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---
technique: building-security-data-api-layer
subdomain: security-data-engineering
title: "Building Security Data API Layer"
description: "Techniques and methodologies for building security data api layer"
tags:
  - API-design
  - security-data
  - REST
  - GraphQL
  - data-access
metadata:
  mitre-attack: []
---

# Building Security Data API Layer

> Design and implement secure API layers for accessing, querying, and managing security data across SIEM, SOAR, and threat intelligence platforms.

## Overview

A security data API layer provides unified, authenticated access to security telemetry, alerts, and investigation data. This technique covers API design patterns, authentication, rate limiting, and query optimization for security data services.

## Core Concepts

- **Unified query interface**: Abstract multiple backend data stores behind a single API
- **Authentication & authorization**: OAuth2/OIDC with scope-based access to sensitive data
- **Rate limiting**: Protect backend systems from query abuse and resource exhaustion
- **Query optimization**: Push-down predicates, pagination, and streaming for large result sets
- **Audit logging**: Record all API access for compliance and forensic purposes

## Workflow

1. Inventory security data sources and access patterns
2. Design API schema with resource-oriented endpoints
3. Implement authentication with OAuth2 and API key support
4. Build query translation layer for backend data stores
5. Add rate limiting and quota management
6. Implement pagination and streaming for large datasets
7. Deploy comprehensive audit logging
8. Write OpenAPI specification and generate client SDKs
9. Load test API under realistic query patterns
10. Monitor API health, latency, and error rates

## Implementation

```python
from dataclasses import dataclass, field
from datetime import datetime
from typing import Any, Optional
import json


@dataclass
class APIRequest:
    endpoint: str
    method: str
    params: dict = field(default_factory=dict)
    auth_token: str = ""
    timestamp: datetime = field(default_factory=datetime.utcnow)


@dataclass
class APIResponse:
    status: int
    data: Any = None
    error: str | None = None
    pagination: dict = field(default_factory=dict)


class SecurityDataAPI:
    """Unified API layer for security data access."""

    def __init__(self, rate_limit: int = 100) -> None:
        self.rate_limit = rate_limit
        self.request_log: list[APIRequest] = []
        self.backends: dict[str, Any] = {}

    def register_backend(self, name: str, connector: Any) -> None:
        self.backends[name] = connector

    def query(self, request: APIRequest) -> APIResponse:
        self.request_log.append(request)
        if not self._check_rate_limit(request.auth_token):
            return APIResponse(status=429, error="Rate limit exceeded")
        if not self._validate_auth(request.auth_token):
            return APIResponse(status=401, error="Unauthorized")
        return APIResponse(status=200, data={"results": [], "count": 0})

    def _check_rate_limit(self, token: str) -> bool:
        recent = [r for r in self.request_log[-self.rate_limit:] if r.auth_token == token]
        return len(recent) < self.rate_limit

    def _validate_auth(self, token: str) -> bool:
        return bool(token and len(token) > 8)

    def audit_trail(self) -> list[dict]:
        return [{"endpoint": r.endpoint, "method": r.method, "time": r.timestamp.isoformat()} for r in self.request_log]
```

## Best Practices

- Use OAuth2 with short-lived tokens—API keys as fallback only for service accounts
- Implement field-level access control for sensitive data (e.g., raw packet captures)
- Log every API call with caller identity, query parameters, and response size
- Use cursor-based pagination for time-series security data—offset pagination is unreliable
- Version APIs explicitly (v1, v2) and maintain backward compatibility
- Rate limit by token and by IP to prevent both authenticated and anonymous abuse

## Related Techniques

- [Performing Detection Signal Analysis](../performing-detection-signal-analysis/SKILL.md)
- [Implementing Security Data Backup Strategy](../implementing-security-data-backup-strategy/SKILL.md)
