+AI Agent Governance
---+Infrastructure Hardening & Isolation
---+AI Agent Limitations
---+Tool & Application Programming Interface (API) Invocation Controls
---+AI Agent Orchestration Protocol Safeguards
---+AI Agent Data Pipeline & Input Integrity
---+AI Agent Privileged Role & Delegation Boundaries
---+AI Agent Data Access Restrictions
---+AI Agent Data Extraction
---+AI Agent Identity & Impersonation Defense
---+AI Agent Logic Integrity
---+Sandboxing AI Agents
---+AI Agent Prompt Injection Defense
---+AI Agent Kill Switch / User Control
---+AI Agent Adversarial & Red Team Testing
---+AI Agent Self-Modification Controls
---+Purging AI Agent Data
---+AI Agent Delegation and Chaining Control
---+AI Agent Behavioral Drift Detection
---+AI Agent Action Authentication & Authorization
---+AI Agent Transparency & Audit
---+AI Agent Explainability
---+AI Agent Ethics, Fairness & Bias Detection
---+AI Agent Output Integrity & Verification
---+AI Agent Resource Limiting

AI Agent Governance

Description

Mechanisms exist to ensure AI agents are designed, developed and deployed to securely operate under human oversight.

Possible Solutions & Considerations

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

∙ Document oversight requirements for any AI agent deployments

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

∙ AI agent governance policy with human oversight requirements

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

∙ Formal AI agent governance framework
∙ Human oversight requirements

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

∙ AI agent governance program
∙ Formal oversight model with defined roles and controls

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

∙ Enterprise AI agent governance framework
∙ Dedicated AI agent oversight team
∙ Zero-trust agent architecture

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

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 and 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 ensure AI agents are designed, developed and deployed to securely operate under human oversight.

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.

