+Article 53 Obligations for providers of general-purpose AI models

Article 53 Obligations for providers of general-purpose AI models

Article 53

Obligations for providers of general-purpose AI models

1.   Providers of general-purpose AI models shall:

(a)

draw up and keep up-to-date the technical documentation of the model, including its training and testing process and the results of its evaluation, which shall contain, at a minimum, the information set out in Annex XI for the purpose of providing it, upon request, to the AI Office and the national competent authorities;

(b)

draw up, keep up-to-date and make available information and documentation to providers of AI systems who intend to integrate the general-purpose AI model into their AI systems. Without prejudice to the need to observe and protect intellectual property rights and confidential business information or trade secrets in accordance with Union and national law, the information and documentation shall:

(i)

enable providers of AI systems to have a good understanding of the capabilities and limitations of the general-purpose AI model and to comply with their obligations pursuant to this Regulation; and

(ii)

contain, at a minimum, the elements set out in Annex XII;

(c)

put in place a policy to comply with Union law on copyright and related rights, and in particular to identify and comply with, including through state-of-the-art technologies, a reservation of rights expressed pursuant to Article 4(3) of Directive (EU) 2019/790;

(d)

draw up and make publicly available a sufficiently detailed summary about the content used for training of the general-purpose AI model, according to a template provided by the AI Office.

2.   The obligations set out in paragraph 1, points (a) and (b), shall not apply to providers of AI models that are released under a free and open-source licence that allows for the access, usage, modification, and distribution of the model, and whose parameters, including the weights, the information on the model architecture, and the information on model usage, are made publicly available. This exception shall not apply to general-purpose AI models with systemic risks.

3.   Providers of general-purpose AI models shall cooperate as necessary with the Commission and the national competent authorities in the exercise of their competences and powers pursuant to this Regulation.

4.   Providers of general-purpose AI models may rely on codes of practice within the meaning of Article 56 to demonstrate compliance with the obligations set out in paragraph 1 of this Article, until a harmonised standard is published. Compliance with European harmonised standards grants providers the presumption of conformity to the extent that those standards cover those obligations. Providers of general-purpose AI models who do not adhere to an approved code of practice or do not comply with a European harmonised standard shall demonstrate alternative adequate means of compliance for assessment by the Commission.

5.   For the purpose of facilitating compliance with Annex XI, in particular points 2 (d) and (e) thereof, the Commission is empowered to adopt delegated acts in accordance with Article 97 to detail measurement and calculation methodologies with a view to allowing for comparable and verifiable documentation.

6.   The Commission is empowered to adopt delegated acts in accordance with Article 97(2) to amend Annexes XI and XII in light of evolving technological developments.

7.   Any information or documentation obtained pursuant to this Article, including trade secrets, shall be treated in accordance with the confidentiality obligations set out in Article 78.

1. Übersicht

1.1 Referenzen

1.2 Identifizierte Anforderungen

1.3 Related Standards

2. Identifizierte Anforderungen

Anforderungen

3. Related Standards

Standards
SCF AI & Autonomous Technologies Intellectual Property Infringement Protections

Description

Mechanisms exist to prevent third-party Intellectual Property (IP) rights infringement by Artificial Intelligence (AI) and Autonomous Technologies (AAT).

Possible Solutions & Considerations

Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2

∙ Legal review
∙ Artificial Intelligence (AI) / autonomous technologies governance program

Small Business (10-49 staff) / BLS Firm Size Classes 3-4

∙ Legal review
∙ Artificial Intelligence (AI) / autonomous technologies governance program

Medium Business (50-249 staff) / BLS Firm Size Classes 5-6

∙ Legal review
∙ Steering committee
∙ Board of Directors (BoD)
∙ Artificial Intelligence (AI) / autonomous technologies governance program

Large Business (250-999 staff) / BLS Firm Size Classes 7-8

∙ Legal review
∙ Steering committee
∙ Board of Directors (BoD)
∙ Artificial Intelligence (AI) / autonomous technologies governance program

