The full picture.
Architecture, governance, and how it scales.
Every layer that didn't fit on the main page — behavioral detection pipeline, ML governance, multi-tenant isolation, operating modes, resilience, deployment options, and the technical FAQ.
Self-Learning EDR. Cloud-Managed. Zero Kernel Risk.
A lightweight agent monitors behavioral telemetry across desktop and mobile platforms. Versioned ONNX models run directly on the endpoint — producing risk scores, confidence levels, and explainable breakdowns. Containment is confidence-gated and policy-controlled.
Edge-First Inference
ONNX models run locally on the endpoint. Sub-15ms detection latency. No cloud round-trip for containment decisions. Three-stage fallback ensures zero blind spots.
Zero Kernel Drivers
User-mode ETW and eBPF provides deep process, network, and registry visibility without BSOD risk or system instability. No kernel attack surface.
Cloud-Managed SaaS
Same agent, same ML engine, same console for every customer. Adding a new tenant is a database record — not an infrastructure project.
Explainable AI
Every decision carries a composite risk score, per-feature contribution breakdown, model version, and confidence level. No black-box verdicts.
Multi-Platform
Native agents for Windows, Linux, macOS, Android, and iOS. Consistent detection logic across all platforms. Under 80MB memory, under 2% CPU.
Collective Defense
When one endpoint detects a new threat, the entire fleet is updated within minutes. Every endpoint strengthens protection for everyone.
Core principle: Protecting 10 endpoints and protecting 10,000 endpoints use the same product foundation. Every model update is canary-validated. Every deployment is governed. The platform improves continuously.
Centralized Intelligence, Distributed Enforcement
QuickSecure is not just an agent that runs on endpoints. At its center sits a cloud-native AI security engine that continuously learns from fleet-wide telemetry, threat intelligence feeds, and labeled decision outcomes. Every endpoint contributes behavioral data. The central engine aggregates, correlates, and produces actionable intelligence that flows back to every agent in the fleet.
This creates a collective defense network: when one endpoint encounters a new threat pattern, the central engine evaluates it, and within minutes the entire fleet is updated with new Indicators of Compromise. The more endpoints participate, the stronger the detection capability becomes for everyone.
Zero Kernel Attack Surface
User-mode ETW and eBPF provides deep process, network, and registry visibility without BSOD risk or system instability. No kernel attack surface.
Versioned Model Registry
Every ONNX model is versioned, signed, and tracked. Full lineage from training data to production deployment. Rollback to any previous version in seconds.
Explainable Decision Logic
Composite risk score with per-feature contribution breakdown. Model version, policy threshold, and confidence level recorded per decision. No black-box verdicts.
Drift Monitoring (PSI)
Population Stability Index tracks distribution shift between training and production features. Automatic retraining triggers when PSI exceeds configurable thresholds.
Canary Deployment
New model versions are validated on a subset of endpoints before fleet-wide promotion. Canary traffic percentage and rollback criteria are policy-defined.
Three-Stage Fallback
ONNX edge model → Random Forest → rule-based heuristics. If the primary model fails or confidence is insufficient, fallback stages engage automatically.
Embedded AI Intelligence — Not a Chatbot
The AI Security Engine is not a conversational assistant bolted onto a dashboard. It is embedded directly into security workflows — incident triage, IOC investigation, posture assessment, and operational guidance. Every AI output is grounded in your actual telemetry, structured for analyst consumption, and recorded in a tamper-evident audit log.
AI Incident Explanation
Root cause analysis, MITRE ATT&CK correlation, severity assessment, and remediation guidance — generated from structured incident data, not free-form prompts.
AI IOC Assessment
Threat intelligence correlation, confidence scoring, and contextual analysis for Indicators of Compromise — integrated directly into the IOC database workflow.
Workspace AI Assistant
Security posture analysis, threat summaries, and prioritized recommendations for your tenant — grounded in your own endpoint fleet data and threat history.
How It Works — From Agent to Control Plane
QuickSecure operates across six coordinated layers. Each layer has defined responsibilities, clear boundaries, and independent failure domains.
Endpoint Agent
Collects behavioral telemetry across 150+ forensic checkpoints on desktop and mobile. ONNX inference runs locally. Decisions evaluated against policy thresholds and operating mode constraints.
Detection Pipeline
Three-stage fallback: ONNX → Random Forest → heuristics. Every decision produces composite risk score, model confidence, and explainable feature contributions. Containment is never blind.
Control Plane & SIEM
Governs tenant isolation, policy assignment, and event routing. CentralOnly, DirectOnly, or Hybrid modes. Webhook, Syslog (CEF), and Microsoft Sentinel with transactional outbox delivery.
