A framework for securing what AI systems can know, remember, and reason about.
Author: Quinton Stackfield
Organization: Atom Labs
License: MIT
Purpose:
Define a cognitive-layer security model that governs information flow, memory, and reasoning boundaries within autonomous AI systems.
Least-Context Access Control (LCAC) extends the principles of Zero Trust into the cognitive layer.
It is designed to secure reasoning itself, governing what an AI system can know, remember, or transfer across contexts.
LCAC establishes the foundation for the emerging field of Cognitive Security, enabling controlled reasoning and bounded autonomy in self-governing AI systems.
Where Zero Trust governs identity and action, LCAC governs cognition and inference.
As AI systems move from reactive models to autonomous reasoning agents, the attack surface has shifted.
Compromise no longer occurs only through identity or network intrusion, but through contextual contamination. Where an agent carries or infers knowledge across domains in unintended ways.
LCAC addresses this by enforcing reasoning isolation, ensuring every inference occurs within a bounded context of trust.
| Principle | Description |
|---|---|
| Cognitive Least Privilege | Limit what an AI agent can know or recall based on its contextual authorization. |
| Reasoning Isolation | Prevent inference drift by isolating reasoning chains within defined trust zones. |
| Cognitive Integrity | Guarantee that inferences are traceable, verifiable, and free from unauthorized contextual blending. |
| Runtime Governance | Embed ethical alignment, compliance, and decision transparency directly into system logic. |
| Contextual Trust Anchors | Replace static permissions with dynamic, evidence-based reasoning limits. |
LCAC introduces a Cognitive Control Plane above traditional Model and Data Control Planes.
This layer mediates the flow of context, reasoning, and knowledge between AI agents, ensuring cognitive operations remain within authorized boundaries.
- Data Plane: Manages storage, retrieval, and access to factual data.
- Model Plane: Manages algorithmic inference, policy, and functional execution.
- Cognitive Plane (LCAC): Governs reasoning, contextual recall, and information blending between agents.
Each reasoning event is treated as a bounded transaction.
LCAC verifies cognitive integrity before and after inference, ensuring no cross-context contamination or reasoning drift occurs.
| Function | Description |
|---|---|
| Scope Control | Applies contextual access limits to memory and reasoning layers. |
| Inference Isolation | Each reasoning chain executes within its own trust boundary. |
| Auditability | All inference events are recorded with provenance and reasoning traceability. |
| Dynamic Revocation | Reasoning sessions can be terminated or redacted when trust thresholds are exceeded. |
| Trust Metric | Each agent maintains a Cognitive Trust Score based on reasoning alignment and policy adherence. |
LCAC complements but does not replace Zero Trust.
While Zero Trust secures action and access, LCAC secures knowledge and reasoning.
It extends naturally into:
- Cognitive Security: Defining reasoning as a protected surface.
- AI Governance: Providing auditable, runtime enforcement of ethical constraints.
- Agent Autonomy: Enabling self-governing reasoning processes under verifiable constraints.
The next phase of research expands LCAC into the Cognitive Security Stack, integrating:
- Policy-based reasoning isolation for distributed agent systems.
- Reinforcement mechanisms for ethical runtime verification.
- Secure multi-agent collaboration models governed by LCAC principles.
atomlabs-lcac-framework/
├── README.md
├── LICENSE
└── docs/
├── lcac_principles.md
├── lcac_architecture.md
├── lcac_policy_examples.md
├── lcac_use_cases.md
└── lcac_metrics.md
- LinkedIn White Paper: From Zero Trust to Cognitive Trust
- Medium Article: Beyond Zero Trust - Introducing LCAC
The LCAC framework is operational within the Vanta Capital Intelligence Operating System, where it secures cognition across autonomous trading, governance, and decision-making agents.
Vanta implements LCAC as part of its Cognitive Security Stack, enabling bounded reasoning, cross-agent isolation, and verifiable trust telemetry in real-world conditions.
For the full architecture, implementation details, and live documentation of LCAC in production, visit:
Vanta Capital Intelligence OS