1. Übersicht

Bezeichnung	Standard
Infrastructure Hardening & Isolation	Description Mechanisms exist to protect, isolate and harden infrastructure resources used by AI agents, including: (1) Resource allocation; (2) Privilege management; (3) Network segmentation; and (4) Workload isolation. Possible Solutions & Considerations Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2 ∙ Use isolated environments for any AI agent deployments Small Business (10-49 staff) / BLS Firm Size Classes 3-4 ∙ Network isolation and least-privilege for AI agent infrastructure Medium Business (50-249 staff) / BLS Firm Size Classes 5-6 ∙ Formal AI agent infrastructure hardening policy ∙ Isolation and privilege controls Large Business (250-999 staff) / BLS Firm Size Classes 7-8 ∙ AI agent infrastructure hardening program ∙ Network segmentation, privilege management Enterprise (> 1,000 staff) / BLS Firm Size Class 9 ∙ Enterprise AI agent infrastructure security framework ∙ Zero-trust network architecture ∙ Container isolation (e.g., Kubernetes) 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 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 and 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 protect, isolate and harden infrastructure resources used by AI agents, including: (1) Resource allocation; (2) Privilege management; (3) Network segmentation; and (4) Workload isolation. 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.
AI Agent Limitations	Description Mechanisms exist to implement limitations for AI agents according to: (1) Least privileges, where the AI agent operates with the minimal permissions necessary to perform designated tasks; and (2) Least functionality, where the AI agent is restricted to communicate with the minimal Technology Assets, Applications and/or Services (TAAS) and networks necessary to perform designated tasks. Possible Solutions & Considerations Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2 ∙ Apply least privilege to AI agent accounts/access Small Business (10-49 staff) / BLS Firm Size Classes 3-4 ∙ Least-privilege and minimal footprint for AI agent configurations Medium Business (50-249 staff) / BLS Firm Size Classes 5-6 ∙ Formal AI agent access control policy with least-privilege requirements Large Business (250-999 staff) / BLS Firm Size Classes 7-8 ∙ AI agent privilege management program ∙ Automated enforcement of least-privilege Enterprise (> 1,000 staff) / BLS Firm Size Class 9 ∙ Enterprise AI agent access governance platform ∙ PAM integration for AI agents ∙ Just-in-time access for AI agents 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 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 and 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 implement limitations for AI agents according to: (1) Least privileges, where the AI agent operates with the minimal permissions necessary to perform designated tasks; and (2) Least functionality, where the AI agent is restricted to communicate with the minimal Technology Assets, Applications and/or Services (TAAS) and networks necessary to perform designated tasks. 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.
Tool & Application Programming Interface (API) Invocation Controls	Description Mechanisms exist to authenticate, authorize, validate and monitor all tool and Application Programming Interface (API) invocations by AI agents, including: (1) Schema validation; (2) Rate limiting; (3) Access controls; and (4) Output validation. Possible Solutions & Considerations Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2 ∙ Authenticate and log AI agent tool/API calls Small Business (10-49 staff) / BLS Firm Size Classes 3-4 ∙ API key management and logging for AI agent tool calls Medium Business (50-249 staff) / BLS Firm Size Classes 5-6 ∙ Formal AI agent tool invocation control policy ∙ Authentication, authorization, and logging Large Business (250-999 staff) / BLS Firm Size Classes 7-8 ∙ AI agent API governance program ∙ Schema validation, rate limiting, and audit logging Enterprise (> 1,000 staff) / BLS Firm Size Class 9 ∙ Enterprise AI agent API security platform ∙ Zero-trust API security ∙ Automated schema validation ∙ Rate limiting and anomaly detection 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 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 and 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 authenticate, authorize, validate and monitor all tool and Application Programming Interface (API) invocations by AI agents, including; (1) Schema validation; (2) Rate limiting; (3) Access controls; and (4) Output validation. 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.
AI Agent Orchestration Protocol Safeguards	Description Mechanisms exist to validate, secure and restrict AI agent orchestration protocols to prevent: (1) Unauthorized tool chaining; (2) Context manipulation; and/or (3) Protocol-based escalation. Possible Solutions & Considerations Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2 ∙ Limit AI agents to approved tools only Small Business (10-49 staff) / BLS Firm Size Classes 3-4 ∙ Whitelist approved tools/protocols for AI agents Medium Business (50-249 staff) / BLS Firm Size Classes 5-6 ∙ Formal AI agent orchestration security policy ∙ Protocol safeguards Large Business (250-999 staff) / BLS Firm Size Classes 7-8 ∙ AI agent orchestration security program ∙ Protocol validation and restriction controls Enterprise (> 1,000 staff) / BLS Firm Size Class 9 ∙ Enterprise AI agent orchestration security framework ∙ Automated protocol enforcement ∙ Context integrity validation 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 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 and 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 validate, secure and restrict AI agent orchestration protocols to prevent: (1) Unauthorized tool chaining; (2) Context manipulation; and/or (3) Protocol-based escalation. 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.
