QuickSecure
Autonomous Endpoint Detection & Containment

The Product, in Plain Terms

QuickSecure is a self-learning endpoint detection and response (EDR) product. A lightweight agent runs on protected systems — Windows, Linux, macOS, Android, and iOS — and monitors behavioral telemetry, persistence mechanisms, network activity, and file-system operations. It does this without installing kernel drivers, which eliminates the risk of system instability or BSOD events caused by the security agent itself.

When the agent detects suspicious activity, it evaluates the threat using a versioned ONNX machine learning model running directly on the endpoint. The model produces a composite risk score, a confidence level, and an explainable breakdown of which signals contributed to the classification. Based on these outputs, the operating mode, and the configured policy thresholds, the agent either logs the event, presents it for human review, or contains the threat autonomously.

The platform is delivered as a cloud-managed SaaS product. Every customer receives the same agent, the same ML engine, and the same cloud console. Configuration is handled through standardized policy settings, not custom code. Adding a new customer requires a new tenant record — not a new deployment, not a custom build, not an engineering project.

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 Layer (Agent)

A lightweight agent runs on protected systems across desktop (Windows, Linux, macOS) and mobile (Android, iOS) platforms. It collects behavioral telemetry, persistence indicators, network signals, and other high-signal forensic checkpoints — over 150 data points per evaluation cycle. Inference is performed locally using versioned ONNX models. Decisions are evaluated against policy thresholds and operating mode constraints before any containment action is taken.

Detection & Inference Pipeline

Each event passes through a structured, safety-first decision pipeline. The primary path uses the ONNX edge model. If confidence falls below threshold or model validation fails, a fallback Random Forest engages. If that also yields insufficient confidence, rule-based heuristics provide a deterministic final safeguard. Every decision produces a composite risk score, model confidence, explainable feature contributions, and recorded model version and policy context. Containment is never blind. It is policy-controlled and confidence-gated.

Cloud Control Plane & SIEM Routing

The control plane governs tenant isolation, policy assignment, operating modes (Shadow, Supervised, Autonomous), and event routing. Three routing modes are supported: CentralOnly (Corxor Central), DirectOnly (customer SIEM), and Hybrid (dual delivery). The routing engine uses a transactional outbox pattern with exponential backoff, dead-letter queues, per-tenant rate limiting, and fault isolation. Webhook, Syslog (CEF), and Microsoft Sentinel are supported.

Central AI Security Engine

The centralized AI engine aggregates threat intelligence from the entire endpoint fleet. It manages model governance — registry, signing, canary deployment, drift monitoring (PSI), and rollback. It processes labeled decision outcomes (TP/FP/FN/TN) to continuously improve model accuracy. It distributes Indicators of Compromise across all tenants, creating a collective defense posture that strengthens with every new endpoint in the network.

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:

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.

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.

Questions from CTOs, Architects & SOC Leaders