SOC Alert Triage Cursor Rules Template

Overview

This Cursor rules template documents how to configure Cursor AI to help build a SOC alert triage platform. It covers the Python FastAPI PostgreSQL stack for log ingestion, alert grouping, AI summaries, and analyst workflows. The guidelines are actionable so you can paste the included .cursorrules block into your project root.

When to Use These Cursor Rules

• Starting a SOC alert triage project and establishing a repeatable Cursor AI workflow.
• Setting up log ingestion pipelines and alert correlation with AI-assisted summaries for analysts.
• Enforcing architecture constraints to prevent drift from production-grade SOC tooling.
• Standardizing authentication, data handling, and testing across services.

Copyable .cursorrules Configuration

Paste this block in the project root as .cursorrules. It includes Framework Role & Context, Code Style, Architecture & Directory Rules, Authentication & Security, Database/ORM patterns, Testing/Linting, and Prohibited Actions.

# Cursor rules for SOC alert triage platform
FrameWork: Python
Runtime: Python 3.11
Stack: FastAPI, PostgreSQL, SQLAlchemy, Alembic, Redis, OpenAI API
Context: You are an AI coding assistant guiding the development of a SOC alert triage platform with log ingestion, alert grouping, AI summaries and analyst workflows using Cursor AI.
Role: System
CodeStyle: PEP8; Black formatting; isort; mypy
ArchitectureDirectory: src/api, src/ingestion, src/alerts, src/ai, src/db; tests/
AuthSecurity: JWT/OAuth2; HTTPS; strict secret handling; token rotation
DatabaseORM: PostgreSQL; ORM: SQLAlchemy; migrations: Alembic
TestingLint: Pytest; Black; isort; mypy; flake8; pre-commit hooks
Prohibited: Do not expose secrets; Do not bypass auth; Do not run shell commands in AI outputs; Do not write/assume real user data; Do not emit hardcoded passwords

Recommended Project Structure

SOC_ALERT_TRIAGE/
  src/
    api/
      main.py
    ingestion/
    alerts/
    ai/
    db/
      models/
      migrations/
  tests/
  config/

Core Engineering Principles

• Clear module boundaries: ingestion, grouping, AI, analyst workflows.
• Explicit typing and linting enforced by CI.
• Idempotent ingestion and deterministic alert grouping.
• Data security, least privilege, and secrets management by design.
• Observability through structured logs and metrics.

Code Construction Rules

• Use SQLAlchemy models with explicit relationships and migrations.
• Separate business logic from API routes; keep services small and testable.
• All external calls go through a single adapter layer; mock in tests.
• AI calls are rate-limited and batched; avoid leaking API keys in logs.
• Include type hints and docstrings; enforce mypy in CI.

Security and Production Rules

• JWT/OAuth2 authentication for all endpoints; TLS in production.
• Secrets managed by vault; environment-specific configs; no hardcoded tokens.
• Audit logs for access and alert decisions; tamper-evident logging where possible.
• Input validation, output escaping, and defensive coding against log spoofing.

Testing Checklist

• Unit tests for parsing and normalization of logs.
• Integration tests for ingestion and alert grouping across services.
• End-to-end tests for analyst workflows with AI summaries.
• CI checks for linting, typing, and security scanning.

Common Mistakes to Avoid

• Forgetting to isolate API keys in test environments.
• Overloading AI with raw logs; summarize and redact sensitive fields.
• Skipping migrations or hardcoding database connections.
• Ignoring observability; missing traces for alert decisions.

Related Cursor rules templates

Explore adjacent Cursor rules templates for similar stacks, workflows, and production constraints.

• Cursor Rules Template for AI Bookkeeping with Python FastAPI & PostgreSQL
• Cursor Rules Template: FastAPI + SQLAlchemy for AI Legal Research Assistant
• Cursor Rules Template: NLP Chart, SQL & Reports for AI Data Analyst App
• Cursor Rules Template: Python FastAPI Knowledge Base

FAQ

What does this Cursor rules template cover?

This Cursor rules template describes a SOC alert triage platform with log ingestion, alert grouping, AI summaries, and analyst workflows, including a concrete .cursorrules block and a stack-specific project structure.

Which stack is assumed?

A Python based stack with FastAPI, PostgreSQL via SQLAlchemy, Alembic for migrations, Redis for queues, and the OpenAI API for AI assisted summaries.

How do I apply the .cursorrules block?

Copy the provided block into the project root as .cursorrules. Adapt environment references and keys to your project. Do not expose secrets in code or logs.

What tests should I run?

Unit tests for parsing and AI helpers, integration tests for ingestion and grouping, and end-to-end tests for analyst workflows. Use CI to enforce linting and typing.

How can I extend for additional log sources?

Follow the directory rules and create adapters under src/ingestion, with a consistent schema and tests; ensure AI summaries can handle new sources through a common normalization layer.