FedRAMP AI Controls Mapping for the LLM Request Path

FedRAMP AI controls mapping should begin with one inference call, not a catalog export. An authenticated principal sends a prompt, a policy evaluates the destination and data, the model returns a response, and an audit record preserves the decision. Five NIST SP 800-53 families land directly on that path: Access Control, Audit and Accountability, System and Communications Protection, System and Information Integrity, and Configuration Management. NIST publishes the Rev. 5 catalog, while FedRAMP applies baselines and assessment requirements to cloud services. The mapping below gives engineers testable control behavior.

AC maps identity to model authorization

AC-2 governs account management, AC-3 covers access enforcement, and AC-6 applies least privilege. For an AI call, the enforcement point needs the verified human or workload identity behind the application credential. Policy can then restrict models, routes, actions, and data classes by role. The implementation test uses two identities with different permissions and confirms that one request proceeds while the other is denied. Evidence should name the principal, requested model, rule, and outcome. A shared provider key can remain a transport credential, but it cannot carry the full enterprise authorization decision by itself.

AU maps the call to a durable decision record

AU-2 identifies events for logging, AU-3 defines record content, AU-9 protects audit information, and AU-12 addresses generation. Treat inference requests, response evaluations, denials, and policy changes as defined events. Each record needs a unique ID, synchronized timestamp, source, identity, model destination, classification, policy version, and outcome. Protect the write path from the application making the call. On an assessor's laptop, a query for one employee and one Tuesday should return the corresponding decisions without stitching together browser, application, and provider logs by hand. The FedRAMP AI audit evidence guide provides a field-level version of this mapping.

SC maps to the protected request channel

The SC family addresses boundary protection, transmission confidentiality, and system separation. AI prompts often contain regulated material, so TLS protects the connection while route policy constrains the approved endpoint. Network controls establish permitted paths and segmentation. An AI enforcement layer adds content and identity context to the boundary decision for HTTP model traffic. Those controls complement each other. DeepInspect cannot replace network segmentation, provider authorization, or encryption management. It can enforce that a classified prompt goes only to an approved model route when the request traverses its boundary, then record the decision for assessment.

SI maps monitoring to AI-specific events

The SI family covers flaw remediation, malicious-code protection, monitoring, and alerts across the system. AI request monitoring should surface unexpected destinations, policy-engine failures, repeated denials, and prompt-injection indicators relevant to the configured rules. Model behavior remains probabilistic, so the preventive decision should come from deterministic policy where the organization has a fixed requirement. My view is that a daily chart of token volume has almost no security value unless an analyst can open the underlying identity and destination events. Monitoring has to lead to a named request, policy, and owner.

CM maps routes and policies to approved change

CM controls govern baselines, configuration settings, and changes. Model names, provider routes, permitted regions, role mappings, and data rules form part of the AI control configuration. Store policies as versioned artifacts, require approval for sensitive changes, and include the active version in every decision record. A model alias can silently point to a new deployment, so route resolution belongs in change review and continuous monitoring. The red pen moment comes when an assessor compares the approved policy version with the event record and finds they match. That is stronger than a screenshot of today's configuration.

The mapping needs test procedures

Each mapped control should include an implementation statement, evidence source, owner, frequency, and repeatable test. Test AC-3 by attempting an unauthorized model call. Inspect the generated fields for AU-3, then verify integrity protection and access permissions for AU-9. The SC procedure traces the actual destination and encryption state. A CM test deploys an approved policy change and confirms that new events carry the new version. This structure connects the control catalog with observed system behavior. It also prevents one gateway control from being stretched across responsibilities belonging to IAM, network, endpoint, or provider teams.

DeepInspect

DeepInspect covers a defined slice of this mapping at the HTTP AI request boundary. It accepts identity context, evaluates per-role and per-route rules, classifies request data, restricts model destinations, and can fail closed. Each enforcement decision creates a tamper-evident record with the evidence fields needed for AC and AU testing.

FedRAMP authorization still requires the full baseline, SSP, assessment, continuous monitoring, and controls outside AI traffic. DeepInspect supplies request-path enforcement and decision evidence, then exports those records into the organization's broader audit process. Book a demo today.