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Data Masking and DLP Standard Template (ISO/IEC 27001 A.8.11, A.8.12)

Masking and pseudonymisation techniques, test data, re-identification risk, DLP channels, rule catalogue, tuning, alert handling, staff privacy

ISMS và ISO/IEC 27001Đầy đủISO/IEC 27001:2022 + Amd 1:2024 A.8.11, A.8.12 (cited only); ISO/IEC 27002:2022; ISO/IEC 27559:2022datamaskingdlpstandard
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Cách dùng: Use it when A.8.11 or A.8.12 is applicable or customers ask how their data stays out of test systems and unapproved channels. Fill the data types and triggers first, then the masking technique table and the DLP channel coverage table, linked to your classification policy. The main pitfall is enforcing DLP blocking on day one instead of tuning in monitor mode, and calling pseudonymised data anonymous.

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Data Masking and Data Leakage Prevention Standard: [Organization name]

Technical standard for two controls added to Annex A in 2022: data masking (A.8.11) and data leakage prevention (A.8.12) of ISO/IEC 27001:2022 + Amd 1:2024, with guidance from ISO/IEC 27002:2022. It sets when and how to mask, pseudonymise or anonymise data, the rules for test and non-production data, which channels data leakage prevention (DLP) covers, how DLP rules are deployed, tuned and handled as security events, and the privacy limits on monitoring staff. Replace every [bracketed] value and every row marked Example. This is a documentation format, not legal advice.

Document control

FieldValue
Document ID[DOC-ISMS-062]
Version[1.0]
Status[Draft / In review / Approved / Superseded]
Owner[@security-engineering-lead]
Approvers/reviewers[@isms-manager], [@ciso], [@dpo], [@hr-lead], [@head-of-engineering]
Last updatedYYYY-MM-DD
Effective fromYYYY-MM-DD
Classification[Internal]
Standard and editionISO/IEC 27001:2022 + Amd 1:2024 (A.8.11, A.8.12); ISO/IEC 27002:2022
Next scheduled reviewYYYY-MM-DD
Inputs[Data classification policy], [Asset inventory DOC-ISMS-012], [Risk register DOC-ISMS-016], [DPIA reference]
Rule catalogue version[DLP-RULESET v1.0, YYYY-MM-DD]
Related documents[Information transfer policy DOC-ISMS-043], [Security monitoring procedure DOC-ISMS-064], [Secure development policy DOC-ISMS-065]

Approvals

RoleNameDecisionDate
Standard owner[@security-engineering-lead][Prepared]YYYY-MM-DD
Data protection officer[@dpo][Privacy review completed]YYYY-MM-DD
HR or employee representative consultation[@hr-lead][Consulted, where required]YYYY-MM-DD
Top management sponsor[@ciso][Approved / Approved with changes]YYYY-MM-DD

Revision history

VersionDateAuthorChange
0.1YYYY-MM-DD[@owner]First draft
1.0YYYY-MM-DD[@owner]Approved for issue; DLP in monitor mode
1.1 (Example)YYYY-MM-DD[@owner]Rules DLP-RUL-001 and 004 moved to block after tuning period
[x.y]YYYY-MM-DD[@author][Change summary]

Contents

1. Purpose, scope and authority

This standard applies to all information classed Confidential or Restricted under data/data-classification-policy, and to all personal data, wherever it is stored or processed inside the ISMS scope ([DOC-ISMS-002]). It covers:

  • Masking (A.8.11): deciding who sees full values and who sees a reduced or transformed version, so that support staff, analysts, developers, log readers and test environments get only the detail their task needs (sections 3 to 6).
  • Data leakage prevention (A.8.12): knowing every route by which sensitive data can leave the organization's control (mail, sharing links, chat, browser uploads, AI assistants, USB, print, bulk database exports) and, for each route, choosing whether to watch it, warn the user, block it or rely on another control (sections 7 to 11).

It applies to employees, contractors and suppliers using organization-managed devices, accounts and services. Personal devices are covered only inside managed containers defined in isms/endpoint-device-byod-policy.

