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Security & Vulnerability Management

OEM Vulnerability Scanner

AI-powered vulnerability scanner monitoring multi-OEM sources with intelligent analysis, prioritization, mitigation planning, and automated notifications.

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Technologies Used

StreamlitPythonSQLitePlaywrightBeautifulSoupRequestsPlotlyGoogle Gemini 2.0 FlashSMTP

Created on January 20, 2025

Project Overview

OEM Vulnerability Scanner is a comprehensive AI‑assisted security monitoring platform that aggregates critical vulnerabilities from 10+ OEM and authoritative sources, performs automated enrichment, prioritization, mitigation planning, and delivers real-time notifications with role‑aware reporting.

Supported Sources

  • NVD (API)
  • CISA KEV Catalog
  • Microsoft Security Response Center
  • Cisco Security Advisories
  • Google Cloud Security Bulletins
  • Oracle Security Alerts
  • VMware Security Advisories
  • IBM Security Bulletins
  • Adobe Security Bulletins
  • HPE Security Bulletins

Core Features

🔍 Multi-Source Collection

  • Parallel ingestion of 10+ OEM feeds
  • Automated de-duplication (by CVE)
  • Incremental discovery with timestamp tracking

🤖 AI-Powered Analysis (Gemini 2.0 Flash)

  • Plain-language vulnerability summaries
  • Technical + business impact assessment
  • Exploitability / attack vector evaluation
  • Context-aware prioritization (1–10)
  • Automated mitigation & remediation strategy
  • Audience-specific (Engineer / Exec / Compliance) reports
  • Enhanced threat intelligence enrichment

⚙️ Smart Prioritization

  • Severity + exploit status + publication recency
  • Organizational context weighting (extensible)
  • Risk scoring rationale and remediation timeframe

📥 Data Management

  • SQLite storage with uniqueness on CVE
  • Timestamped discovery + notification flags
  • CSV export (global or filtered)

📊 Interactive Streamlit Dashboard

  • Real-time vulnerability feed
  • Severity, OEM, date-range filtering
  • Trend charts, distributions, heatmaps
  • AI enrichment panel
  • On-demand CSV export

📧 Email Notification System

  • Automated alerts for Critical / High
  • HTML formatted content + optional AI insights
  • Multiple managed recipients
  • CSV attachment option
  • Test notification workflow

🧠 Mitigation Planning

  • Immediate actions
  • Long-term remediation steps
  • Compensating controls
  • Resource estimation
  • Verification procedures

Technology Stack

  • Frontend: Streamlit
  • Backend: Python 3.8+
  • Data: SQLite
  • AI: Google Gemini 2.0 Flash
  • Scraping: Playwright (JS-required), BeautifulSoup, Requests
  • Visualization: Plotly
  • Email: SMTP (HTML)

Architecture Overview

  1. Source Registry (OEM_SOURCES) defines extraction strategy
  2. Scraper Orchestrator runs selected sources (Playwright where needed)
  3. Normalization layer maps raw fields → unified schema
  4. AI Enrichment pipeline (optional / cached)
  5. Persistence layer (SQLite) with de-duplication on CVE
  6. Notification dispatcher (severity + state aware)
  7. Streamlit UI queries + visualizes + exports
  8. CLI entry point for headless automation / cron