Document ID: RW-PA-001 Document Type: Privacy Assessment Version: Draft 1.0 Status: Working Draft Related Documents:
This Privacy Assessment evaluates the privacy posture of the Red Witch menstrual-cycle tracking application and assesses whether identified risks, design inputs, and architectural controls adequately address the privacy, safety, autonomy, and data-sovereignty concerns associated with reproductive-health data.
The assessment considers:
The objective is to determine whether Red Witch’s design supports a privacy-preserving, non-extractive, and user-controlled approach to menstrual health tracking.
The assessment covers:
The assessment does not evaluate:
Menstrual and reproductive-health information represents a category of highly sensitive personal information.
Potential harms associated with misuse include:
Unlike many consumer applications, privacy risks arise not only from unauthorized disclosure but also from inappropriate collection, inference, secondary use, and contextual misuse.
Consequently, privacy must be evaluated not only through confidentiality and security controls, but also through user agency, consent, governance, and contextual integrity.
Red Witch adopts the following privacy principles:
User data belongs to the user.
No collection, processing, sharing, or reuse shall occur without an explicit and legitimate user-authorized purpose.
Only information necessary to provide requested functionality shall be collected.
Data collection for speculative future use is prohibited.
User data should remain on the user’s device whenever practical.
Cloud storage shall be optional and require explicit user consent.
Consent must be:
Withdrawal of consent must be effective and meaningful.
Users shall be able to determine:
The application shall not rely on business models based upon:
The application shall recognize that data is not ownerless.
User data shall remain under user governance and shall not be treated as an unrestricted corporate asset.
The proposed architecture prioritizes local storage and offline functionality.
Assessment: Strong
Privacy Benefit:
Current design inputs emphasize collection of only information required for functionality.
Assessment: Strong
Privacy Benefit:
Current requirements emphasize:
Assessment: Strong
Privacy Benefit:
Threat modeling includes:
Assessment: Strong
Privacy Benefit:
The project explicitly rejects assumptions of implicit ownership and bundled consent.
Assessment: Strong
Privacy Benefit:
Current documentation focuses primarily on collected and stored data.
Insufficient attention is given to:
Examples:
Risk:
Derived information may become more sensitive than original user-entered data.
Recommendation:
Establish a dedicated Inference Governance Policy.
Current documentation defines ownership of entered data but does not explicitly define ownership of generated predictions.
Recommendation:
Users should retain ownership and control over:
Current requirements do not specify how predictions should be explained.
Risk:
Users may perceive the application as surveillant or opaque.
Recommendation:
Provide user-visible explanations for:
Privacy controls exist but user experience requirements are not explicitly defined.
Recommendation:
Create Privacy UX requirements covering:
Current documentation partially addresses acquisition and corporate change risks.
Recommendation:
Establish governance controls covering:
Traditional privacy assessments focus on unauthorized access.
For Red Witch, contextual privacy is equally important.
Users may accept highly sensitive processing when:
Users may reject otherwise secure systems when:
Assessment:
Current documentation addresses contextual privacy indirectly through consent, sovereignty, transparency, and anti-coercive design.
However, contextual expectations regarding inference and prediction should be documented more explicitly.
Assessment Rating: Partially Addressed
The project demonstrates strong alignment with modern data-sovereignty principles through:
Assessment Rating: Strong
The design substantially exceeds typical consumer-app privacy practices.
| Category | Assessment |
|---|---|
| Data Minimization | Strong |
| Local Storage | Strong |
| Security Threat Coverage | Strong |
| Privacy Threat Coverage | Strong |
| Consent Model | Strong |
| Data Sovereignty | Strong |
| Contextual Privacy | Moderate |
| Privacy UX | Moderate |
| Inference Governance | Developing |
| Derived Data Governance | Developing |
| Corporate Governance Risk | Moderate |
Red Witch demonstrates a privacy posture significantly stronger than typical commercial menstrual-tracking applications.
The project incorporates:
The most significant remaining challenge is governance of derived information and predictive inference.
Future privacy work should focus on:
Subject to resolution of these gaps, the overall privacy posture is assessed as:
High Privacy Maturity – User-Centric and Sovereignty-Oriented