Enterprise (> 1,000 staff) / BLS Firm Size Class 9

∙ Legal review
∙ Steering committee
∙ Board of Directors (BoD)
∙ Artificial Intelligence (AI) / autonomous technologies governance program

SCR-CMM

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

Artificial Intelligence and Autonomous Technology (AAT) domain capabilities are ad hoc and inconsistent. Capability criteria associated with this control may include:
▪ Policies, standards & procedures associated with AAT domain capabilities provide limited coverage due to the depth and breadth of the existing documentation.
▪ AAT-related processes are expected to follow the organization's existing processes (e.g., incident response, asset management, change control, risk assessments, etc.).
▪ No formal Governance, Risk & Compliance (GRC) team exists to provide AAT oversight, where the Chief Information Officer (CIO), or similar function, governs technology decisions what is acceptable for AAT within the organization.

Level 2 Planned Tracked

Artificial Intelligence and Autonomous Technology (AAT) 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 AAT domain capabilities are formally documented and centrally-managed by the entity.
▪ Standardized Operating Procedures (SOP) associated with AAT 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 AAT domain capabilities to address applicable statutory, regulatory and/or contractual requirements for Technology Assets, Applications, Services and/or Data (TAASD).
▪ Artificial Intelligence (AI)-related controls are primarily administrative and preventative in nature (e.g., policies, standards, procedures & guidelines).
▪ Asset management may be a defined function (e.g., team or department) or assigned as an additional duty to existing IT and/or cybersecurity personnel.
▪ AAT is regarded as a technology and governed by the entity's existing IT governance practices.
▪ No formal Governance, Risk & Compliance (GRC) team exists to provide oversight of AAT-related activities. GRC functions are assigned to existing IT and/or cybersecurity personnel.

Level 3 Well Defined

Artificial Intelligence and Autonomous Technology (AAT) 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 AAT 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 AAT domain capabilities are well-documented and kept current by process owners.
▪ An Artificial Intelligence Governance (AIG) team, or similar function, is appropriately staffed and supported to implement and maintain AAT domain capabilities.
▪ Technology is leveraged to enhance the efficiency and accuracy of AI governance, risk management and compliance operations (e.g., dedicated AI governance platform).
▪ 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 AAT 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 prevent third-party Intellectual Property (IP) rights infringement by AAT.

Level 4 Quantitatively Controlled

Utilize SCR-CMM Level 3 criteria definitions:
▪ There are no defined Level 4 criteria, since it is reasonable to assume a quantitatively-controlled process is not necessary to operationalize this control.
▪ While it may be possible to develop “metrics-driven” capabilities for this control, the criteria would be organization-specific to define.

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.
SCF Data Source Lineage & Origin Disclosure

Description

Mechanisms exist to ensure Artificial Intelligence and Autonomous Technologies (AAT) publicly disclose information with sufficient detail to assess:
(1) Content lineage; and
(2) The origin of data used by the AAT.

Possible Solutions & Considerations

Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2

∙ Disclose data sources used by AI tools in user documentation

Small Business (10-49 staff) / BLS Firm Size Classes 3-4

∙ Policy requiring disclosure of AI training data sources

Medium Business (50-249 staff) / BLS Firm Size Classes 5-6

∙ Formal AI transparency policy
∙ Data source disclosure in user documentation

Large Business (250-999 staff) / BLS Firm Size Classes 7-8

∙ AI transparency program
∙ Public disclosure of data lineage
∙ Model cards with data sourcing

Enterprise (> 1,000 staff) / BLS Firm Size Class 9

∙ Enterprise AI transparency framework
∙ Automated disclosure generation
∙ Regulatory compliance tracking for AI transparency

SCR-CMM

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

Artificial Intelligence and Autonomous Technology (AAT) domain capabilities are ad hoc and inconsistent. Capability criteria associated with this control may include:
▪ Policies, standards & procedures associated with AAT domain capabilities provide limited coverage due to the depth and breadth of the existing documentation.
▪ AAT-related processes are expected to follow the organization's existing processes (e.g., incident response, asset management, change control, risk assessments, etc.).
▪ No formal Governance, Risk & Compliance (GRC) team exists to provide AAT oversight, where the Chief Information Officer (CIO), or similar function, governs technology decisions what is acceptable for AAT within the organization.