Central AI Engine
Aggregates fleet-wide intelligence. Model governance — registry, signing, canary deployment, drift monitoring (PSI), rollback. Distributes IoCs for collective defense.
Multi-Tenant by Design, Not by Retrofit
The default deployment model is cloud-managed SaaS. The architecture uses strict multi-tenant data partitioning, horizontal scaling of control plane components, centralized model governance, and shared infrastructure with isolated tenant contexts. There is zero per-customer code divergence.
🔒 Tenant Isolation
Each tenant gets dedicated data partitions, per-tenant ML model governance, per-tenant SIEM routing, and isolated policy contexts — all on shared infrastructure.
📈 Horizontal Scaling
Control plane components scale independently. Adding customers scales linearly — no re-architecture, no dedicated infrastructure per tenant unless explicitly requested.
🚫 Zero Custom Code
No per-customer forks, branches, or custom builds. Configuration-driven differentiation only. Consistent quality, faster updates, and lower operational cost.
Why this matters: Many security vendors position themselves as "cloud-native" while requiring per-customer deployment engineering. QuickSecure's tenant onboarding is a database record and a policy assignment — not an infrastructure project.
Progressive Trust — Earned, Not Assumed
The agent monitors over 150 forensic checkpoints covering persistence analysis (WMI, COM hijacking, registry, scheduled tasks, systemd/cron), behavioral detection (process hollowing, LSASS access, credential dumping, LOLBins, fileless malware), network intelligence (C2 beacons, DNS tunneling, AbuseIPDB/URLHaus/MalwareBazaar integration), and supply chain defense (git scanning, CI/CD integrity, typosquatting, secret exposure).
Organizations progress through three operating modes as confidence in detection accuracy grows:
Observe Only
Full inference pipeline runs, zero containment actions taken. Compares "would-contain" vs "actually-contain" to validate model accuracy before enabling autonomous behavior.
Human-in-the-Loop
Detections generate recommended actions. An admin reviews, approves, or dismisses each one. Every decision enriches the TP/FP labeling system for model retraining.
Confidence-Gated
When confidence exceeds policy threshold and risk criteria are met, containment executes automatically. Every action is logged, reversible, and feeds back into the learning loop.
Built to Survive Hostile Environments
An endpoint security product that crashes under load, loses events during outages, or allows tampering of its decision logs is worse than no product at all.
Self-Healing
Automatic recovery under degradation. The agent restores state without manual intervention when services are lost.
Backpressure
Adaptive circuit breakers prevent telemetry overload from freezing containment decisions.
Tamper-Evident
Cryptographic integrity on every event, decision, and config change. Unauthorized modifications are flagged.
ML Integrity
Model poisoning protection via signatures, drift monitoring, and canary validation.
No Vendor Lock-in
Deployable on-premise, hybrid, or multi-cloud. Architecturally independent from any single provider.
SaaS Default — Sovereign Optional
The primary deployment model is cloud-managed SaaS — fastest path to protection, first to receive updates. For regulated or sovereign environments, QuickSecure also operates in dedicated single-tenant infrastructure, on-premise data centers, sovereign cloud environments, and hybrid configurations.
The product core does not change across deployment models. The detection engine, inference pipeline, ML governance, and containment logic remain identical. Infrastructure ownership and data residency change. The security product does not.
Product vs. Service Layer
QuickSecure is the product. It includes its own SOC console — incident review, risk scoring, model confidence visualization, audit trails, policy management, and fleet intelligence — without external tooling.
Corxor MSSP is an optional operational layer. Customers may run QuickSecure independently, integrate with their internal SOC, engage Corxor as MSSP, or use it via third-party MSSP partners through multi-tenant white-label support. The platform architecture is independent from the service model.
Protection for everyone who can't afford to be the next headline
From a single laptop to a multi-tenant MSSP fleet, QuickSecure delivers intelligent, explainable and autonomous protection — without drowning your people in alerts.
Cloud & hosting providers
Multi-tenant by design. Protect customer workloads, prove isolation, and shut down crypto-mining abuse, web-shells and lateral movement before they hit your bill — or your reputation. One agent, every VM and container host.
MSSPs & professional security teams
QuickSecure is the autonomous tier under your SOC. Per-tenant policies, dedicated ML models and direct SIEM routing mean it triages and contains at machine speed — so your analysts spend their hours on the incidents that actually need a human.
