<!-- Copyright (c) 2026 defconxt. All rights reserved. -->
<!-- Licensed under AGPL-3.0 — see LICENSE file for details. -->
---
name: automating-security-posture-scoring
description: >-
  Automate security posture scoring with weighted control assessments, continuous
  monitoring data aggregation, trend analysis, benchmark comparison, and
  executive reporting for organizational security health visibility.
domain: cybersecurity
subdomain: security-operations-automation
tags:
  - posture-scoring
  - security-metrics
  - continuous-monitoring
  - benchmarks
  - risk-scoring
  - executive-reporting
version: "1.0"
author: defconxt
license: AGPL-3.0
metadata:
  mitre-attack: []
---

# Automating Security Posture Scoring

## Overview

Security posture scoring aggregates data from vulnerability management, IAM,
endpoint protection, network security, and compliance systems into a composite
score that reflects organizational security health. Scores enable trend
tracking, benchmark comparison, and executive communication.

Mode: `[MODE: ARCHITECT]` — Security measurement and governance.

## Prerequisites

| Requirement | Details |
|---|---|
| Python 3.10+ | Required |
| API access to security tools (vulnerability scanner, EDR, IAM, SIEM) | Required |
| Historical posture data for trend analysis | Required |
| Framework mappings (NIST CSF, CIS Controls) | Required |

## Key Concepts

### Weighted Scoring Model

```python
DOMAIN_WEIGHTS = {
    "vulnerability_management": 0.25,
    "identity_access": 0.20,
    "endpoint_protection": 0.20,
    "network_security": 0.15,
    "data_protection": 0.10,
    "incident_response": 0.10,
}

def calculate_posture_score(domain_scores: dict[str, float]) -> float:
    """Calculate weighted composite posture score (0-100)."""
    score = 0.0
    for domain, weight in DOMAIN_WEIGHTS.items():
        domain_score = domain_scores.get(domain, 0.0)
        score += domain_score * weight
    return round(score, 1)
```

### Trend Analysis

```python
def analyze_trend(scores: list[float]) -> dict:
    """Analyze posture score trend over time."""
    if len(scores) < 2:
        return {"trend": "insufficient_data"}
    delta = scores[-1] - scores[0]
    avg_change = delta / (len(scores) - 1)
    return {
        "current": scores[-1],
        "previous": scores[-2],
        "change": round(delta, 1),
        "avg_change_per_period": round(avg_change, 1),
        "direction": "improving" if delta > 0 else "degrading" if delta < 0 else "stable",
    }
```

## Workflow

### Step 1: Calculate Posture Score

```bash
node scripts/agent.js --action score --scope full
```

### Step 2: Domain Breakdown

```bash
node scripts/agent.js --action breakdown --scope full
```

### Step 3: Trend Report

```bash
node scripts/agent.js --action trend --periods 12
```

## Verification

- [ ] Composite score reflects weighted domain contributions
- [ ] Individual domain scores map to measurable controls
- [ ] Trend analysis identifies improving/degrading areas
- [ ] Benchmark comparison shows position vs. industry peers

## References

- [NIST CSF 2.0 Tiers](https://www.nist.gov/cyberframework)
- [CIS Controls v8 Maturity Model](https://www.cisecurity.org/controls)
- [BSIMM Security Measurement](https://www.bsimm.com/)