Level 2 Planned Tracked

Artificial Intelligence and Autonomous Technology (AAT) 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 AAT domain capabilities are formally documented and centrally-managed by the entity.
▪ Standardized Operating Procedures (SOP) associated with AAT 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 AAT domain capabilities to address applicable statutory, regulatory and/or contractual requirements for Technology Assets, Applications, Services and/or Data (TAASD).
▪ Artificial Intelligence (AI)-related controls are primarily administrative and preventative in nature (e.g., policies, standards, procedures & guidelines).
▪ Asset management may be a defined function (e.g., team or department) or assigned as an additional duty to existing IT and/or cybersecurity personnel.

Level 3 Well Defined

Artificial Intelligence and Autonomous Technology (AAT) 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 AAT 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 AAT domain capabilities are well-documented and kept current by process owners.
▪ An Artificial Intelligence Governance (AIG) team, or similar function, is appropriately staffed and supported to implement and maintain AAT domain capabilities.
▪ Technology is leveraged to enhance the efficiency and accuracy of AI governance, risk management and compliance operations (e.g., dedicated AI governance platform).
▪ 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 AAT 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 ensure Artificial Intelligence and Autonomous Technologies (AAT) publicly disclose information with sufficient detail to assess:
(1) Content lineage; and
(2) The origin of data used by the AAT.

Level 4 Quantitatively Controlled

Utilize SCR-CMM Level 3 criteria definitions:
▪ There are no defined Level 4 criteria, since it is reasonable to assume a quantitatively-controlled process is not necessary to operationalize this control.
▪ While it may be possible to develop “metrics-driven” capabilities for this control, the criteria would be organization-specific to define.

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.
SCF AI & Autonomous Technologies Implementation Documentation

Description

Mechanisms exist to ensure Artificial Intelligence (AI) and Autonomous Technologies (AAT) include clear and concise documentation that is relevant, accessible and comprehensible to personnel implementing and maintaining the AAT that, at a minimum, provides:
(1) Contact details of the provider;
(2) Characteristics, capabilities and limitations of performance of the AAT;
(3) Errata from the AAT's initial conformity assessment;
(4) Details necessary to interpret the outputs of the AAT;
(5) Human oversight measures necessary to facilitate the interpretation of the outputs of the AAT;
(6) Computational and hardware resources needed to operate the AAT;
(7) Projected useable lifetime of the AAT; and
(8) A description of the mechanisms included within the AAT system to properly collect, store and interpret event logs.

Possible Solutions & Considerations

Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2

∙ Document AI implementation steps and configuration

Small Business (10-49 staff) / BLS Firm Size Classes 3-4

∙ AI implementation documentation template

Medium Business (50-249 staff) / BLS Firm Size Classes 5-6

∙ Formal AI implementation documentation policy
∙ Technical documentation requirements

Large Business (250-999 staff) / BLS Firm Size Classes 7-8

∙ AI documentation program
∙ Standardized implementation documentation templates

Enterprise (> 1,000 staff) / BLS Firm Size Class 9

∙ Enterprise AI documentation platform
∙ Automated documentation generation from MLOps tools
∙ Model cards and system cards

SCR-CMM

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

Artificial Intelligence and Autonomous Technology (AAT) domain capabilities are ad hoc and inconsistent. Capability criteria associated with this control may include:
▪ Policies, standards & procedures associated with AAT domain capabilities provide limited coverage due to the depth and breadth of the existing documentation.
▪ AAT-related processes are expected to follow the organization's existing processes (e.g., incident response, asset management, change control, risk assessments, etc.).
▪ No formal Governance, Risk & Compliance (GRC) team exists to provide AAT oversight, where the Chief Information Officer (CIO), or similar function, governs technology decisions what is acceptable for AAT within the organization.