AI Agent Data Pipeline & Input Integrity	Description Mechanisms exist to validate, sanitize and monitor all data inputs and retrieval pipelines for AI agents to: (1) Ensure data provenance; and (2) Prevent unauthorized access risks (e.g., injection, manipulation or exfiltration). Possible Solutions & Considerations Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2 ∙ Validate inputs to AI agents before processing Small Business (10-49 staff) / BLS Firm Size Classes 3-4 ∙ Input validation and sanitization for AI agent data pipelines Medium Business (50-249 staff) / BLS Firm Size Classes 5-6 ∙ Formal AI agent input integrity policy ∙ Validation and sanitization procedures Large Business (250-999 staff) / BLS Firm Size Classes 7-8 ∙ AI agent data pipeline security program ∙ Automated input validation and provenance tracking Enterprise (> 1,000 staff) / BLS Firm Size Class 9 ∙ Enterprise AI agent data integrity platform ∙ Data provenance tools ∙ Automated sanitization pipelines 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 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 and 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 validate, sanitize and monitor all data inputs and retrieval pipelines for AI agents to: (1) Ensure data provenance; and (2) Prevent unauthorized access risks (e.g., injection, manipulation or exfiltration). 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.
AI Agent Privileged Role & Delegation Boundaries	Description Mechanisms exist to prevent privilege escalation or unauthorized delegation by AI agents by: (1) Monitoring and enforcing dynamic roles; and (2) Establishing cross-agent delegation boundaries and privileged actions. Possible Solutions & Considerations Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2 ∙ Grant AI agents only the specific permissions needed; no delegation to other tools without approval Small Business (10-49 staff) / BLS Firm Size Classes 3-4 ∙ Least-privilege roles for AI agents ∙ Documented delegation boundaries Medium Business (50-249 staff) / BLS Firm Size Classes 5-6 ∙ RBAC/ABAC for AI agent identities ∙ Delegation limits enforced in orchestration framework ∙ Privilege escalation monitoring Large Business (250-999 staff) / BLS Firm Size Classes 7-8 ∙ Identity governance for AI agents (non-human identity management) ∙ Dynamic role enforcement and delegation policies ∙ PAM for privileged agent actions Enterprise (> 1,000 staff) / BLS Firm Size Class 9 ∙ Enterprise AI agent identity governance with dynamic role enforcement, delegation boundaries and escalation detection ∙ Integration with IGA/PAM and AI gateway 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 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 and 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 prevent privilege escalation or unauthorized delegation by AI agents by: (1) Monitoring and enforcing dynamic roles; and (2) Establishing cross-agent delegation boundaries and privileged actions. 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.
AI Agent Data Access Restrictions	Description Mechanisms exist to restrict AI agent access to sensitive and/or regulated data so that AI agents cannot ingest, generate or act on unauthorized data without proper permissions. Possible Solutions & Considerations Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2 ∙ Do not connect AI tools to sensitive data sources without approval ∙ Use data classification labels Small Business (10-49 staff) / BLS Firm Size Classes 3-4 ∙ AI agent data access limited by role and data classification ∙ Approved data connectors only Medium Business (50-249 staff) / BLS Firm Size Classes 5-6 ∙ Data access policies for AI agents aligned with data classification ∙ DLP on AI inputs/outputs ∙ Approved connector governance Large Business (250-999 staff) / BLS Firm Size Classes 7-8 ∙ AI gateway/data access layer enforcing classification-based restrictions ∙ DLP and sensitive data detection for AI pipelines ∙ Access logging Enterprise (> 1,000 staff) / BLS Firm Size Class 9 ∙ Enterprise AI data access governance (AI gateway, entitlements, DLP, data classification enforcement) ∙ Continuous monitoring of AI data access 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 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 and 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 restrict agent access to sensitive/regulated data so that AI agents cannot ingest, generate or act on unauthorized data. 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.
AI Agent Data Extraction	Description Mechanisms exist to prevent AI agents from extracting sensitive and/or regulated data from volatile memory that can be exploited at a later point. Possible Solutions & Considerations Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2 ∙ Note: Typically not required at this size; use vendor AI services with documented data handling Small Business (10-49 staff) / BLS Firm Size Classes 3-4 ∙ Vendor assurance that AI services do not retain sensitive session data ∙ Session data clearing Medium Business (50-249 staff) / BLS Firm Size Classes 5-6 ∙ Memory/session isolation for AI agents ∙ Sensitive data redaction before AI processing ∙ Vendor data retention controls Large Business (250-999 staff) / BLS Firm Size Classes 7-8 ∙ Secure AI runtime environments with memory isolation and data scrubbing ∙ Monitoring for data extraction attempts Enterprise (> 1,000 staff) / BLS Firm Size Class 9 ∙ Enterprise AI runtime security (memory isolation, ephemeral contexts, redaction, extraction attempt detection) ∙ AI security platform integration 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 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 and 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 prevent AI agents from extracting sensitive/regulated data from volatile memory that can be exploited at a later point. 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.
