AI Security Fabric
A continuously learning autonomous containment engine with explainable decision logic, production-grade ML governance, versioned model distribution, and drift-monitored inference. Built for organizations that require verifiable, auditable autonomous security.
Production ML Lifecycle
Every model version is tracked, validated, and monitored — from training to production containment
Model Registry
Versioned, signed ONNX models with full lineage tracking and instant rollback capability.
- SHA-256 signed model artifacts
- Version lineage and parent tracking
- One-click model rollback
- Training metadata persistence
Canary Deployment
New model versions validated on endpoint subsets before fleet-wide promotion.
- Configurable traffic split
- FP rate gate for promotion
- Automatic rollback on exceedance
- Endpoint-level canary assignment
Drift Detection
Population Stability Index tracks feature distribution shift between training and production.
- PSI scoring per feature
- Confidence distribution monitoring
- Automatic retraining trigger
- Severity classification (None/Low/Moderate/Significant)
Fallback Chain
Three-stage inference pipeline ensures detection continuity under all conditions.
- ONNX edge model (primary)
- Random Forest (secondary)
- Rule-based heuristics (tertiary)
- Fallback stage annotation per decision
Ground Truth Labeling
TP/FP/FN/TN labeling system that feeds supervised model improvement.
- Admin-driven label assignment
- Feature vector persistence
- Confusion matrix dashboard
- Label-driven retrain triggers
Explainable Decisions
Every containment decision includes a risk score breakdown with factor-level explanation.
- Per-feature contribution analysis
- Independent signal source documentation
- Model version + policy threshold recorded
- Audit trail per decision
Progressive Trust — Earned, Not Assumed
Three operational modes allow organizations to adopt autonomy incrementally. Each mode builds on validated confidence. Advance only when the data supports it.
- Shadow Mode — Learning: Full inference pipeline active, zero containment. WouldContain vs ActuallyContain comparison. Drift baseline establishment.
- Supervised Mode — Human-in-the-Loop: Detections generate recommended actions. Admin reviews, approves, or dismisses. Every decision enriches the TP/FP labeling system.
- Full Autonomous — Self-Driving Security: Confidence-gated automatic containment. Policy-defined thresholds. Fallback chain. Full audit trail + rollback capability.
Trust Engineering
Verifiable safety mechanisms at every layer — every gate inspectable, every decision reversible
Model Signed & Verified
Every deployed model artifact is SHA-256 signed and verified before inference begins. Tampering detected at load time.
Autonomous Safety Gates
Policy-defined confidence thresholds, rate limits, and severity gates prevent runaway containment. Human escalation for critical decisions.
Allowlist Protection
Enterprise allowlists prevent false positives on approved software. Centrally managed, fleet-synchronized.
Emergency Kill Switch
Single-action kill switch disables all autonomous containment fleet-wide. Immediate effect via priority directives.
Architecture
From endpoint inference to cloud governance — observable at every layer
ENDPOINT LAYER (User-Mode Agent) ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ ┌──────────────────┐ │ ETW/eBPF │ │ Behavioral │ │ ONNX ML │ │ Containment │ │ Consumer │──│ Analyzer │──│ Engine │──│ Engine │ │ │ │ 150+ Checks │ │ Fallback: │ │ Policy-Driven │ │ │ │ │ │ ONNX→RF→Rule│ │ Audit Trail │ └──────────────┘ └──────────────┘ └──────────────┘ └──────────────────┘ No Kernel Hooks │ Feature Vectors Persisted │ Confidence-Gated Containment CLOUD GOVERNANCE (ML Command Center) ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ ┌──────────────────┐ │ Telemetry │ │ Model │ │ Drift │ │ ML Command │ │ Collector │──│ Registry │──│ Monitor │──│ Center │ │ Protobuf │ │ Versioned │ │ PSI Scoring │ │ Confusion Matrix│ │ TLS 1.3 │ │ Canary │ │ Retrain │ │ Decision Intel │ └──────────────┘ └──────────────┘ └──────────────┘ └──────────────────┘ Signed Model Distribution │ TP/FP/FN/TN Labeling │ Fleet Learning
Evaluate the AI Security Fabric
14-day pilot. Up to 10 endpoints. No credit card required. Manual approval — we review every application to ensure a quality experience.