+Purging AI Agent Data

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.

1. Přehled

Název Standard

1.1 Odkazy

1.2 Identifikované požadavky

1.3 Související regulace

2. Identifikované požadavky

Požadavky
Zdroj Požadavek

3. Související regulace

Regulace
Zdroj Regulace

Propojené úkoly

Vazby
Typ vazby Úkol
is related to Annual
is related to relative Control Weighting = 05
is related to Technology
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 Loss, Theft or Damage of Assets
blocks Unauthorized Retention / Inability to Dispose of Data
blocks Business / Service Interruption
blocks Data Loss / Integrity Compromise
blocks Reduced Operational Productivity
blocks Regulatory / Legal / Contractual Financial Liability
blocks Inability to Demonstrate Due Diligence / Due Care
blocks Loss of Investigative / Evidentiary Capability
blocks Recovery Failure / Unacceptable Recovery Delay
blocks AI Output / Decision Integrity Failure
blocks AI Data Confidentiality / Integrity / Provenance Loss
blocks Unintended or Unsafe Technology Behavior
blocks Loss of Data Integrity
blocks Loss of Data / Service Availability
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 Artificial Intelligence & Autonomous Technologies (AAT) System Failure or Unintended Behavior
blocks Fraud, Corruption and/or Intentional Criminal Conduct
blocks Adversarial Artificial Intelligence (AI) Attack
is blocked by AAT-39.16 Purging AI Agent Data – Assessment Procedure
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