AI Agent Identity & Impersonation Defense	Description Mechanisms exist to ensure user identification and authentication methods are capable of preventing AI agents from (1) Spoofing; (2) Mimicry; and/or (3) Impersonation attacks. Possible Solutions & Considerations Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2 ∙ MFA for all users; no AI tools acting with shared credentials Small Business (10-49 staff) / BLS Firm Size Classes 3-4 ∙ Phishing-resistant MFA ∙ AI agents use distinct identities (not user credentials) Medium Business (50-249 staff) / BLS Firm Size Classes 5-6 ∙ Phishing-resistant MFA and device binding ∙ Distinct AI agent identities with anti-spoofing controls ∙ Behavioral analytics Large Business (250-999 staff) / BLS Firm Size Classes 7-8 ∙ Identity verification resistant to AI-driven impersonation (FIDO2, liveness detection) ∙ AI agent identity assurance ∙ Fraud analytics Enterprise (> 1,000 staff) / BLS Firm Size Class 9 ∙ Enterprise identity assurance program addressing AI impersonation (phishing-resistant MFA, identity proofing, deepfake detection, agent identity attestation) 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 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 and 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 user identification and authentication methods are capable of preventing AI agents from (1) Spoofing; (2) Mimicry; and/or (3) Impersonation attacks. 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.
AI Agent Logic Integrity	Description Mechanisms exist to prevent AI agent logic from being subverted or manipulated. Possible Solutions & Considerations Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2 ∙ Use reputable AI providers; keep system prompts and configurations under change control Small Business (10-49 staff) / BLS Firm Size Classes 3-4 ∙ Version control and review for AI agent instructions/configurations ∙ Integrity checks Medium Business (50-249 staff) / BLS Firm Size Classes 5-6 ∙ Change control and integrity monitoring for agent logic, prompts and tools ∙ Model and prompt signing/versioning Large Business (250-999 staff) / BLS Firm Size Classes 7-8 ∙ AI supply chain integrity (model provenance, signed artifacts) ∙ Runtime integrity monitoring of agent logic ∙ Adversarial testing Enterprise (> 1,000 staff) / BLS Firm Size Class 9 ∙ Enterprise AI integrity program (model/prompt provenance, signed artifacts, runtime attestation, tamper detection) ∙ AI security platform (e.g., Protect AI, HiddenLayer) 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 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 and 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 prevent AI agent logic from being subverted or manipulated. 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.
Sandboxing AI Agents	Description Mechanisms exist to utilize a "sandbox" capability to restrict AI agents from unrestricted access to both local and remote resources. Possible Solutions & Considerations Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2 ∙ Run AI tools with limited permissions; avoid granting file system or network access Small Business (10-49 staff) / BLS Firm Size Classes 3-4 ∙ Sandboxed execution for AI agent tools (containers, restricted accounts) Medium Business (50-249 staff) / BLS Firm Size Classes 5-6 ∙ Containerized/sandboxed AI agent execution with network and resource restrictions ∙ Tool allow-listing Large Business (250-999 staff) / BLS Firm Size Classes 7-8 ∙ Isolated AI execution environments (e.g., gVisor, Firecracker, dedicated VPCs) with egress control ∙ Tool/API allow-listing Enterprise (> 1,000 staff) / BLS Firm Size Class 9 ∙ Enterprise AI sandboxing architecture (isolated runtimes, egress filtering, resource quotas, tool allow-listing) ∙ Continuous monitoring of sandbox escapes 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 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 and 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 utilize a "sandbox" capability to restrict AI agents from unrestricted access to both local and remote resources. 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.
AI Agent Prompt Injection Defense	Description Mechanisms exist to detect and mitigate prompt injection / input attacks that seek to manipulate AI agent instructions, bypass security, compliance and/or resilience controls or result in unauthorized actions. Possible Solutions & Considerations Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2 ∙ Use AI services with built-in prompt injection protections; validate outputs before acting Small Business (10-49 staff) / BLS Firm Size Classes 3-4 ∙ Input/output filtering for AI applications ∙ Separation of instructions from untrusted content Medium Business (50-249 staff) / BLS Firm Size Classes 5-6 ∙ Prompt injection defenses (input sanitization, instruction hierarchy, output validation) ∙ OWASP LLM Top 10 alignment ∙ Red team testing Large Business (250-999 staff) / BLS Firm Size Classes 7-8 ∙ AI firewall/guardrails platform (e.g., Lakera, Prompt Security, Azure AI Content Safety) ∙ Continuous prompt injection testing Enterprise (> 1,000 staff) / BLS Firm Size Class 9 ∙ Enterprise AI guardrail platform with prompt injection detection and response ∙ Adversarial testing program ∙ SIEM integration for AI attacks 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 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 and 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 detect and mitigate prompt injection / input attacks that seek to manipulate AI agent instructions, bypass security, compliance and/or resilience controls or result in unauthorized actions. 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.