2. Roles and responsibilities

RoleResponsibilities
Standard owner [@security-engineering-lead]Maintains this standard and the rule catalogue; runs tuning reviews; reports metrics
Information ownersDefine which data types need masking or DLP protection; approve unmasked access and rule exceptions for their data as risk owners, within the approval limits in section 12
Engineering leadsImplement masking in applications, pipelines and test data provisioning per section 5
DLP analysts (security team or managed service)Triage alerts within the service levels in section 10; only named, trained analysts may view alert content
Data protection officer [@dpo]Reviews techniques against privacy law, reviews the monitoring impact (section 11), advises on breach assessment
HR lead [@hr-lead]Handles cases where an alert indicates possible misconduct, under isms/security-disciplinary-process
ISMS manager [@isms-manager]Links rules to risks and the SoA; follows audit findings; includes metrics in the measurement programme

3. Data in scope and triggers

Data typeExample identifiersClassificationMasking required whereDLP detection method
Customer personal data (Example)Name, e-mail, phone, address, customer IDConfidentialSupport tools, analytics, logs, non-productionLabel plus pattern plus exact data match on customer table
Special category or health data (Example)Diagnosis, appointment reason, patient identifierRestrictedEverywhere outside authorised clinical rolesLabel plus exact data match; block outbound
Payment card data (Example)Primary account numberRestrictedDisplay shows last four digits at most; never in logsPattern with checksum validation
Credentials and secrets (Example)API keys, private keys, tokensRestrictedNever displayed; redacted in logsSecret patterns in code, chat and paste sites; see security/secrets-management-standard
Source code and designs (Example)Repository content, CAD files, OT programsConfidentialNot applicableFingerprint and location rules; repository visibility monitoring
Commercial documents (Example)Contracts, price lists, board papersConfidentialNot applicableSensitivity label and document fingerprint

4. Masking, pseudonymisation and anonymisation techniques

Technique IDTechniqueHow it worksReversible?Still personal data?Typical use
MSK-TEC-001Static redactionReplace the value with a fixed token such as ***NoUsually yes if other identifiers remainLogs, exports to third parties
MSK-TEC-002Partial maskingShow part of the value (last four digits, first letter)NoYesSupport screens, receipts
MSK-TEC-003Dynamic maskingMask at query or display time based on the user's roleYes for authorised rolesYesProduction support and analytics tools
MSK-TEC-004Keyed pseudonymisationReplace identifier with a keyed hash (HMAC) or token from a vaultOnly with the key or vaultYes (pseudonymised)Analytics joins, data science, data shared between teams
MSK-TEC-005Format-preserving encryptionEncrypt so the output keeps the formatYes with the keyYesLegacy systems that validate formats
MSK-TEC-006Substitution with synthetic valuesReplace with realistic fake values from a generatorNoNo for the substituted fields, check the restTest and demo data
MSK-TEC-007Generalisation and suppressionReduce precision (age bands, postcode prefix), drop rare valuesNoDepends on re-identification risk assessmentStatistics, research extracts
MSK-TEC-008Aggregation with thresholdsPublish counts only above a minimum cell sizeNoNormally no, if thresholds are adequateDashboards, external reports
MSK-TEC-009Fully synthetic dataGenerate a data set with similar statistics but no real recordsNoNormally no; test for memorised recordsModel training, vendor testing

Rules:

  1. MSK-STD-001: Logs and error messages must not contain Restricted data or credentials in clear; apply MSK-TEC-001 at the logging library (see security/security-logging-standard).
  2. MSK-STD-002: Staff who do not need full identifiers see masked values by default (MSK-TEC-002 or 003). Unmasking is a privileged action that is logged, in line with the access control policy (isms/access-control-policy).
  3. MSK-STD-003: Data is described as anonymised only after a documented re-identification risk assessment (section 6). Otherwise it is treated as pseudonymised personal data.
  4. MSK-STD-004: Unsalted or unkeyed hashes of low-entropy identifiers (e-mail, phone, national ID) are not an approved masking technique.

