needed. Where they are not, write masking rules in a one-page standard: which fields (ID numbers, bank details, contact details, salary or health data), which technique, and who may approve an exception. Use built-in features where they exist, such as dynamic data masking in databases, field-level security in the CRM and restricted columns in BI tools, and generate synthetic data for testing. Keep pseudonymisation keys separate from the data. Record any approved use of live data in testing, with an end date.

Common nonconformities

Unmasked production personal information in test or development environments; analytics datasets containing identifiers the analysis does not need; no rules defining which fields are masked or how; pseudonymisation keys stored with the data; support staff seeing full ID or account numbers without need; re-identification risk never considered; live data used in testing without approval.

Related clauses

ISO/IEC 27002:2022 8.11 (guidance); ISO 27001 6.1.3; Annex A 5.12 (classification), 5.15 (access control), 5.34 (privacy and protection of PII), 8.3 (information access restriction), 8.24 (cryptography), 8.33 (test information); POPIA s6 (exclusions), s10 (minimality), s19; NIST CSF 2.0 PR.DS (data security); ISO/IEC 20889 (de-identification).

Resources for this clause

Get the free ISO 27001 Annex A — 93 Controls Quick Reference (A3 PDF)

Free, instant download. We'll only email you the occasional practical quality update — no spam, unsubscribe anytime.

Qlause provides interpretive guidance only and is not a substitute for the standard. Refer to your licensed copy of the relevant standard for the authoritative text.

Certification & implementation

Working on a certification or system implementation project?

Implementing ISO 9001, moving to the 2026 edition, getting ready for a certification audit, or stuck on a clause that doesn't seem to fit your operation? Tell us where you are and where you're stuck. We'll look at it and suggest a practical next step, or connect you with people we trust who can help.

Email hello@qlause.app

No sales pitch, no obligation — we read every message.