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.
自学习EDR。云管理。零内核风险。
轻量级代理监控桌面和移动平台的行为遥测。版本化ONNX模型直接在端点上运行——生成风险评分、置信度等级和可解释分析。遏制受置信度门控和策略控制。
边缘优先推理
ONNX模型在端点本地运行。15毫秒以下的检测延迟。无云往返。三阶段回退确保零盲点。
零内核驱动
用户模式ETW和eBPF提供深层进程、网络和注册表可见性，无蓝屏风险或系统不稳定。无内核攻击面。
云管理SaaS
相同的代理、相同的ML引擎、相同的控制台服务每个客户。添加新租户只是一条数据库记录——而非基础设施项目。
可解释AI
每个决策包含复合风险评分、每个特征的贡献度分解、模型版本和置信度等级。无黑箱裁决。
多平台
适用于Windows、Linux、macOS、Android和iOS的原生代理。所有平台的检测逻辑一致。内存80MB以下，CPU 2%以下。
集体防御
当一个端点检测到新威胁时，整个舰队在几分钟内更新。每个端点都增强所有人的保护。
核心原则： 保护10个端点和保护10,000个端点使用相同的产品基础。每次模型更新都经过金丝雀验证。每次部署都经过治理。平台持续改进。
集中智能，分布执行
QuickSecure不仅仅是端点上的代理。其核心是一个云原生AI安全引擎，从全舰队遥测数据、威胁情报源和标记的决策结果中持续学习。每个端点贡献行为数据。中央引擎聚合、关联并产生可操作的情报，回流到舰队中的每个代理。
这创建了集体防御网络：当一个端点遇到新的威胁模式时，中央引擎评估它，几分钟内整个舰队就会更新新的入侵指标。参与的端点越多，每个人的检测能力就越强。
零内核攻击面
用户模式ETW和eBPF提供深层进程、网络和注册表可见性，无蓝屏风险或系统不稳定。无内核攻击面。
版本化模型注册表
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.
Transparent Per-Endpoint Pricing
Same product at every tier. Capability level and support SLA differ.
- Shadow + Supervised modes
- Basic SOC console view
- Explainable AI scoring
- Collective IoC sync
- 90-day event retention
- Email support (48h SLA)
- AI Security Assistant
- Shadow + Supervised modes
- Built-in SOC console
- Explainable AI scoring
- Collective IoC sync
- 90-day event retention
- Email support (24h SLA)
- JSON export + Webhooks
- AI Incident Explanation
- AI IOC Assessment
- Everything in Business
- Full autonomous mode
- Advanced policy engine
- Confidence-gated containment
- Central SIEM Hub
- 180-day event retention
- Priority support (8h SLA)
- Model version management
- Workspace AI Assistant
- Everything in Advanced
- Enterprise tenant isolation
- Tenant-dedicated ML models
- Multi-tenant SOC dashboard
- Direct SIEM export (Sentinel, Splunk, Syslog)
- Per-tenant rate limiting
- On-premise deployment option
- Custom retention & dedicated support
- AI Governance & Audit
- AI API Access
- Premium Provider Choice
Volume discounts available for 100+ endpoints. First-year pricing guaranteed for annual commitments.
Try the AI Security Engine
Ask a security question to see the same AI engine that powers incident explanation, IOC assessment, and workspace intelligence inside QuickSecure — running live right now.
🟢 Live demo — real AI inference against our self-hosted model with threat intelligence grounding. Click any example or type your own question.
Self-hosted AI inference — no data sent to third parties. Rate-limited public demo.
Unlock full AIYour 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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