AAT-39.12: AI Agent Prompt Injection Defense
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.
Renumbered: Formerly AAT-29.12 in SCF 2025.4.
Control Question: Does the organization 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?
APAC (1)
| Framework | Mapping Values |
|---|---|
| APAC Australia ISM June 2026 | ISM-1924 |
Capability Maturity Model
Level 0 — Not Performed
Practices are non-existent, based on the inability to demonstrate an implemented and operational capability. A reasonable person would conclude the control is not being performed.
Level 1 — Performed Informally
SCR-CMM Level 1 criteria definitions are not available for this control: ▪ A reasonable person would conclude this control requires a structured process. ▪ At this level of maturity, the "ad hoc" nature of performing a capability informally would indicate the intent of the control is not met due to a lack of consistency and formality.
Level 2 — Planned & Tracked
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.
Assessment Objectives
- AAT-39.12_A01 prompt injection / input attacks that seek to manipulate AI agent instructions, bypass controls or result in unauthorized actions can be detected.
- AAT-39.12_A02 means to prevent or mitigate prompt injection / input attacks that seek to manipulate AI agent instructions, bypass controls or result in unauthorized actions are implemented.
Technology Recommendations
Micro/Small
- Use AI services with built-in prompt injection protections; validate outputs before acting
Small
- Input/output filtering for AI applications
- Separation of instructions from untrusted content
Medium
- Prompt injection defenses (input sanitization, instruction hierarchy, output validation)
- OWASP LLM Top 10 alignment
- Red team testing
Large
- AI firewall/guardrails platform (e.g., Lakera, Prompt Security, Azure AI Content Safety)
- Continuous prompt injection testing
Enterprise
- Enterprise AI guardrail platform with prompt injection detection and response
- Adversarial testing program
- SIEM integration for AI attacks