Energy & critical infrastructure
Sub-15ms on-device response, zero kernel drivers, and detection that keeps working when the cloud doesn't. Built for environments where downtime is not an option and a cloud dependency is a liability.
SMBs & professionals
Enterprise-grade detection without an enterprise SOC. Autonomous mode does the work a security team would — explainable, governed and affordable — so a 10-person company gets the same machine-speed defense as a Fortune 500.
Individuals & families — identity protection
Most identity theft starts on the endpoint: infostealers harvesting saved passwords, session-cookie theft, and credential-dumping malware. QuickSecure detects and contains those at the source — and explains, in plain language, what it stopped and why.
Enterprises
Strict tenant isolation, tenant-dedicated models, governed AI with a full decision audit trail, an on-premise option, and direct export to Sentinel, Splunk and Syslog/CEF. Autonomous defense that satisfies your auditors, not just your firewall.
We make your EDR and SIEM stronger — we don't replace them
QuickSecure isn't another console for your team to babysit. It's the autonomous response layer that acts in the milliseconds before a human — or another tool — can. Even mature security stacks run it as their machine-speed first responder.
Feeds your SIEM, doesn't fight it
Every detection and autonomous action streams to Sentinel, Splunk, Syslog/CEF or a webhook — fully explained, with model version, confidence and MITRE mapping. Better signal in, fewer false positives to chase.
The autonomous layer most EDRs lack
Confidence-gated containment kills the process, isolates the host and quarantines the file at machine speed — then writes a reviewable record. Detection alone isn't response; QuickSecure closes the loop.
Collective defense across the fleet
When one endpoint sees a threat, every other endpoint is inoculated instantly via Bloom-filter IOC distribution. Your whole estate gets smarter the moment any single device does.
What we've shipped recently
QuickSecure advances on the path from Detection → Response → Autonomy. A few of the capabilities that landed in the last release cycle:
Watchdog + service-respawn keep protection alive across reboot, sleep/resume and power changes — the agent recovers itself, on battery or AC.
Thousands of curated behavioral & file/memory rules, synced from the cloud, matching malware families and attacker behavior on-device — no signatures-only blind spots.
Response is gated on model confidence and policy, so the agent acts decisively on real threats and stays calm on the rest.
Versioned model registry, canary rollout, drift monitoring and automatic rollback — production ML governance, with every decision auditable.
Transparent Per-Endpoint Pricing
Same product at every tier. Capability level and support SLA differ.
- Dashboard, Scan & System Configuration
- Threat Intelligence (summary)
- Shadow + Supervised modes
- Explainable AI scoring
- Collective IoC sync
- 90-day event retention
- Email support (48h SLA)
- AI Security Assistant
- Everything in Standard
- Full Threat Intelligence feed
- Detection Sources & Network Monitor
- Dependency Audit (supply chain)
- Built-in SOC console
- SIEM routing — JSON export + Webhooks
- Priority support (24h SLA)
- AI Incident Explanation + IOC Assessment
- Autonomous mode & Email Security — add-ons
- Everything in Business
- Full autonomous mode + confidence-gated containment
- API access (API Activity module)
- Enterprise tenant isolation + dedicated ML models
- Multi-tenant SOC dashboard
- Direct SIEM export (Sentinel, Splunk, Syslog)
- On-premise deployment + custom retention
- Per-tenant rate limiting & dedicated support
- AI Governance & Audit
- Premium Provider Choice
Volume discounts available for 100+ endpoints. First-year pricing guaranteed for annual commitments.
Your AI, Your Rules
QuickSecure's AI Security Engine is governed, audited, and tenant-aware. You control the inference path — self-hosted for maximum privacy, or premium providers for enhanced reasoning. No lock-in.
Self-Hosted Default
All AI inference runs on self-hosted infrastructure by default. No data leaves your environment. Zero third-party API calls. Full data sovereignty from day one.
Premium Provider Option
Enterprise customers can optionally enable premium AI providers for enhanced reasoning quality. Provider routing is per-tenant, policy-controlled, and fully audited.
Governed & Auditable
Every AI interaction — regardless of provider — is logged in a tamper-evident audit trail. Model selection, token usage, response quality, and provider fallback events are all recorded.
Privacy-First Path
Self-hosted Qwen/Mistral models via Ollama. No external API calls. Ideal for regulated industries, sovereign environments, and maximum data privacy.
Premium Quality Path
Enterprise opt-in to premium providers (Anthropic Claude, etc.) for complex incident analysis and advanced reasoning. Routed per-tenant with automatic fallback to self-hosted if unavailable.
Questions from CTOs, Architects & SOC Leaders
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