PRI-24: Data Subject Consent
Mechanisms exist to enable data subjects to authorize the collection, receipt, processing, storage, transmission, sharing, updating and/or disposal of their Personal Data (PD), where the data subject is provided, prior to collection, with: (1) Plain language explaining the potential data privacy risks of the authorization; (2) A means to decline the authorization; and (3) Necessary choice and consent-related criteria required by applicable statutory, regulatory and contractual obligations.
Renumbered: Formerly PRI-03 in SCF 2025.4.
Control Question: Does the organization enable data subjects to authorize the collection, receipt, processing, storage, transmission, sharing, updating and/or disposal of their Personal Data (PD), where the data subject is provided, prior to collection, with: (1) Plain language explaining the potential data privacy risks of the authorization; (2) A means to decline the authorization; and (3) Necessary choice and consent-related criteria required by applicable statutory, regulatory and contractual obligations?
General (14)
| Framework | Mapping Values |
|---|---|
| AICPA Privacy Management Framework (PMF) | N2.1-POF1 C3.1 C3.1-POF1 C3.1-POF3 C3.2 C3.2-POF2 C3.2-POF3 C3.2-POF4 |
| AICPA TSC 2017:2022 (used for SOC 2) (source) | P2.0 P2.1 P2.1-POF1 P2.1-POF2 P2.1-POF3 P2.1-POF5 P2.1-POF6 P3.2 P3.2-POF2 |
| APEC Privacy Framework 2015 | 2(e) 4(a) 5 |
| ISO 27002 2022 | 5.33 |
| ISO 27017 2015 | 18.1.4 |
| ISO 27018 2025 | 5.33 |
| ISO 29100 2024 | 6.2 |
| NIST 800-53 R4 | IP-1 |
| NIST 800-53 R5.2 | PT-04 |
| NIST 800-53B R5 (privacy) (source) | PT-04 |
| NIST 800-82 R3 | PT-04 |
| NIST Privacy Framework 1.0 | CT.PO-P1 CT.PO-P3 |
| OECD Privacy Principles | 1 4(a) |
| SCF DPMP 2026 | 2.0 2.1 2.2 |
US (15)
| Framework | Mapping Values |
|---|---|
| USA Federal CMS MARS-E 2.0 | IP-1 IP-1.a IP-1.b IP-1.c IP-1.d IP-1(1) |
| USA Federal Data Privacy Framework 2023 | II.2.a II.2.c |
| USA Federal 45 CFR 155.260 | 155.260(a)(3)(iv) |
| USA Federal FERPA 2010 | 1232h(b) 1232h(b)(1) 1232h(b)(2) 1232h(b)(3) 1232h(b)(4) 1232h(b)(5) 1232h(b)(6) 1232h(b)(7) 1232h(b)(8) |
| USA Federal HIPAA Administrative Simplification 2013 | § 164.506(b)(1) § 164.508(a)(2) § 164.508(c)(1)(v) § 164.508(c)(3) § 164.510(b)(2)(i) § 164.510(b)(2)(ii) § 164.510(b)(2)(iii) § 164.510(b)(3) § 164.514(f)(2)(ii) § 164.514(f)(2)(iv) § 164.514(f)(2)(v) |
| USA California CCPA 2025 | 7002(e) 7010(b) 7012(a) 7012(b) 7012(c) 7012(d) 7012(e) 7012(e)(1) 7012(e)(2) 7012(e)(3) 7012(e)(4) 7012(e)(5) 7012(e)(6) 7027(c) 7027(d) |
| USA Illinois BIPA 2008 | 15(b)(3) 15(d) 15(d)(1) 15(d)(2) 15(d)(3) 15(d)(4) |
| USA Montana CDPA 2025 | 30-14-2811(3)(a) 30-14-2811(3)(b)(i) 30-14-2812(2)(b) |
