Classification-aware workflow
Also called: classification-aware agent controls, clearance-aware AI workflow
An agent workflow that treats data classification as an enforced input to every access and action decision, not as a label.
What classification-aware workflow means.
A classification-aware workflow makes the classification level of data a first-class attribute in the authorization decision, so an agent's access is constrained by clearance and need-to-know on every read and every action. It extends to outputs: material derived from classified inputs inherits the appropriate handling, so a summary cannot silently become less protected than its sources. The distinction from ordinary access control is that classification is enforced at the policy decision point rather than recorded as metadata and trusted to downstream behavior.
Why it matters.
Aggregation is the specific risk. Individually unremarkable facts can combine into something that warrants protection, and an agent that reads widely and summarizes is a very efficient aggregator. Enforcing classification per action, and propagating it to derived output, is what keeps an agent from producing a document whose sensitivity nobody assessed.
How it works in practice.
Classification is an authorization attribute
The policy engine evaluates the resource's classification against the agent's operating clearance for each access, alongside role and tenant.
Derived output inherits handling
Output produced from classified inputs carries handling requirements forward rather than defaulting to the workflow's own level.
Identity is bound to real credentials
Clearance has to attach to a verified identity, which in defense environments means CAC or PIV rather than an application-local account.
The record carries the decision
Audit entries include the classification context of each action, which is what an accreditation reviewer needs to see.
What people get wrong.
That tagging data with a classification is the same as enforcing it. A label the execution path does not consult is documentation. Enforcement means the policy decision point can deny an action on classification grounds and records that it did.
Common questions.
What classification levels does Trunnion support?
The control plane supports classification-aware workflows up to TS/SCI, with CAC and PIV identity traceability for DoD environments. The accreditation posture of any specific deployment is determined by that environment's authorizing body, not by the platform.
How does this differ from ordinary access control?
Ordinary access control asks whether this identity may reach this resource. Classification-aware control additionally asks whether this clearance permits this material, and applies the answer to derived output as well as direct reads.
Does Trunnion hold an ATO?
Trunnion is engineered to align with NIST SP 800-53 control families and is designed to be deployable within accredited environments. Authority to Operate is granted by an authorizing official for a specific system in a specific environment; Trunnion does not claim one on a customer's behalf.
Standards referenced.
Trunnion is engineered to align with these control families. Alignment by design is not a claim of current certification or authorization.
Read next.
- Air-gapped AI deploymentRunning an AI system inside a network with no physical or logical connection to external networks, including no model API calls.
- ABAC for AI agentsAccess control that evaluates attributes of the agent, the resource, and the context on every action, instead of granting a fixed role up front.
- Agent governanceThe control layer that decides what an AI agent may do, who approves consequential actions, and how every step is proven afterward.
Get started
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Governance, approval, and provable audit built into the control plane, from cloud to air-gap. Request a demo against a workflow you actually run.