← Showcase / 03 // CYBERSECURITY CORE
STATUS // RUNNING // DEPLOYED AI-ASSISTED SPA

VigileAI
SOC Copilot Console

An advanced AI-assisted Security Operations Center copilot engineered as a single-page application. Handles IOC analysis, alert triage, threat hunting, dark web monitoring, CVE intelligence, and automated detection-rule generation — all in one unified interface.

ReactGenerative AISupabaseSecurity AnalyticsTypeScriptVercel
vigileai // private deployment
VigileAI SOC console screenshot
// THE PROBLEM

Alert noise is killing analyst response time

SOC analysts were drowning in thousands of alerts daily, manually pivoting between disconnected tools for IOC lookups, threat intel feeds, CVE databases, and log analysis — losing critical response time to tool-switching friction.

Detection rules were written manually from scratch, dark web monitoring was irregular, and there was no single pane of glass tying threat context together. High signal-to-noise ratio meant real threats were buried.

// THE SOLUTION

One console, every threat layer

Built a React SPA with a unified SOC console that aggregates IOC analysis, alert triage queues, and threat hunting into a single interface. The AI layer ingests raw alert data and provides enriched context — MITRE ATT&CK mapping, risk scoring, and suggested response actions — in real time.

Detection rule generation is automated: analysts describe the threat pattern in natural language, and the AI generates ready-to-deploy SIGMA rules. Dark web monitoring runs as a background job, surfacing credential leaks and data exposure automatically.

// ARCHITECTURE DECISIONS

Engineering choices that mattered.

01
// SPA ARCHITECTURE

Single-page over multi-page

A SOC console lives and breathes in-session. Analysts switch between modules constantly — an SPA eliminates page reloads entirely, keeping threat context and open investigations in memory throughout the session.

02
// SECURITY LAYER

Supabase RLS + encrypted storage

Row-level security policies ensure analysts only access data within their scope. Sensitive IOC data and API keys are stored encrypted — security tooling needs to be secure itself.

03
// AI CONTEXT

Threat-aware prompt engineering

The AI doesn't just answer generic security questions — it receives the live alert queue, IOC enrichment data, and session context before generating SIGMA rules or triage recommendations, making every output immediately actionable.

// STACK BREAKDOWN

Technology deployed.

FRONTEND
React + TypeScript

Component-based SPA with strict TypeScript for a secure, type-safe codebase across all security modules.

DATABASE + AUTH
Supabase (PostgreSQL + RLS)

Row-level security policies, encrypted storage, and real-time subscriptions for live alert queue updates.

AI ENGINE
Generative AI (context-aware)

Threat-aware prompt engineering with live alert context. SIGMA rule generation, MITRE ATT&CK mapping, triage scoring.

DEPLOYMENT
Vercel Edge Network

Zero-config deployments with environment-variable isolation for API keys and sensitive configuration.

INTELLIGENCE
Security Analytics Layer

IOC enrichment, CVE intelligence feeds, and dark web monitoring integrated into the unified console.

AUTOMATION
Rule Generation Engine

Natural language to SIGMA detection rules. Analysts describe the threat pattern, the engine writes the rule.

// OUTCOMES

What shipped.

0
MANUAL IOC LOOKUPS
Auto
RULE GENERATION
7+
SOC MODULES
Live
PRODUCTION STATUS
// PREVIOUS BLUEPRINT

FitTribe Performance Platform

Read Case Study  →
// YOUR BUILD, NEXT

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