UK AI Cyber Security Code of Practice 3.4: Continuous monitoring and review of system infrastructure against risk appetite

What does 3.4 require?

Developers and system operators should keep monitoring and reviewing their system infrastructure in line with their risk appetite, recognising that AI systems retain a higher residual risk than conventional systems even after controls are applied.

Maintained by Gerard Blokdyk

Other controls in Secure design (Principles 1 to 4) – UK AI Cyber Security Code of Practice

1.1 AI security content in the cyber security training programme
1.2 Ongoing staff awareness of AI threats, with secure AI coding training for developers
2.1 Assess the need, the risks and the mitigations before building an AI system
2.2 Design for resilience against adversarial attack, unexpected input and failure
2.3 Create an audit trail for the AI system
2.4 AI-specific risk assessment and due diligence for external components
2.5 Match intended use to data sensitivity, and encourage staff to report AI security risks
2.6 Least-privilege, risk-assessed permissions for the AI system on other systems

Query this from an agent

The graph holds this control, the 0 it maps to, and the evidence behind each claim, over MCP and REST.

MCP endpoint All UK AI Cyber Security Code of Practice controls