| USA Nevada Privacy Law 2023 | 603A.500.2(a) 603A.500.2(b) 603A.500.3 603A.500.3(a) 603A.500.3(b) 603A.500.3(c) 603A.500.3(d) 603A.535.5 603A.535.6 603A.535.6(a) 603A.535.6(b) 603A.535.6(c) 603A.535.6(d) 603A.535.7 |
| USA Oregon CPA 2023 | Section 5(2)(b) Section 5(2)(c) |
| USA Oregon 646A 2025 | 646A.578(6) 646A.583(1)(a)(C) |
| USA Tennessee TIPA 2025 | 47-18-3203(a)(2)(E) 47-18-3203(b) 47-18-3204(a)(6) |
| USA Texas CDPA 2025 | 541.101(b)(4) 541.107(a) |
| USA Texas TRAIGA 2025 | Sec. 2 / 503.001(b-1) 552.054(b) |
| USA Virginia CDPA 2023 | 59.1-578.A.5 59.1-578.D |
EMEA (14)
| Framework | Mapping Values |
|---|---|
| EMEA Austria FAPPD 2000 | § 8(1) § 12(1) § 12(2) § 12(3) § 12(4) |
| EMEA Switzerland FADP 2025 | 2.1.6.6 2.1.6.7 2.1.6.7.a 2.1.6.7.b 2.1.6.7.c |
| EMEA Germany FDPA 2017 | 2.1.2.26(2) 2.1.2.26(3) 2.1.2.27(4) 3.2.51(1) 3.2.51(2) 3.2.51(5) |
| EMEA EU GDPR 2016 | Article 7.1 Article 7.2 Article 9.2(a) Article 21.1 Article 21.2 Article 21.3 Article 21.4 Article 21.5 Article 21.6 |
| EMEA Greece PIRPPD 1997 | B.5.1 B.7.2.a |
| EMEA Hungary Act CXII 2011 | II.5.5(1)(a) II.5.5(2)(a) II.5.6(3) II.5.6(4) II.7.8(1)(a) II.8.9(4) II.11.12(3)(a) II.15.21(1)(a) II.15.21(1)(b) II.15.21(1)(c) |
| EMEA Israel PPL 2025 | s.1 |
| EMEA Kenya DPA 2019 | IV.26(c) IV.28(2)(c) IV.32(4) |
| EMEA Nigeria DPR 2019 | 2.3(2) 2.3(2)(a) 2.3(2)(b) 2.3(2)(c) 2.3(2)(d) 2.3(2)(e) 2.8(b) 2.12(a) 3.1(14)(a) 3.1(14)(b) 3.1(14)(c) |
| EMEA Qatar PDPPL 2020 | 2.4 2.5.2 |
| EMEA Russia 152-FZ 2025 | Art. 6 Art. 9 Art. 10.1 |
| EMEA Saudi Arabia PDPL | Article 5.1 Article 10.1 Article 15.1 Article 24.1 Article 25.1 Article 25.2 Article 25.3 Article 26 |
| EMEA Serbia 87/2018 | II.15 III.3.31 |
| EMEA South Africa POPIA 2013 | 6.57(1) 6.57(1)(a) 6.57(1)(a)(i) 6.57(1)(a)(ii) 6.57(1)(b) 6.57(1)(c) 6.57(1)(d) 6.57(2) 6.57(3) 6.57(4) |
APAC (13)
| Framework | Mapping Values |
|---|---|
| APAC China Cybersecurity Law 2017 | Article 22 |
| APAC China Privacy Law 2021 | Article 14 |
| APAC Hong Kong PDO 2022 | 35E(1) 35E(1)(a) 35E(1)(b) 35E(1)(b)(i) 35E(1)(b)(ii) 35E(1)(b)(iii) 35E(1)(c) 35E(2) 35E(2)(a) 35E(2)(b) 35E(3) 35E(4) Schedule 1 - 1(3)(a)(i) Schedule 1 - 1(3)(a)(ii) Schedule 1 - 1(3)(b) Schedule 1 - 1(3)(b)(i) Schedule 1 - 1(3)(b)(i)(A) Schedule 1 - 1(3)(b)(i)(B) Schedule 1 - 1(3)(b)(ii) Schedule 1 - 1(3)(b)(ii)(A) |
| APAC India DPDPA 2023 | 4(1)(a) 6(1) 6(3) 6(7) 6(10) 7(a) 7(b)(i) 8(8)(b) |
| APAC India ITR 2011 | 5(1) 5(7) |
| APAC India RBI Digital Payments 2021 | 46.0 49.0 |
| APAC Japan APPI 2020 | IV.1.26-2(1)(i) IV.1.26-2(1)(ii) |
| APAC South Korea PIPA 2011 | III.1.15(2) III.1.15(2)1 III.1.15(2)2 III.1.15(2)3 III.1.15(2)4 III.1.17(1) III.1.17(1)1 III.1.17(1)2 III.1.17(2) III.1.17(2)1 III.1.17(2)2 III.1.17(2)3 III.1.17(2)4 III.1.17(2)5 III.1.17(3) III.1.22(3) |
| APAC Malaysia RMiT 2025 | A11-4 |
| APAC Malaysia PDPA 2010 | 7(3) |
| APAC Philippines DPA 2012 | III.12(a) |