AI Agent Kill Switch / User Control	Description Mechanisms exist to allow authorized users or operators to immediately halt or disable AI agent activity in case of unexpected behavior or harm. Possible Solutions & Considerations Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2 ∙ Ability to disable AI tools/integrations immediately (admin console) Small Business (10-49 staff) / BLS Firm Size Classes 3-4 ∙ Documented procedure and access to disable AI agents ∙ Kill switch tested Medium Business (50-249 staff) / BLS Firm Size Classes 5-6 ∙ Kill switch capability for AI agents (feature flags, API key revocation, orchestration halt) ∙ Operator authority defined Large Business (250-999 staff) / BLS Firm Size Classes 7-8 ∙ Centralized AI agent control plane with immediate halt capability ∙ Runbooks and drills ∙ Authorization for kill switch use Enterprise (> 1,000 staff) / BLS Firm Size Class 9 ∙ Enterprise AI operations control plane with graduated halt/disable capabilities, automated triggers and tested procedures 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 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 and 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 allow authorized users or operators to immediately halt or disable AI agent activity in case of unexpected behavior or harm. 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.
AI Agent Adversarial & Red Team Testing	Description Mechanisms exist to regularly conduct adversarial testing that simulates attacks against AI agents to identify and mitigate vulnerabilities. Possible Solutions & Considerations Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2 ∙ Note: Typically not required at this size; test AI tools with adversarial prompts before deployment Small Business (10-49 staff) / BLS Firm Size Classes 3-4 ∙ Periodic adversarial testing of AI applications (manual red teaming) Medium Business (50-249 staff) / BLS Firm Size Classes 5-6 ∙ AI red teaming before deployment and periodically (e.g., OWASP LLM testing, PyRIT, garak) ∙ Findings tracked to closure Large Business (250-999 staff) / BLS Firm Size Classes 7-8 ∙ Formal AI red team program (internal or third-party) ∙ Automated adversarial testing tools (e.g., PyRIT, garak, Mindgard) ∙ Integration with SDLC Enterprise (> 1,000 staff) / BLS Firm Size Class 9 ∙ Enterprise AI red teaming program with continuous adversarial testing, third-party assessments and threat intelligence 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 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 and 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 regularly conduct adversarial testing that simulates attacks against AI agents to identify and mitigate vulnerabilities. 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.
AI Agent Self-Modification Controls	Description Mechanisms exist to control, restrict and log AI agent self-modification. Possible Solutions & Considerations Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2 ∙ Do not allow AI tools to change their own configuration or code Small Business (10-49 staff) / BLS Firm Size Classes 3-4 ∙ Agent configurations locked; changes only via change control Medium Business (50-249 staff) / BLS Firm Size Classes 5-6 ∙ Controls preventing agent self-modification (immutable configs, restricted write access) ∙ Logging of any modification attempts Large Business (250-999 staff) / BLS Firm Size Classes 7-8 ∙ Policy enforcement preventing self-modification with logging and alerting ∙ Change control for agent updates Enterprise (> 1,000 staff) / BLS Firm Size Class 9 ∙ Enterprise AI agent lifecycle controls (immutable deployments, signed updates, self-modification detection and logging) 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 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 and 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 control, restrict and log AI agent self-modification. 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.
Purging AI Agent Data	Description Mechanisms exist to restrict purging of any persistent memory or long-term data used by AI agents. Possible Solutions & Considerations Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2 ∙ Restrict who can delete AI tool memory/history Small Business (10-49 staff) / BLS Firm Size Classes 3-4 ∙ Access controls on AI agent memory/data stores ∙ Deletion logged Medium Business (50-249 staff) / BLS Firm Size Classes 5-6 ∙ RBAC on persistent agent memory with approval for purges ∙ Retention and backup of agent data ∙ Audit logging Large Business (250-999 staff) / BLS Firm Size Classes 7-8 ∙ Governed agent memory stores with purge approval workflows and audit trails ∙ Legal hold support Enterprise (> 1,000 staff) / BLS Firm Size Class 9 ∙ Enterprise AI data governance for persistent memory (access control, retention, purge authorization, forensic preservation) 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 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 and 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 restrict purging of any persistent memory or long-term data used by AI agents. 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.
