Reskill · NIS
Network & Infrastructure Security
An agent reached a service across a segment boundary, using a tool it found at runtime.
Your segmentation assumed it knew what talks to what. Autonomous traffic breaks that assumption.
Start with these skills
- Hold the physical-security floor under your AI
- Verify off-site disposal actually destroys data
- Control what leaves the secure site
- Verify the provider's secure-area discipline
- Verify secure media transport
The rung you have to reach
Infrastructure Security and Resilience
Security and resilience of the hosting environment for AI workloads, including compute (training clusters, inference servers), network isolation, and cloud/datacenter infrastructure. Focuses on preventing infrastructure-level compromise and outages of AI systems.
L1 · Initial
AI workloads run on general-purpose infrastructure with default security settings. No dedicated or isolated environments for AI training or serving. Network segmentation between AI and other workloads is absent. Hosting infrastructure for AI not differentiated in vulnerability management or monitoring.
L2 · Repeatable
Basic separation between AI development, training, and production environments (e.g., separate accounts/subscriptions or network segments). AI hosting infrastructure included in standard vulnerability management. Initial security configurations documented for AI compute and serving environments but inconsistently applied.
L3 · Defined
Standardized AI infrastructure architecture with documented security baselines. Training and inference environments isolated with defined network boundaries. AI workloads provisioned using Infrastructure-as-Code with security configurations. Hosting infrastructure integrated into CSPM/CNAPP coverage. Hardening and resilience standards applied to AI compute resources.
L4 · Capable
AI infrastructure initial use of zero trust architectures. Model and app serving workloads implement runtime security monitoring and enforcement. Confidential computing evaluated for high-sensitivity training and inference workloads. Deployments managed using IaC with security checks in the pipeline. Resilience includes system prompts, agent configurations, and other AI-specific components.
L5 · Efficient
Zero trust architecture consistently enforced across AI infrastructure. Immutable infrastructure patterns for AI hosting where feasible. Confidential computing deployed for high-sensitivity workloads. AI infrastructure security continuously validated and adapted as new attack vectors emerge. Infrastructure changes automated with security gates.
our model · calibrated to SAE J3016
Your syllabus
The plays that climb the rung.
The curriculum for this function is still forming. Baseline it below, and the fitted plays follow.
Autonomy must not outrun maturity. The gate holds each rung until its controls are evidenced. The gate framework: eight gates, three lanes →