| APAC Singapore PDPA 2012 | 4.1.13 4.1.14(1)(b) 4.1.14(3) 4.1.14(4) 4.1.15(1) 4.1.15(1)(a) 4.1.15(1)(b) 4.1.15(2) 4.1.15(3) 4.1.15(6) 4.1.15(6)(a)(i) 4.1.15(6)(a)(ii) 4.1.15(6)(b) 4.1.15(6)(c) 4.1.15(7) 4.1.15(9)(a) 4.1.15(9)(b) 9.3.46(1) |
| APAC Taiwan PDPA 2025 | I.7 |
Americas (6)
| Framework | Mapping Values |
|---|---|
| Americas Bahamas DPA 2003 | II.7(1) IV.32(1) IV.32(2) IV.32(2)(a) IV.32(2)(b) IV.32(2)(c) IV.32(3) IV.32(4) IV.32(5) IV.32(6) IV.36(2) |
| Americas Brazil LGPD 2018 | II.I.7.I II.I.8 II.I.8.1 II.I.8.2 II.I.8.3 II.I.8.4 |
| Americas Canada PIPEDA 2000 | P2-4.2.5 P3-4.3 P3-4.3.1 P3-4.3.2 P3-4.3.3 P3-4.3.4 P3-4.3.5 P3-4.3.6 P3-4.3.7 P3-4.3.7(a) P3-4.3.7(b) P3-4.3.7(c) P3-4.3.7(d) |
| Americas Chile Act 19628 1999 | I.4 I.8 |
| Americas Colombia Law 1581 2012 | II.4(c) VI.17(b) |
| Americas Mexico FDPA 2010 | II.8 II.9 |
Capability Maturity Model
Level 0 — Not Performed
Practices are non-existent, based on the inability to demonstrate an implemented and operational capability. A reasonable person would conclude the control is not being performed.
Level 1 — Performed Informally
SCR-CMM Level 1 criteria definitions are not available for this control: ▪ A reasonable person would conclude this control requires a structured process. ▪ At this level of maturity, the "ad hoc" nature of performing a capability informally would indicate the intent of the control is not met due to a lack of consistency and formality.
Level 2 — Planned & Tracked
Privacy (PRI) capabilities are requirements-driven, but are not standardized across the entity (e.g., local/regional level consistency). Capability criteria associated with this control reasonably expect the following criteria to exist: ▪ Policies and standards associated with PRI domain capabilities are formally documented and centrally-managed by the entity. ▪ Standardized Operating Procedures (SOP) associated with PRI domain capabilities are documented and maintained by process owners. ▪ IT and/or cybersecurity personnel work with business stakeholders and process owners to appropriately scope and reasonably implement cybersecurity and data protection controls associated with PRI domain capabilities to address applicable statutory, regulatory and/or contractual requirements for Technology Assets, Applications, Services and/or Data (TAASD). ▪ Data privacy management-related controls are primarily administrative and preventative in nature (e.g., policies, standards and procedures & guidelines). ▪ Data privacy management may be a defined function (e.g., team or department) or assigned as an additional duty to existing IT and/or cybersecurity personnel. ▪ The data privacy program is developed to work with IT and cybersecurity staff to ensure that applicable statutory, regulatory and/or contractual data privacy obligations for Personal Data (PD) are properly identified and implemented.