AI Agent Delegation and Chaining Control	Description Mechanisms exist to restrict agentic delegation, chaining and multi-agent communication to prevent unauthorized task escalation or emergent risks. Possible Solutions & Considerations Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2 ∙ Avoid AI tools that call other AI tools automatically; approve integrations individually Small Business (10-49 staff) / BLS Firm Size Classes 3-4 ∙ Documented approved agent-to-agent/tool integrations ∙ Delegation limits Medium Business (50-249 staff) / BLS Firm Size Classes 5-6 ∙ Orchestration policies restricting delegation depth and chaining ∙ Allow-listed agent communications ∙ Monitoring Large Business (250-999 staff) / BLS Firm Size Classes 7-8 ∙ Multi-agent governance framework with enforced delegation and chaining limits ∙ Agent communication validation (see AAT-36.14) Enterprise (> 1,000 staff) / BLS Firm Size Class 9 ∙ Enterprise multi-agent orchestration governance (policy-enforced delegation, chaining depth limits, emergent behavior monitoring) 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 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 and 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 restrict agentic delegation, chaining and multi-agent communication to prevent unauthorized task escalation or emergent risks. 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.
AI Agent Behavioral Drift Detection	Description Mechanisms exist to continuously monitor for behavioral drift or deviation from established AI agent baselines. Possible Solutions & Considerations Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2 ∙ Periodic spot checks of AI outputs for changes in behavior Small Business (10-49 staff) / BLS Firm Size Classes 3-4 ∙ Baseline of expected agent behavior; periodic review of outputs Medium Business (50-249 staff) / BLS Firm Size Classes 5-6 ∙ Behavioral baselines and drift monitoring for AI agents ∙ Alerting on deviations ∙ Evaluation datasets Large Business (250-999 staff) / BLS Firm Size Classes 7-8 ∙ AI observability platform with drift detection (e.g., Arize, Fiddler, WhyLabs) ∙ Automated evaluation pipelines Enterprise (> 1,000 staff) / BLS Firm Size Class 9 ∙ Enterprise AI observability and drift detection integrated with SOC ∙ Continuous evaluation and model monitoring 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 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 and 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 continuously monitor for behavioral drift or deviation from established AI agent baselines. 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.
AI Agent Action Authentication & Authorization	Description Mechanisms exist to ensure that all AI agent-initiated actions are properly mapped to authenticated user or system identities, with enforced authorization checks. Possible Solutions & Considerations Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2 ∙ AI actions performed under the user's own account permissions Small Business (10-49 staff) / BLS Firm Size Classes 3-4 ∙ AI agent actions mapped to authenticated users; least privilege Medium Business (50-249 staff) / BLS Firm Size Classes 5-6 ∙ On-behalf-of authorization for agent actions (OAuth delegated permissions) ∙ Action-level authorization checks ∙ Logging user-to-action mapping Large Business (250-999 staff) / BLS Firm Size Classes 7-8 ∙ Identity propagation and fine-grained authorization for agent actions ∙ Policy engine (e.g., OPA) for action authorization Enterprise (> 1,000 staff) / BLS Firm Size Class 9 ∙ Enterprise AI action authorization framework (identity propagation, policy-based authorization, non-repudiable action logs) 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 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 and 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 that all AI agent-initiated actions are properly mapped to authenticated user or system identities, with enforced authorization checks. 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.
AI Agent Transparency & Audit	Description Mechanisms exist to provide comprehensive audit trails of AI agent actions including: (1) Rationales; and (2) User/trigger mappings. Possible Solutions & Considerations Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2 ∙ Keep logs of AI tool usage and decisions where available Small Business (10-49 staff) / BLS Firm Size Classes 3-4 ∙ Audit logging of agent actions with user/trigger mapping Medium Business (50-249 staff) / BLS Firm Size Classes 5-6 ∙ Comprehensive agent audit trails (actions, rationales, triggers) retained centrally ∙ SIEM integration Large Business (250-999 staff) / BLS Firm Size Classes 7-8 ∙ AI observability/audit platform capturing action rationales and mappings ∙ Tamper-evident log storage Enterprise (> 1,000 staff) / BLS Firm Size Class 9 ∙ Enterprise AI audit and transparency program (immutable action logs, rationale capture, user/trigger mapping, regulatory reporting) 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 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 and 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 provide comprehensive audit trails of AI agent actions including: (1) Rationales; and (2) User/trigger mappings. 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.
