Code can’t contain code. Give AI a boundary it can’t argue with.
As AI agents gain access to sensitive data and networks, containment can’t depend on application-layer controls alone. Explore how hardware-enforced boundaries and cross domain controls govern what moves into and out of AI environments, placing transfer enforcement outside the agent’s control.
Software controls were built for software. AI agents are different.
AI agents are already getting around application-layer controls, and code can’t reliably contain code. The guardrails and filters wrapped around an agent are themselves software. At the same time, agents are being given more autonomy, and humans are leaving the tactical loop. Relying on software alone to hold them puts the mission at risk.
The Case for AI ContainmentAgents are already getting around software controls.
When an agent pursues an objective through a path its developers never anticipated, application-layer protections may not be enough. Explore why containment must govern how AI interacts with surrounding systems, not just how it behaves.
Read the Containment AnalysisGuardrails should not be the final boundary.
Guardrails and filters help govern agent behavior, but containment needs an independent layer of enforcement. Explore Owl’s perspective on placing hardware-enforced transfer controls outside the agent’s compute environment.
Read the Expert PerspectiveAutonomy is growing while humans leave the loop.
As agents act faster and humans step back from tactical decisions, oversight must shift toward setting boundaries, defining rules, and validating outcomes. Explore how containment connects autonomous operations with human control and accountability.
Read the CyberScoop CommentaryThe Case for AI Containment
Containment at Every Layer
Owl's Approach to AI Containment
Hardware-Enforced Boundaries
Hardware outside the compute stack places transfer enforcement beyond the agent’s administrative control. Rather than relying on software guardrails alone, independent boundaries govern what data can enter and leave the environment. The agent operates within those limits without having authority to reconfigure the controls that enforce them or disable enforcement.
Deterministic Governance
Known-good policy provides a consistent basis for governing data movement. Exchanges are verified against predefined rules rather than relying solely on detecting suspicious behavior. This makes transfer decisions predictable, repeatable, and defensible, helping security teams define permitted exchanges and maintain consistent enforcement as AI agents gain greater access and autonomy.
Human-Readable Exchanges
Human-readable transfer records give security teams visibility outside the agent’s environment. Logging exchanges independently separates the audit trail from the system it describes, supporting review and accountability. People can examine data movement, assess compliance with defined policies, and investigate activity without depending solely on the agent’s own account of events.
From Principles to Enforcement
Control data movement, enforce defined policies, and support independent oversight with boundaries outside the agent’s environment. Owl puts these principles into practice through protocol, network, and physical controls that govern permitted exchanges, manage traffic entering and leaving AI environments, and enforce one-way data movement where required.
Layer 1: Protocol
Machine-to-machine traffic is over half of internet traffic, so humans can't review it in the loop. Our Cross Domain Solutions strip traffic to raw data and check it against known-good policy, including AI protocols like MCP. Everything is logged outside the agent.
Layer 2: Network
Assume an AI in a sandbox can reach everything on that network. Our CDS control what enters and leaves the enclave, and an independent SOC sees what the agent can't alter. Wrap your existing sandbox, don't replace it.
Layer 3: Physical
Data diodes give you a hard guarantee: one-way flow, no return path, no callbacks, no pivoting. Fresh data goes in, nothing comes back out. The nuclear industry relies on this model.
Owl’s Solution Portfolio
One Portfolio, Every Boundary
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Policy-Enforced Transfer Across Domains: transfer real-time data, voice, and video across classification boundaries. Owl’s RTB-compliant cross domain solutions support point-to-point and multi-domain environments, helping teams share mission information without relying on manual transfer workflows. Learn more.
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Hardware-enforced, one-way data flow: Edge agents and sensors can report data without opening a path back into command and control. Protocol Filtering Diodes add FPGA-based filtering that blocks anything non-compliant by design. Learn more.
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