5. Test and non-production data

  • MSK-STD-005: Production personal or Restricted data must not be copied to development, test, staging, demo or vendor environments unless masked or substituted (MSK-TEC-004, 006, 007 or 009) inside the production boundary before the copy.
  • MSK-STD-006: Where real data is unavoidable (for example reproducing a defect that only occurs with one customer's data), the information owner approves in writing (with the department head, or higher, where the residual risk requires it under section 12), the data set is minimised, access is limited to named people, the copy is deleted within [14] days, and the approval is recorded as an exception (section 12).
  • MSK-STD-007: Masking pipelines are code: they are reviewed, version-controlled and tested to fail closed (a column added to a production table without a masking rule stops the pipeline).
  • MSK-STD-008: Data shared with suppliers for testing or support follows isms/information-transfer-policy and the supplier agreement.

6. Pseudonymisation secrets and re-identification risk

  • MSK-STD-009: Keys for keyed hashing, tokenisation and format-preserving encryption are managed under security/cryptography-standard and recorded in the cryptographic key register ([DOC-ISMS-070]). They are stored separately from the pseudonymised data and accessible to a separate role.
  • MSK-STD-010: Before data is released as anonymised, or shared outside the organization in pseudonymised form, a re-identification risk assessment considers: direct identifiers removed, indirect identifiers (dates, locations, rare attributes), linkable external data, the recipient's capability and motive, and the release model (public, controlled sharing, internal only). Record the result in the DPIA (compliance/dpia) where one is required.
  • MSK-STD-011: Re-identification of pseudonymised data is permitted only for the purposes recorded in the record of processing (compliance/gdpr-ropa) and is logged.

ISO/IEC 27559:2022 gives a framework for de-identification of personal data, and NIST SP 800-188 (September 2023) describes de-identification techniques and governance; use either as a reference for the assessment method.

7. DLP channels and coverage

Channel IDChannelControl approachCoverage (Example)Residual gap and compensating control
DLP-CHN-001Corporate e-mail outboundGateway or suite DLP: inspect content and labels, encrypt or blockAll mailboxesPersonal webmail blocked by web filtering (A.8.23)
DLP-CHN-002Cloud storage and file sharingSuite DLP and sharing policy: block external sharing of Restricted labelsAll tenantsShadow storage services detected by cloud access broker logs
DLP-CHN-003Collaboration and chatSuite DLP on messages and attachments to external guestsInternal and guest channelsScreenshots of chat not detectable
DLP-CHN-004Endpoint (copy to USB, print, upload in browser, clipboard)Endpoint DLP agent on managed devicesManaged laptopsUnmanaged devices limited to browser access without download
DLP-CHN-005Web uploads and generative AI toolsSecure web gateway and browser controls; approved AI tools only per ai-data/ai-usage-policyManaged devices and networkPhone cameras; awareness training
DLP-CHN-006Source code platformsSecret scanning, push protection, repository visibility alertsAll repositoriesCode pasted elsewhere; covered by DLP-CHN-005
DLP-CHN-007Databases and APIsQuery volume anomalies, export limits, database activity monitoringProduction databasesInsider with legitimate bulk access; access reviews
DLP-CHN-008Removable media and printingBlocked by default; allowed for named roles with encryptionManaged devicesPaper: clear desk policy (isms/clear-desk-clear-screen-policy)

8. DLP rule catalogue

Rule IDData typeChannelConditionModeAction on matchOwner
DLP-RUL-001 (Example)Payment card dataE-mail, file sharing5 or more valid card numbers to an external recipientBlockBlock, notify sender, alert analyst[@security-engineering-lead]
DLP-RUL-002 (Example)Customer personal dataFile sharingRestricted or Confidential label shared to personal domainsWarnUser justification required, logged[@privacy-lead]
DLP-RUL-003 (Example)Health dataAllExact data match on patient identifiers, 10 or more recordsMonitor (tuning)Alert analyst[@privacy-lead]
DLP-RUL-004 (Example)CredentialsCode platform, chatSecret pattern detectedBlockBlock push or message, open secret rotation ticket[@platform-lead]
DLP-RUL-005 (Example)Any Confidential labelGenerative AI toolsUpload to an unapproved AI serviceBlockBlock, show approved tool list[@security-engineering-lead]
DLP-RUL-006 (Example)Source codeEndpointCopy of repository folder to USB or personal cloud syncMonitorAlert analyst[@eng-lead]

9. Deployment and tuning

Every new rule follows these stages:

  1. Monitor for at least [4] weeks: alerts only, no user impact.
  2. Review: analysts label each alert true positive, false positive or benign true positive (real data, legitimate business purpose).
  3. Tune: adjust thresholds, add exact data match or exclusions for approved business flows.
  4. Warn for at least [2] weeks where user justification is useful.
  5. Block when precision is at or above the target and the business owner agrees.

