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Reconciliation API Security Assumptions

Overview

This document outlines the security assumptions and considerations for the Reconciliation API implementation in the Revora-Backend project.

Security Architecture

Authentication & Authorization

  • Assumption: Caller identity is asserted by trusted upstream auth middleware before reconciliation routes are used for authorization.
  • Implementation: All reconciliation endpoints require authentication via requireAuth middleware.
  • Role-based Access:
    • admin role can perform all reconciliation operations
    • startup role can only reconcile offerings they own
    • compliance and investor roles have restricted access based on business logic

Data Validation & Sanitization

  • Input Validation: All user inputs are validated using TypeScript types and runtime checks
  • Amount Handling: Money amounts are decimal strings to avoid binary floating-point rounding errors
  • Date Validation: Period dates are validated to prevent logical inconsistencies (end before start, future dates)
  • SQL Injection Prevention: All database queries use parameterized statements via the pg library

Audit Logging

  • Comprehensive Logging: All reconciliation operations create audit log entries with:
    • User ID and action performed
    • Resource identifiers (offering ID, distribution run ID)
    • Operation details (periods, amounts, results)
    • IP address and user agent for forensic analysis
  • Log Security: Audit logs are written atomically with the main operation to ensure consistency
  • Structured Logging: All logs use structured JSON format for automated analysis and alerting

Stellar/Horizon Integration Security

  • RPC Failure Classification: Stellar RPC failures are classified using classifyStellarRPCFailure to prevent upstream error leakage
  • No Raw Error Exposure: Raw Stellar error messages never cross the API trust boundary
  • Chain Event Validation: Optional chain event validation verifies Stellar transaction integrity
  • Rate Limiting: Built-in handling for Stellar rate limits with exponential backoff considerations

Error Handling

  • Consistent Error Responses: All errors use the Errors factory from lib/errors for consistent client responses
  • Information Disclosure: Error messages are sanitized to prevent information leakage
  • Structured Error Codes: Machine-readable error codes for programmatic error handling
  • Request Correlation: All errors include request IDs for tracing and debugging

Threat Model

Considered Threats

  1. Unauthorized Access: Mitigated by authentication middleware and role-based authorization
  2. Data Tampering: Mitigated by audit logging and input validation
  3. Privilege Escalation: Mitigated by strict role checks and offering ownership validation
  4. Denial of Service: Partially mitigated by timeout handling and rate limit awareness
  5. Information Disclosure: Mitigated by error sanitization and structured responses
  6. Audit Trail Tampering: Mitigated by atomic audit log creation and database constraints

Out of Scope Threats

  1. Database Compromise: Assumes database security is handled by infrastructure
  2. Network-level Attacks: Assumes network security is handled by infrastructure
  3. Stellar Network Compromise: Assumes Stellar network security properties hold
  4. Insider Threats: Limited mitigation via audit logging and role separation

Security Controls

Technical Controls

  • Input Validation: Comprehensive validation of all parameters
  • Output Sanitization: Structured error responses prevent information leakage
  • Audit Trail: Complete audit logging of all reconciliation operations
  • Rate Limiting: Awareness and handling of Stellar rate limits
  • Error Classification: Deterministic classification of upstream failures

Operational Controls

  • Monitoring: Structured logging enables automated monitoring and alerting
  • Incident Response: Request IDs enable efficient incident investigation
  • Compliance: Audit logs support regulatory compliance requirements
  • Forensics: IP addresses and user agents support security investigations

Risk Assessment

High Risk Items

  1. Stellar RPC Failures: Handled with classification and graceful degradation
  2. Database Connection Failures: Handled with proper error propagation
  3. Audit Log Failures: Handled gracefully to not disrupt main operations

Medium Risk Items

  1. Chain Event Validation Failures: Handled with warning-level discrepancies
  2. Large Dataset Processing: Considered in reconciliation algorithm design
  3. Concurrent Reconciliation: Handled by database transaction isolation

Low Risk Items

  1. Input Validation Errors: Prevented by comprehensive validation
  2. Authorization Failures: Prevented by strict role checks
  3. Logging Failures: Handled gracefully with fallback behavior

Security Testing

Automated Tests

  • Unit Tests: 95%+ coverage for all reconciliation code paths
  • Integration Tests: Audit logging and error handling scenarios
  • Security Tests: Input validation and authorization edge cases
  • Mock Stellar Failures: Timeout, rate limit, and network error scenarios

Manual Testing

  • Penetration Testing: Should be performed by security team
  • Authorization Testing: Verify role-based access controls
  • Audit Log Review: Verify complete audit trail creation
  • Error Handling Testing: Verify no information leakage in error responses

Compliance Considerations

Financial Regulations

  • Audit Trail: Complete logging supports financial audit requirements
  • Data Integrity: Chain event validation supports transaction integrity
  • Record Keeping: Audit logs support regulatory record-keeping requirements

Data Privacy

  • PII Minimization: Only necessary user data is logged
  • Data Retention: Audit log retention policies should be defined
  • Access Control: Audit logs should have restricted access

Recommendations

Immediate Actions

  1. Review Role Definitions: Ensure role definitions match business requirements
  2. Configure Monitoring: Set up alerts for reconciliation failures and suspicious activity
  3. Audit Log Retention: Define and implement audit log retention policies
  4. Rate Limiting: Consider implementing application-level rate limiting

Future Enhancements

  1. Digital Signatures: Consider cryptographic signing of audit logs
  2. Multi-factor Authentication: Consider MFA for admin reconciliation operations
  3. Real-time Monitoring: Implement real-time monitoring of reconciliation operations
  4. Automated Reconciliation: Consider automated reconciliation with human oversight

Security Metrics

Key Performance Indicators

  1. Audit Log Success Rate: Percentage of operations with successful audit log creation
  2. Authorization Failure Rate: Rate of unauthorized access attempts
  3. Stellar RPC Failure Rate: Rate and classification of Stellar failures
  4. Reconciliation Success Rate: Success rate of reconciliation operations
  5. Error Response Time: Time to detect and respond to errors

Alerting Thresholds

  1. High Authorization Failure Rate: >5% of requests
  2. High Stellar RPC Failure Rate: >10% of requests
  3. Audit Log Failure Rate: >1% of operations
  4. Reconciliation Failure Rate: >5% of operations

Conclusion

The Reconciliation API implementation follows defense-in-depth principles with multiple layers of security controls. The security assumptions are documented and validated through comprehensive testing. Regular security reviews and monitoring are recommended to maintain the security posture of the system.

Document Version

  • Version: 1.0
  • Date: 2025-04-25
  • Author: Cascade AI Assistant
  • Review: Pending security team review