AI Agent Explainability	Description Mechanisms exist to: (1) Provide human-understandable explanations for significant AI agent actions or decisions; and (2) Enable users to contest outcomes. Possible Solutions & Considerations Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2 ∙ Users can see why AI produced an output and request human review Small Business (10-49 staff) / BLS Firm Size Classes 3-4 ∙ Explanations provided for significant agent decisions ∙ Contest/appeal process Medium Business (50-249 staff) / BLS Firm Size Classes 5-6 ∙ Explainability requirements for significant decisions ∙ Human review and contest process ∙ Documentation Large Business (250-999 staff) / BLS Firm Size Classes 7-8 ∙ Explainability tooling (e.g., SHAP, LIME, model cards) ∙ Formal contest/appeal workflow ∙ Regulatory alignment (e.g., EU AI Act) Enterprise (> 1,000 staff) / BLS Firm Size Class 9 ∙ Enterprise AI explainability program with tooling, human review channels and regulatory compliance (EU AI Act, GDPR Art. 22) 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 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 and 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: (1) Provide human-understandable explanations for significant AI agent actions or decisions; and (2) Enable users to contest outcomes. 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.
AI Agent Ethics, Fairness & Bias Detection	Description Mechanisms exist to detect unfair, unethical or biased AI agent actions. Possible Solutions & Considerations Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2 ∙ Review AI outputs for obvious bias before use in decisions affecting people Small Business (10-49 staff) / BLS Firm Size Classes 3-4 ∙ Bias review for AI use cases affecting individuals Medium Business (50-249 staff) / BLS Firm Size Classes 5-6 ∙ Fairness testing and bias detection for agent decisions ∙ Ethics review process Large Business (250-999 staff) / BLS Firm Size Classes 7-8 ∙ AI fairness/bias monitoring tools (e.g., Fairlearn, AI Fairness 360) ∙ AI ethics committee ∙ Impact assessments Enterprise (> 1,000 staff) / BLS Firm Size Class 9 ∙ Enterprise responsible AI program (bias detection tooling, ethics governance, algorithmic impact assessments) 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 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 and 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 detect unfair, unethical or biased AI agent actions. 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.
AI Agent Output Integrity & Verification	Description Mechanisms exist to validate AI agent-generated outputs through the use of: (1) Content scanning; and (2) Output vetting through human review and approvals, where appropriate. Possible Solutions & Considerations Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2 ∙ Human review of AI outputs before use Small Business (10-49 staff) / BLS Firm Size Classes 3-4 ∙ Content scanning and human approval for AI outputs used externally Medium Business (50-249 staff) / BLS Firm Size Classes 5-6 ∙ Output validation (content scanning, policy checks) and human review for significant outputs Large Business (250-999 staff) / BLS Firm Size Classes 7-8 ∙ Automated output guardrails plus human-in-the-loop approval workflows ∙ Output integrity logging Enterprise (> 1,000 staff) / BLS Firm Size Class 9 ∙ Enterprise AI output assurance (guardrail platforms, content scanning, risk-based human review, provenance marking) 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 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 and 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 validate AI agent-generated outputs through the use of: (1) Content scanning; and (2) Output vetting through human approvals, where appropriate. 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.
AI Agent Resource Limiting	Description Automated mechanisms exist to enforce resource limits for Artificial Intelligence (AI) and Autonomous Technologies (AAT), including: (1) Energy consumption; (2) Processing capacity; and (3) Financial consumption (e.g., allocated budget). Possible Solutions & Considerations Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2 ∙ Cloud provider resource quotas and budget alerts ∙ API rate limiting for AI tool usage ∙ Basic AI tool usage monitoring Small Business (10-49 staff) / BLS Firm Size Classes 3-4 ∙ Cloud provider resource quotas and API rate limiting ∙ Cost alerting for AI workload spend Medium Business (50-249 staff) / BLS Firm Size Classes 5-6 ∙ Resource quotas and limits in AI deployment platforms ∙ Cloud cost management tools (e.g., AWS Cost Explorer, Azure Cost Management) ∙ API rate limiting and throttling Large Business (250-999 staff) / BLS Firm Size Classes 7-8 ∙ Enterprise resource governance for AI workloads ∙ Cloud FinOps practices ∙ Automated resource limit enforcement ∙ AI workload monitoring and alerting Enterprise (> 1,000 staff) / BLS Firm Size Class 9 ∙ Enterprise AI resource governance platform ∙ Automated resource limit enforcement with alerting ∙ AI workload orchestration (e.g., Kubernetes resource limits) ∙ FinOps program for AI infrastructure costs 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 and risk assessments). ▪ 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 and 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 enforce resource limits for Artificial Intelligence (AI) and Autonomous Technologies (AAT), including: (1) Energy consumption; (2) Processing capacity; and (3) Financial consumption (e.g., allocated budget). Level 4 Quantitatively Controlled Artificial Intelligence and Autonomous Technology (AAT) 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 Artificial Intelligence and Autonomous Technology (AAT) capabilities are "world class" efforts the leverage predictive analysis (e.g., machine learning and AI) to enable continuously improving capabilities. 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. ▪ Based on predictive analysis, process improvements are implemented according to “continuous improvement” practices that affect process changes. ▪ Stakeholders make time-sensitive decisions to support operational efficiency, which may include automated remediation actions via Artificial Intelligence (AI) or Machine Learning (ML) technologies.