Tuning measure: precision = true positives / (true positives + false positives). Target for blocking rules: [90%] or more.

RuleTuning period (Example)AlertsTrue positivesFalse positivesBenign true positivesPrecisionDecision
DLP-RUL-001Weeks 1 to 440373092.5%Move to Block
DLP-RUL-003Weeks 1 to 412030603033.3%Stay in Monitor; add exact data match and exclude the approved hospital transfer channel

In the example, DLP-RUL-003 precision is 30 / (30 + 60) = 33.3%; benign true positives (approved flows) are excluded from the precision formula and handled by adding the flow to the rule's allow list.

Review all active rules at least quarterly, and when a new channel, SaaS service or data type is introduced.

10. DLP alert and incident handling

Severity (Example)ExamplesTriage timeEscalation
HighBlock of Restricted data to external party, bulk export of health dataWithin 1 hour in business hours, next morning otherwiseIncident lead per compliance/incident-response-plan
MediumWarn override with weak justification, repeated attempts1 business dayInformation owner
LowSingle monitor-mode match5 business daysBatch review

Outcomes are recorded in the incident register (isms/incident-register) and, for personal data, in the breach assessment (compliance/personal-data-breach-assessment). Legal notification deadlines (for example 72 hours to the supervisory authority under GDPR Article 33 where a notifiable breach occurs) run from awareness, so High alerts cannot wait for a weekly review.

11. Privacy and staff monitoring

  • DLP-STD-001: Staff are informed of DLP monitoring in the acceptable use policy (compliance/acceptable-use-policy) and the employee security handbook (isms/employee-security-handbook), including what is inspected, why, and who can see results.
  • DLP-STD-002: A DPIA (compliance/dpia) is carried out before deploying content inspection of staff communications where privacy law requires one; employee representatives are consulted where local law or agreements require it.
  • DLP-STD-003: DLP collects the minimum needed: rule matches and metadata by default; full content capture only for High severity rules and kept no longer than [90] days unless part of an open incident.
  • DLP-STD-004: Access to alert content is limited to named DLP analysts, logged, and reviewed quarterly. Private or special category content seen incidentally is not used for any other purpose.
  • DLP-STD-005: DLP is not used for productivity monitoring or performance management.

12. Exceptions

Exceptions use security/security-exception-request. Each records the rule or statement affected, the data and volume, the business reason, compensating controls, the residual risk score (1 to 25, per compliance/risk-methodology), approver and expiry date. Each exception is approved at the authority the risk methodology (DOC-ISMS-010 section 2.4) sets for the residual risk: the risk owner for Low; the risk owner and department head for Medium (top management if the risk category is Averse, DOC-ISMS-015 section 9 rule 1); top management with a treatment decision for High, recorded in the risk acceptance record (DOC-ISMS-019). Critical residual risk is not approvable as an exception: treat it or stop the activity. Maximum duration is 12 months for Low or Medium and 6 months for High; at expiry the exception is reassessed, and a renewal is a new decision (DOC-ISMS-122 section 7). Real data in test is further limited to [14] days (MSK-STD-006).

Exception IDStatement or ruleReasonCompensating controlResidual scoreExpiry
DLP-EXC-001 (Example)DLP-RUL-003Nightly schedule export to a hospital customer over the managed transfer serviceTransfer by managed file transfer with encryption and recipient allow list4 LowYYYY-MM-DD
DLP-EXC-002 (Example)MSK-STD-005Reproduce defect affecting one customer tenantMinimised data set, 2 named engineers, deletion after 14 days6 MediumYYYY-MM-DD

