Automatic redaction in logs

📋 Product Requirements Document

PRD: Automatic redaction in logs

Issue: #149
Milestone: Phase 4: Security
Labels: pii-redaction, hacktoberfest

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PRD: Automatic Redaction in Logs

1. Overview

1.1 Purpose

The purpose of this feature development is to implement an automatic redaction system within MeshHook’s logging facilities to ensure that Personally Identifiable Information (PII) is detected and redacted from logs before they are stored or displayed. This initiative is critical for enhancing privacy and compliance with data protection regulations across MeshHook’s operations, particularly in multi-tenant environments where data segregation and privacy are paramount.

1.2 Alignment with Project Goals

This feature directly contributes to MeshHook's overarching goals of delivering a secure, privacy-compliant, and reliable workflow engine. By adding automatic log redaction capabilities, we reinforce our commitment to security and privacy, ensuring MeshHook remains a trusted tool for developers, automation engineers, and enterprise teams dealing with sensitive information.

2. Functional Requirements

1. Automatic Detection and Redaction: Automatically identify and redact PII in logs, using predefined patterns and heuristics, before storage or display.
2. Customizable Redaction Rules: Allow administrators to define custom redaction rules, accommodating various data protection requirements and compliance standards.
3. Audit Trail: Implement an audit trail for redaction activities, capturing the occurrence of redaction without storing the original PII.
4. Performance: The redaction process must operate with minimal latency, ensuring log processing remains efficient.
5. API for Redaction Rule Management: Provide API endpoints for managing redaction rules, including creation, listing, and deletion.

3. Non-Functional Requirements

• Performance: The redaction process should not increase log processing times by more than 10%.
• Reliability: Achieve at least 99.9% accuracy in detecting and redacting PII from logs.
• Security: Use state-of-the-art techniques to ensure that redacted logs are irreversible, preventing any possibility of reconstructing the original PII.
• Maintainability: Develop the log redaction feature in a modular, well-documented manner to facilitate future updates and maintenance.

4. Technical Specifications

4.1 Architecture Context

• Integration Points:
  • The feature will integrate with Supabase Realtime for the streaming of logs and the existing logging mechanism within MeshHook’s SvelteKit components and worker processes.
• Components Affected:
  • The logging service layer will be modified to include the redaction process.
  • The database schema will be expanded to accommodate the storage of redaction rules and audit logs.

4.2 Implementation Approach

1. Analysis: Review the current logging infrastructure to identify integration points for the redaction process.
2. Data Model Design:
   • log_redaction_rules: To store patterns and rules for identifying PII.
   • log_redaction_audit: To log instances of redaction, including timestamps and rule identifiers.
3. Redaction Logic Development: Implement the logic for detecting PII based on rules and redacting it from logs.
4. API Development: Create RESTful API endpoints for managing redaction rules.
5. Integration: Integrate the redaction logic into the existing logging flow.
6. Testing & Documentation: Conduct thorough testing and update the API and technical documentation.

4.3 Data Model Changes

• log_redaction_rules(id SERIAL PRIMARY KEY, pattern TEXT, description TEXT, created_at TIMESTAMP)
• log_redaction_audit(id SERIAL PRIMARY KEY, rule_id INTEGER REFERENCES log_redaction_rules(id), redacted_at TIMESTAMP)

4.4 API Endpoints

• POST /api/redaction-rules: Add a new redaction rule.
• GET /api/redaction-rules: Retrieve all redaction rules.
• DELETE /api/redaction-rules/{id}: Remove a redaction rule.

5. Acceptance Criteria

• PII is automatically detected and redacted from logs based on predefined and custom rules.
• The log redaction process does not increase overall log processing time by more than 10%.
• New API endpoints for managing redaction rules are fully functional.
• An audit trail for redaction activities is maintained without storing original PII.
• Documentation is updated to reflect the new redaction features and API endpoints.
• The solution achieves >95% test coverage including unit and integration tests.

6. Dependencies and Prerequisites

• Access to the MeshHook codebase and development environment.
• Supabase account and Postgres for development and testing.
• Understanding of the existing logging mechanism and data storage architecture.

7. Implementation Notes

7.1 Development Guidelines

• Adhere to MeshHook’s coding standards and documentation practices.
• Develop in a feature branch, with code reviews required before merging.
• Ensure all new code is accompanied by comprehensive tests.

7.2 Testing Strategy

• Unit Testing: For the redaction logic and rule management API endpoints.
• Integration Testing: To cover the entire process from log generation to storage/display with redaction applied.
• Performance Testing: To ensure the redaction process meets the specified performance criteria.

7.3 Security Considerations

• Verify that redacted logs cannot be reverse-engineered to reveal PII.
• Secure management of redaction rules to prevent unauthorized access or manipulation.

7.4 Monitoring & Observability

• Implement monitoring to observe the impact of the redaction process on log processing times.
• Set up alerts for failures in the redaction process or deviations from expected performance metrics.

8. Related Documentation

• MeshHook PRD, Architecture, and Security guidelines (as listed in the initial PRD).

Note: This document and the procedures outlined are in alignment with MeshHook’s goals of enhancing privacy, security, and compliance capabilities within its workflow engine.

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This PRD was AI-generated using gpt-4-turbo-preview from GitHub issue #149
Generated: 2025-10-10

📎 Generated Documentation

• 📄 PRD Document: 149-automatic-redaction-in-logs.md
• 🎨 PlantUML Diagram: 149-automatic-redaction-in-logs.puml
• 🖼️ Diagram Image: 149-automatic-redaction-in-logs.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

Start by reviewing the existing logging infrastructure, logging service layer, SvelteKit components, worker processes, and database schema to identify integration points. Then assess the proposed redaction rules, audit tables, and REST endpoints. Done means PII is redacted before storage or display, rule management and auditing work, performance and test-coverage targets are met, and documentation is updated.