Artifact sanitization

[ralyodio]

📋 Product Requirements Document

PRD: Artifact sanitization

Issue: #150
Milestone: Phase 4: Security
Labels: pii-redaction, hacktoberfest

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PRD: Artifact Sanitization

Overview

Artifact Sanitization is a critical feature designed to enhance the security posture of MeshHook by automatically redacting Personally Identifiable Information (PII) from workflow artifacts. This feature is integral to ensuring MeshHook remains compliant with global data protection regulations and maintains its commitment to user privacy within its multi-tenant environment. The objective is to seamlessly integrate PII redaction capabilities into the workflow engine, thereby safeguarding sensitive information without compromising the workflow's performance or integrity.

Functional Requirements

1. Sanitization Engine: Develop a sanitization engine capable of detecting and redacting PII from workflow artifacts. This engine should support common PII types (e.g., names, email addresses, phone numbers) and allow for extensibility.

2. Customization Capabilities: Users must be able to define custom PII redaction rules per project. This includes specifying identifiers for what constitutes PII and determining the redaction technique (e.g., obfuscation, removal).

3. Workflow Integration: Embed the sanitization process within the workflow execution pipeline, ensuring artifacts are sanitized before storage. This should be a configurable step in the pipeline.

4. Audit Trail: Implement an audit logging mechanism for tracking sanitization actions. This includes logging what data was sanitized, the rule applied, and timestamp, without logging the PII itself.

Non-Functional Requirements

• Performance: The sanitization process must introduce minimal latency to the workflow execution, aiming for a sub-second impact per artifact.

• Accuracy: Employ advanced PII detection techniques to minimize false positives and negatives. The engine should correctly identify PII with high confidence.

• Security: Adopt secure coding practices throughout the development of the sanitization engine to prevent security vulnerabilities.

• Maintainability: Architect the sanitization engine for easy maintenance and updates, allowing for the evolution of PII detection algorithms and redaction methods.

Technical Specifications

Architecture Context

The artifact sanitization feature will be incorporated into MeshHook's existing architecture, specifically within the workflow execution pipeline. It will act as a filter, processing artifacts post-execution and pre-storage.

Integration Points:

• Workflow Execution Pipeline: Inject the sanitization step after workflow execution and before the artifact storage phase.
• Supabase Storage: Store sanitized artifacts securely, ensuring that only cleaned versions are persisted.

Implementation Approach

1. Requirement Analysis: Conduct an initial analysis to understand the current handling of workflow artifacts and identify common PII categories.

2. Sanitization Engine Design: Architect the engine focusing on modular design for PII detection (using regex, ML models) and redaction methods.

3. Integration Design: Plan the integration with the workflow pipeline to ensure the sanitization step does not disrupt existing processes.

4. Development: Follow Test-Driven Development (TDD) to build the sanitization engine and integration components.

5. Testing: Perform comprehensive testing, including unit, integration, and end-to-end tests, to validate functionality and performance.

6. Documentation: Create detailed documentation for the sanitization feature, including setup, configuration, and usage guidelines.

7. Deployment: Prepare and execute a deployment plan for rolling out the sanitization feature to production environments.

Data Model Changes

• SanitizationRules: A new database table to store user-defined PII redaction rules. Columns include rule_id, project_id, pattern, redaction_method, and created_at.

API Endpoints

• GET /projects/{projectId}/sanitization-rules: Retrieves a list of sanitization rules defined for a project.
• POST /projects/{projectId}/sanitization-rules: Allows creation or updating of sanitization rules for a project.

Acceptance Criteria

• The sanitization engine can accurately identify and redact PII across various artifact types.
• Users can create, update, and delete custom PII redaction rules.
• Sanitization process is integrated within the workflow pipeline with negligible performance impact.
• Sanitization actions are audited, with logs available for review.
• Comprehensive documentation is available, guiding users on configuring and using the sanitization feature.
• The feature meets all specified security and performance benchmarks.

Dependencies

• Access to MeshHook's current codebase and infrastructure.
• Supabase for artifact storage and log streaming capabilities.
• Development libraries for regex and potentially machine learning models for PII detection.

Implementation Notes

Development Guidelines

• Adhere to MeshHook's coding standards, ensuring code is modular, well-commented, and follows secure coding practices.

• Utilize environment variables for sensitive configurations to enhance security.

Testing Strategy

• Develop unit tests for the sanitization engine's core functionality.

• Create integration tests to verify the engine's integration with the workflow pipeline.

• Execute end-to-end tests to assess the feature's impact on the overall system performance and reliability.

Security Considerations

• Ensure sanitization rules and logs are stored securely, implementing access control based on project_id.

• Review and implement secure coding practices to mitigate risks such as injection attacks and unauthorized access to sensitive information.

Monitoring & Observability

• Integrate metrics to monitor the impact of the sanitization process on workflow execution times.

• Implement logging for all sanitization actions to support auditability and troubleshooting.

Related Documentation

• Main PRD
• Architecture
• Security Guidelines
• Operations Guide

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This PRD was AI-generated using gpt-4-turbo-preview from GitHub issue #150
Generated: 2025-10-10

📎 Generated Documentation

• 📄 PRD Document: 150-artifact-sanitization.md
• 🎨 PlantUML Diagram: 150-artifact-sanitization.puml
• 🖼️ Diagram Image: 150-artifact-sanitization.png

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This issue body was auto-generated from the PRD. Original issue content is preserved in the PRD document.
Last updated: 2025-10-10