13. Size tiers

AspectSmall: Quillmere Analytics Ltd (46 staff)Medium: Quillmere Health Systems (320 staff)Large: Quillmere Group (2,400 staff, 6 sites)
Main riskCustomer analytics data (as processor) copied to test or personal toolsPatient-related scheduling data leaving to unapproved channels; health data in testDesigns, OT programs and commercial data across 6 sites in 4 countries
MaskingMasking pipeline for staging built into the data platform; dynamic masking in the support consoleKeyed pseudonymisation for analytics; synthetic data for demos to hospitalsCentral data platform policies; pseudonymised HR data for group reporting
DLPSuite DLP on mail and file sharing, secret scanning, endpoint controls via device management; alerts reviewed by the 0.5 FTE ISMS manager and one engineerSuite DLP plus endpoint DLP; 3-person security team triages; DPIA completedDedicated DLP platform, cloud access broker, regional analysts, works council consultation where required
Tuning cadenceQuarterlyMonthlyMonthly per region, central rule board

14. Records and evidence

RecordProvesOwnerLocation (Example)Retention (Example)
Masking rule inventory per data setMSK-STD-005, 007Engineering leadsMasking pipeline repositoryLife of the system
Masking pipeline test resultsFail-closed behaviour worksEngineering leadsCI pipeline records1 year
Unmasking access logsMSK-STD-002Standard ownerCentral logging1 year
Re-identification risk assessmentsMSK-STD-010DPODPIA registerLife of the processing plus 3 years
DLP rule catalogue with versionsRules defined and approvedStandard ownerISMS document store3 years
Tuning reviews and precision figuresSection 9Standard ownerTuning review notes3 years
Alert triage recordsSection 10DLP analystsDLP console export, ticketing system1 year, longer if linked to an incident
Alert content access reviewsDLP-STD-004DPOQuarterly review records3 years
Exception recordsSection 12ISMS managerException register3 years after expiry

15. Control mapping

Control (ISO/IEC 27001:2022 Annex A)Sections
A.8.11 data masking (new in 2022)3 to 6
A.8.12 data leakage prevention (new in 2022)7 to 11
A.5.12 information classification3
A.5.14 information transfer7, 12
A.5.34 privacy and PII protection6, 11
A.8.33 test information5
A.8.31 separation of environments5
A.8.16 monitoring activities10
A.8.23 web filtering7 (DLP-CHN-001, 005)

As international examples, GDPR Article 4(5) defines pseudonymisation and Article 32(1)(a) names pseudonymisation and encryption as possible security measures. Record the laws that bind you in the legal register ([DOC-ISMS-014]).

16. References

ReferenceEdition and status (checked 2026-11-01)Use
ISO/IEC 27001:2022 + Amd 1:2024Current; https://www.iso.org/standard/82875.html and https://www.iso.org/standard/88435.htmlControls A.8.11, A.8.12 and related
ISO/IEC 27002:2022Current; https://www.iso.org/standard/75652.htmlControl guidance
ISO/IEC 27559:2022Current; https://www.iso.org/standard/71677.htmlDe-identification framework
ISO/IEC 29100:2024Current; https://www.iso.org/standard/85938.htmlPrivacy framework
ISO/IEC 27701:2025Current; https://www.iso.org/standard/85819.htmlPrivacy information management
NIST SP 800-188, De-Identifying Government Datasets: Techniques and GovernanceFinal, September 2023De-identification techniques
Regulation (EU) 2016/679 (GDPR)Articles 4(5), 32, 33, 35International example
Related templatesdata/data-classification-policy, isms/information-transfer-policy, isms/secure-development-policy, isms/security-monitoring-procedure, compliance/dpia, compliance/personal-data-breach-assessment, isms/control-evidence-matrix

Standard and licence note

Structure aligned with ISO/IEC 27001:2022 + Amd 1:2024 (Annex A controls A.8.11 and A.8.12) and ISO/IEC 27002:2022, with references to ISO/IEC 27559:2022 and ISO/IEC 29100:2024. Control numbers are cited with short labels written for this template; no text, tables or definitions from ISO or IEC standards are reproduced, and you need the official standards to implement and audit the controls. NIST SP 800-188 is a US government work. EU legal texts are cited by article only. The techniques table, rules and examples are original. Check the current editions and the law that applies to you before use. This is a documentation format, not legal advice.

Template licence: MIT.

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