Kernel Level Security
Why Enterprise AI Security must live in the Kernel.
Modern enterprise infrastructure is deterministic. When a system calls an API, accesses a database, or executes a deployment, the outcome is binary: it either succeeds within defined parameters or it is a failure.
AI Agents, however, are probabilistic. They operate on statistical likelihoods and confidence scores. When you wire a probabilistic engine directly into deterministic infrastructure, you create a "Reasoning Gap"—a space where hallucinations, prompt injections, and logic errors become systemic risks.
The Sevorix Hypothesis: You cannot secure a probabilistic system using probabilistic tools. To protect deterministic infrastructure, the enforcement layer must exist at the Ground-Truth level: The Operating System Kernel.
Not all security layers are created equal. As you move down the stack, the bypass surface shrinks — until kernel enforcement, where scope is every syscall from a supervised process tree.
Prompt & system-instruction guardrails
The Risk: Relying on the agent to "behave". Attackers can use obfuscation or semantic jailbreaks to bypass these instructions entirely.
L7 gateways & proxies
The Risk: These are application-layer tools that can be bypassed if an agent modifies local environment variables or uses non-standard protocols to initiate out-of-band connections.
Kernel enforcement (eBPF + seccomp)
The Sevorix Standard:Targeted interception, by design. Sevorix registers the agent's process tree into a shared eBPF map at launch, and the kernel program watches only that tree. Inside it, no shell command, outbound request, or intercepted syscall reaches the OS without a policy verdict.
Sevorix leverages eBPF (Extended Berkeley Packet Filter) to insert high-performance, deterministic "Circuit Breakers" directly into the OS kernel.
Deterministic Blocking: We don't provide a "risk score." Our kernel hooks execute binary allow / deny logic. If a behavior violates the security policy, the kernel terminates the process or kills the connection before the first packet leaves the node.
Three-tier enforcement latency: In-kernel blocks resolve at Ring-0 with no round trip. L1 cache hits — a SHA-256 match against the local semantic cache — return in nanoseconds. Only a cache miss escalates to concurrent multi-model evaluation, inside a sub-50ms end-to-end budget.
Full Context Visibility: We see the ground truth: network destinations, file descriptors, and process execution. We don't have to guess what the agent is doing; we see exactly what the machine is doing.
As global regulations catch up to autonomous agents, "Best Effort" security is becoming a liability. Sevorix provides auditable, technical proof-of-control that supports modern frameworks.
EU AI Act Compliance: Supports the "technical redundancy and fail-safe plans" under Article 15 for high-risk AI deployments.
NIST AI Risk Management: Provides the "Measure and Manage" data required to prove system robustness in enterprise environments.