# Sec Privacy Engineering

> Design privacy-protecting systems — GDPR / CCPA / HIPAA compliance, data minimisation, anonymisation, consent management, data retention, breach notification — with explicit privacy impact assessments.

- Skill: `quantumquirkxyz/sec-privacy-engineering` (Agent Skill)
- Install (CLI): `npx skillmds@latest add quantumquirkxyz/sec-privacy-engineering`
- Raw SKILL.md: https://api.skillmd.com/api/skills/quantumquirkxyz/sec-privacy-engineering/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: quantumquirkxyz (https://skillmd.com/u/quantumquirkxyz)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/quantumquirkxyz/sec-privacy-engineering

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## Contract

- **Input:** system architecture, data types, users, jurisdictions.
- **Output:** Privacy Impact Assessment + data-flow map + compliance checklist.
- **Side effects:** may require legal review (not done by skill alone).
- **Dependencies:** legal / compliance expert for final approval.
- **Stop condition:** PIA and checklist complete; legal review noted.
- **Risk:** medium — privacy violations have legal / reputation consequences; requires expert validation.
- **Boundary:** designs privacy controls and documents compliance gaps; does not provide legal advice.

# Privacy Engineering

Design **privacy-protecting systems** — GDPR / CCPA / HIPAA — with explicit data minimisation, anonymisation, consent, and breach-notification controls.

## Process

### 1. Data inventory
- What data is collected? (PII, health data, financial, behavioural, biometric, location)
- Source (user input, sensors, third party, derived).
- Classification (public, internal, confidential, restricted, secret).

**Completion criterion:** inventory saved.

### 2. Purpose and legal basis
- Why is each data needed? Can the purpose be achieved with less data?
- Legal basis: consent, contract, legal obligation, vital interest, public task, legitimate interest (with balance test).
- Users must be informed clearly.

**Completion criterion:** purpose and basis stated per data type.

### 3. Data-flow mapping
Map flows: collection → processing → storage → sharing → archive → deletion.
Mark where data crosses borders (jurisdiction change) or enters third-party systems.

**Completion criterion:** data-flow diagram saved.

### 4. Controls
- **Minimisation:** collect only needed fields; use pseudonymisation where possible.
- **Encryption:** at rest (AES-256), in transit (TLS 1.3), in use (homomorphic / secure enclaves if required).
- **Access:** least-privilege; role-based; audit logs.
- **Retention:** define retention period per data type; automatic deletion after period.
- **Consent:** explicit, granular, revocable; record consent state.
- **Breach notification:** 72-hour notification for GDPR; process for detection, containment, notification, remediation.

**Completion criterion:** controls matched to risks; gaps documented.

### 5. Impact assessment
Identify high-risk processing (systematic profiling, large-scale sensitive data, automated decision-making with legal effects). For high-risk: conduct Data Protection Impact Assessment (DPIA / PIA).

**Completion criterion:** PIA completed for high-risk processing; justification if low-risk.

### 6. Checklists and compliance
- GDPR: lawful basis, consent, data subject rights (access / rectification / erasure / portability / restriction / objection), DPO, breach notification, transfer safeguards.
- CCPA: notice at collection, opt-out of sale, non-discrimination, service-provider contracts.
- HIPAA: PHI safeguards (administrative, physical, technical), business associate agreements.

**Completion criterion:** checklist filled; gaps flagged for legal review.