Level 2 Planned Tracked

Artificial Intelligence and Autonomous Technology (AAT) 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 AAT domain capabilities are formally documented and centrally-managed by the entity.
▪ Standardized Operating Procedures (SOP) associated with AAT 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 AAT domain capabilities to address applicable statutory, regulatory and/or contractual requirements for Technology Assets, Applications, Services and/or Data (TAASD).
▪ Artificial Intelligence (AI)-related controls are primarily administrative and preventative in nature (e.g., policies, standards, procedures & guidelines).
▪ Asset management may be a defined function (e.g., team or department) or assigned as an additional duty to existing IT and/or cybersecurity personnel.

Level 3 Well Defined

Artificial Intelligence and Autonomous Technology (AAT) 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 AAT 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 AAT domain capabilities are well-documented and kept current by process owners.
▪ An Artificial Intelligence Governance (AIG) team, or similar function, is appropriately staffed and supported to implement and maintain AAT domain capabilities.
▪ Technology is leveraged to enhance the efficiency and accuracy of AI governance, risk management and compliance operations (e.g., dedicated AI governance platform).
▪ 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 AAT 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 ensure AAT include clear and concise documentation that is relevant, accessible and comprehensible to personnel implementing and maintaining the AAT that, at a minimum, provides:
(1) Contact details of the provider;
(2) Characteristics, capabilities and limitations of performance of the AAT;
(3) Errata from the AAT's initial conformity assessment;
(4) Details necessary to interpret the outputs of the AAT;
(5) Human oversight measures necessary to facilitate the interpretation of the outputs of the AAT;
(6) Computational and hardware resources needed to operate the AAT;
(7) Projected useable lifetime of the AAT; and
(8) A description of the mechanisms included within the AAT system to properly collect, store and interpret event logs.

Level 4 Quantitatively Controlled

Utilize SCR-CMM Level 3 criteria definitions:
▪ There are no defined Level 4 criteria, since it is reasonable to assume a quantitatively-controlled process is not necessary to operationalize this control.
▪ While it may be possible to develop “metrics-driven” capabilities for this control, the criteria would be organization-specific to define.

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.
SCF Product Conformity Governance

Description

Mechanisms exist to ensure developed Technology Assets, Applications and/or Services (TAAS) conform to applicable statutory and regulatory requirements, based on the product's and/or service's:
(1) Use case(s); and
(2) Geographic markets.

Possible Solutions & Considerations

Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2

Small Business (10-49 staff) / BLS Firm Size Classes 3-4

Medium Business (50-249 staff) / BLS Firm Size Classes 5-6

Large Business (250-999 staff) / BLS Firm Size Classes 7-8

∙ Formal software release management process with security review

Enterprise (> 1,000 staff) / BLS Firm Size Class 9

∙ Enterprise software release management platform with security gates (e.g., JFrog Artifactory)
∙ Release approval workflows

SCR-CMM

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

Technology Development & Acquisition (TDA) 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 TDA domain capabilities are formally documented and centrally-managed by the entity.
▪ Standardized Operating Procedures (SOP) associated with TDA 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 TDA domain capabilities to address applicable statutory, regulatory and/or contractual requirements for Technology Assets, Applications, Services and/or Data (TAASD).
▪ Technology development and acquisition-related controls are primarily administrative and preventative in nature (e.g., policies, standards, procedures & guidelines).
▪ Technology development and acquisition management may be a defined function (e.g., team or department) or assigned as an additional duty to existing IT and/or cybersecurity personnel.
▪ Secure development practices mostly conform to industry-recognized standards for secure engineering of Technology Assets, Applications and/or Services (TAAS) (e.g., OWASP, NIST SP 800-218, NIST SP 800-160, etc.).
▪ An application development team, or similar function, uses a structured process to design, build and maintain secure configurations for test, development, staging and production environments.

