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ERD · CYBERSECURITY PLATFORM

Cybersecurity Platform Database Schema (ERD) Examples

Database schemas are the backbone of cybersecurity platforms, organizing data on vulnerabilities, threats, events, and assets. This collection showcases ER diagrams for common cybersecurity scenarios—from managing vulnerabilities to correlating security events—helping architects, developers, and security engineers design robust data models.

4 EXAMPLES· UPDATED 2026-07-31
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CYBERSECURITY

Cybersecurity Platform ERD

DATABASE

SIEM Event Correlation Database Schema

CYBERSECURITY

Threat Intelligence Platform Database Schema

CYBERSECURITY

Vulnerability Management Database

ABOUT

About these examples.

Whether you're building a SIEM system, a threat intelligence platform, or a vulnerability management database, these examples provide a starting point. Use the generator below to customize and create your own schema diagrams.

HOW TO

Make one yourself.

  1. 1

    Identify key entities

    Determine the main objects in your cybersecurity platform, such as Assets, Vulnerabilities, Threats, Incidents, Alerts, and Users.

  2. 2

    Define relationships

    Map how entities relate—for example, an Asset can have many Vulnerabilities, and an Incident may originate from a Threat.

  3. 3

    Add attributes and keys

    Specify fields for each entity (e.g., severity, detection date, CVSS score) and define primary/foreign keys to enforce integrity.

  4. 4

    Refine and export

    Use the generator to fine-tune your diagram, then export as an image or embed in documentation for your team.

FAQ

Frequently asked questions

What entities are commonly included in a cybersecurity platform database schema?01
Typical entities include Assets (devices, applications), Vulnerabilities (CVEs, weaknesses), Threats (attack patterns), Incidents (security events), Alerts (detections), and Users (analysts, admins). Additional entities may cover remediation tasks, scanners, or integration logs.
How do I model relationships between vulnerabilities and assets?02
Use a many-to-many relationship via a join table (e.g., AssetVulnerability) that includes context like discovery date, severity override, and mitigation status. This allows each asset to have multiple vulnerabilities and each vulnerability to affect multiple assets.
Should I normalize my cybersecurity database schema?03
Normalization is recommended to maintain data integrity and avoid redundancy, especially for master data (assets, vulnerabilities). However, for high-velocity event data (like SIEM logs), a partially denormalized structure or a NoSQL approach may be more performant.
How to handle schema changes for evolving threat intelligence feeds?04
Design for flexibility: use an entity-attribute-value (EAV) pattern for dynamic properties, store raw feed data in a JSON column, or maintain a separate 'custom attributes' table. Version your schema and plan regular reviews to align with new data sources.
Can I use the generated ERD for documentation?05
Absolutely. The generator produces clear, editable diagrams that you can export as PNG, SVG, or PDF. Embed them in architecture documents, security playbooks, or onboarding guides to align your team on the data model.
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