Level 3 — Well Defined
Privacy (PRI) capabilities are standardized across the entity for applicability to People, Processes, Technologies, Data and/or Facilities (PPTDF) to ensure consistency for Technology Assets, Applications, Services and/or Data (TAASD). Capability criteria associated with this control reasonably expect the following criteria to exist: ▪ Policies and standards associated with PRI domain capabilities are formally documented and centrally-managed by the entity's Governance, Risk & Compliance (GRC) team, or similar function. ▪ Standardized Operating Procedures (SOP) associated with PRI domain capabilities are well-documented and kept current by process owners. ▪ A data privacy team, or similar function, is appropriately staffed and supported to implement and maintain PRI domain capabilities. ▪ Technology is leveraged to enhance the efficiency and accuracy of data privacy operations (e.g., privacy notice management software and customer management solution). ▪ The entity's Governance, Risk & Compliance (GRC) team, or similar function, works with business stakeholders and process owners to appropriately scope and reasonably implement cybersecurity and data protection controls associated with PRI domain capabilities to address Minimum Compliance Requirements (MCR) (e.g., applicable statutory, regulatory and/or contractual requirements) and Discretionary Security Requirements (DSR) (e.g., entity-required controls). ▪ An implemented and operational capability exists to Mechanisms exist to enable data subjects to authorize the collection, receipt, processing, storage, transmission, sharing, updating and/or disposal of their Personal Data (PD), where the data subject is provided, prior to collection, with: (1) Plain language explaining the potential data privacy risks of the authorization; (2) A means to decline the authorization; and (3) Necessary choice and consent-related criteria required by applicable statutory, regulatory and contractual obligations.
Level 4 — Quantitatively Controlled
Privacy (PRI) capabilities, in addition to being standardized across the entity and centrally managed to ensure consistency across Technology Assets, Applications, Services and/or Data (TAASD), efforts are metrics driven to provide sufficient insight for decision makers to predict optimal performance, ensure continued operations and/or identify areas for improvement. Capability criteria associated with this control reasonably expect the following criteria to exist: ▪ Applicable SCR-CMM Level 3 (Well Defined) capabilities are implemented and operational. ▪ Metrics reporting includes quantitative analysis of Key Performance Indicators (KPIs). ▪ Metrics reporting includes quantitative analysis of Key Risk Indicators (KRIs). ▪ Scope of metrics, KPIs and KRIs covers organization-wide cybersecurity and data protection controls, including functions performed by third-parties. ▪ Organizational leadership maintains a formal process to objectively review and respond to metrics, KPIs and KRIs (e.g., monthly or quarterly review). ▪ Based on metrics analysis, process improvement recommendations are submitted for review and are handled in accordance with change control processes. ▪ Business and technical stakeholders are involved in reviewing and approving proposed changes to evolve capabilities.
Level 5 — Continuously Improving
Utilize SCR-CMM Level 3 or Level 4 (if available) criteria definitions: ▪ There are no defined Level 5 criteria, since it is reasonable to assume a continuously-improving process is not necessary to operationalize this control. ▪ Level 5 capabilities should be considered “world-class” where the control builds on Level 4 capabilities, but are continuously improving through Artificial Intelligence (AI) and/or Machine Learning (ML) technologies. ▪ While it may be possible to develop responsive capabilities for this control through the use of AI and/or ML technologies, the criteria would be organization-specific to define.
Assessment Objectives
- PRI-24_A01 the tools or mechanisms to be implemented for individuals to consent to the processing of their Personal Data (PD) are defined.
- PRI-24_A02 tools or mechanisms are implemented for individuals to consent to the processing of their Personal Data (PD) prior to its collection that facilitates individuals’ informed decision-making.
Evidence Requirements
- E-PRI-10 Data Subject Consent Records
-
Documented evidence of data subject consent management, including opt-in / opt-out records and parent or guardian consent for minors.
Privacy
Technology Recommendations
Micro/Small
- Data classification program
- Data privacy program
- Data Protection Impact Assessment (DPIA)
- Product / project management
Small
- Data classification program
- Data privacy program
- Data Protection Impact Assessment (DPIA)
- Product / project management
Medium
- Data classification program
- Data privacy program
- Data Protection Impact Assessment (DPIA)
- Product / project management
Large
- Data classification program
- Data privacy program
- Data Protection Impact Assessment (DPIA)
- Product / project management
Enterprise
- Data classification program
- Data privacy program
- Data Protection Impact Assessment (DPIA)
- Product / project management