Level 3 Well Defined

Technology Development & Acquisition (TDA) 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 TDA 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 TDA domain capabilities are well-documented and kept current by process owners.
▪ A software development team, or similar function, is appropriately staffed and supported to implement and maintain TDA domain capabilities.
▪ Technology is leveraged to enhance the efficiency and accuracy of technology development and acquisition management (e.g., project management software, software escrow solution, software testing tools, etc.).
▪ 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 TDA 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 ensure developed Technology Assets, Applications and/or Services (TAAS) conform to applicable statutory and regulatory requirements, based on the product's and/or service's:
(1) Use case(s); and
(2) Geographic markets.

Level 4 Quantitatively Controlled

Utilize SCR-CMM Level 3 criteria definitions:
▪ There are no defined Level 4 criteria, since it is reasonable to assume a quantitatively-controlled process is not necessary to operationalize this control.
▪ While it may be possible to develop “metrics-driven” capabilities for this control, the criteria would be organization-specific to define.

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.
SCF Technical Documentation Artifacts

Description

Mechanisms exist to generate appropriate technical documentation artifacts for Technology Assets, Applications and/or Services (TAAS) in sufficient detail to demonstrate conformity with applicable statutory, regulatory and contractual compliance requirements.

Possible Solutions & Considerations

Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2

Small Business (10-49 staff) / BLS Firm Size Classes 3-4

Medium Business (50-249 staff) / BLS Firm Size Classes 5-6

Large Business (250-999 staff) / BLS Firm Size Classes 7-8

∙ Formal hardware/firmware security review in acquisition

Enterprise (> 1,000 staff) / BLS Firm Size Class 9

∙ Enterprise hardware security program
∙ Firmware security analysis
∙ Hardware supply chain security

SCR-CMM

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

Technology Development & Acquisition (TDA) 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 TDA domain capabilities are formally documented and centrally-managed by the entity.
▪ Standardized Operating Procedures (SOP) associated with TDA 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 TDA domain capabilities to address applicable statutory, regulatory and/or contractual requirements for Technology Assets, Applications, Services and/or Data (TAASD).
▪ Technology development and acquisition-related controls are primarily administrative and preventative in nature (e.g., policies, standards, procedures & guidelines).
▪ Technology development and acquisition management may be a defined function (e.g., team or department) or assigned as an additional duty to existing IT and/or cybersecurity personnel.
▪ Secure development practices mostly conform to industry-recognized standards for secure engineering of Technology Assets, Applications and/or Services (TAAS) (e.g., OWASP, NIST SP 800-218, NIST SP 800-160, etc.).
▪ An application development team, or similar function, uses a structured process to design, build and maintain secure configurations for test, development, staging and production environments.

Level 3 Well Defined

Technology Development & Acquisition (TDA) 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 TDA 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 TDA domain capabilities are well-documented and kept current by process owners.
▪ A software development team, or similar function, is appropriately staffed and supported to implement and maintain TDA domain capabilities.
▪ Technology is leveraged to enhance the efficiency and accuracy of technology development and acquisition management (e.g., project management software, software escrow solution, software testing tools, etc.).
▪ 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 TDA 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 generate appropriate technical documentation artifacts for Technology Assets, Applications and/or Services (TAAS) in sufficient detail to demonstrate conformity with applicable statutory, regulatory and contractual compliance requirements.

Level 4 Quantitatively Controlled

Utilize SCR-CMM Level 3 criteria definitions:
▪ There are no defined Level 4 criteria, since it is reasonable to assume a quantitatively-controlled process is not necessary to operationalize this control.
▪ While it may be possible to develop “metrics-driven” capabilities for this control, the criteria would be organization-specific to define.

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.
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