<!-- Copyright (c) 2026 defconxt. All rights reserved. -->
<!-- Licensed under AGPL-3.0 — see LICENSE file for details. -->
---
name: implementing-identity-data-governance
description: >-
  Establish governance over identity data quality, lifecycle, and compliance. Covers data standards, quality monitoring, and privacy compliance.
domain: cybersecurity
subdomain: identity-security
tags:
  - identity-data
  - data-quality
  - data-governance
  - identity-lifecycle
  - privacy
version: "1.0"
author: defconxt
license: AGPL-3.0
metadata:
  mitre-attack: ["T1078"]
---

# Implementing Identity Data Governance

## Overview

Identity data governance ensures that identity information is accurate,
consistent, and compliant across all systems. Poor identity data quality
leads to access errors, compliance failures, and security gaps.

## Prerequisites

| Requirement | Install |
|---|---|
| Identity provider | Azure AD, Okta, or AD |
| HR system | Authoritative source for employee data |
| IGA platform | Identity governance and administration |
| Python 3.10+ | For agent tooling |

## Key Concepts

### Data Quality Dimensions

| Dimension | Definition | Example Issue |
|---|---|---|
| Accuracy | Data matches real-world state | Wrong job title |
| Completeness | Required attributes populated | Missing manager |
| Consistency | Same data across systems | Email differs in AD vs HR |
| Timeliness | Updates applied promptly | Terminated user active |
| Uniqueness | No duplicate identities | Same person, two accounts |

### Authoritative Sources

- **HR system** — Name, title, department, manager, status
- **IT provisioning** — Username, email, group memberships
- **Security team** — Privileged access designations
- **User self-service** — Phone, preferred name, MFA methods

### Privacy Requirements

Identity data is personal data under GDPR, CCPA:
- **Minimization** — Collect only necessary attributes
- **Purpose limitation** — Use only for stated purposes
- **Retention limits** — Delete when no longer needed
- **Subject rights** — Support access, correction, deletion

## Workflow

1. **Define identity data standards** — required attributes, formats, quality rules
2. **Map authoritative sources** — designate single source of truth per attribute
3. **Implement quality monitoring** — automated checks for accuracy and completeness
4. **Configure synchronization** — ensure consistent data across all systems
5. **Establish data ownership** — assign stewards for identity data domains
6. **Implement privacy controls** — apply minimization and retention policies
7. **Audit and report** — measure data quality metrics and remediate issues

## Quick Reference

```bash
# Run the agent
node scripts/agent.js analyze --target <scope>
node scripts/agent.js report --target <scope>
```

## Detection

```yaml
title: Identity Data Governance Detection
id: 935057ae-146f-42ba-bffd-bafb06618a09
status: experimental
description: Detects suspicious activity related to implementing identity data governance techniques in identity security context
logsource:
  category: authentication
  product: windows
detection:
  selection:
    EventType: authentication
    Status: failure
  condition: selection
level: high
tags:
  - attack.t1078
  - attack.credential_access
falsepositives:
  - Service account authentication during scheduled batch processing
```

## Verification

| Check | Method |
|---|---|
| Standards defined | Identity data dictionary published |
| Sources mapped | Authoritative source documented per attribute |
| Monitoring active | Quality checks running daily |
| Sync working | Identity data consistent across systems within 4 hours |
| Privacy compliant | Minimization and retention controls in effect |

## References

- [ISO 27001 A.5.14](https://www.iso.org/standard/27001)
- [GDPR Art. 5](https://gdpr-info.eu/art-5-gdpr/)
- [NIST SP 800-63](https://csrc.nist.gov/pubs/sp/800/63/4/ipd)
- [Data Governance Institute](https://datagovernance.com/)