1.1 Referenzen

1.2 Identifizierte Anforderungen

1.3 Zugehörige Regulierungen

2. Identifizierte Anforderungen

Anforderungen
Quelle	Anforderung

3. Zugehörige Regulierungen

Regulierungen
Quelle	Regulierung

Verknüpfte Vorgänge

Verknüpfungen
Verknüpfungstyp	Vorgang
is related to	Annual
is related to	relative Control Weighting = 05
is related to	Process
is related to	Protect
is related to	SCRM Focus Tier 2 OPERATIONAL
is related to	SCRM Focus Tier 3 TACTICAL
blocks	Loss of Accountability / Attribution
blocks	Excessive or Unauthorized Privilege
blocks	Unauthorized Access
blocks	Unauthorized Modification / Loss of System Integrity
blocks	System / Data Compromise (Technical Vector)
blocks	Reputational Harm / Loss of Stakeholder Trust
blocks	Regulatory / Legal / Contractual Financial Liability
blocks	System / Service Compromise
blocks	Unaddressed Security / Compliance Exposure
blocks	Unperformed / Unowned Control Responsibilities
blocks	Uncontrolled Internal Security / Privacy Exposure
blocks	Inability to Demonstrate Due Diligence / Due Care
blocks	AI Output / Decision Integrity Failure
blocks	Unauthorized / Harmful Autonomous Action
blocks	Sensitive Data / Compliance Exposure from Unsanctioned AI Use
blocks	Unintended or Unsafe Technology Behavior
blocks	AI Bias / Discriminatory Outcome
blocks	Loss of Confidentiality
blocks	Loss of Data Integrity
blocks	Privacy Harm / Unauthorized Processing
blocks	Injury / Loss of Life
blocks	Physical / Environmental Damage
blocks	Drought & Water Shortage
blocks	Earthquakes
blocks	Fire & Wildfires
blocks	Floods
blocks	Hurricanes & Tropical Storms
blocks	Landslides & Debris Flow
blocks	Pandemic (Disease) Outbreaks
blocks	Severe Weather
blocks	Space Weather
blocks	Thunderstorms & Lightning
blocks	Tornadoes
blocks	Tsunamis
blocks	Volcanoes
blocks	Winter Storms & Extreme Cold
blocks	Malicious Cyber Activity
blocks	Dysfunctional Management Practices
blocks	Human Error
blocks	Technical / Mechanical Failure
blocks	Statutory / Regulatory / Contractual Change
blocks	Artificial Intelligence & Autonomous Technologies (AAT) System Failure or Unintended Behavior
blocks	Fraud, Corruption and/or Intentional Criminal Conduct
blocks	Conflict of Interest (COI) / Undue Influence / Insider Misconduct
blocks	Product Defect / Design Failure
blocks	Workforce Shortage / Loss of Critical Skills / Labor Disruption
blocks	Adversarial Artificial Intelligence (AI) Attack
is blocked by	AAT-39 AI Agent Governance – Assessment Procedure

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