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RPC Failure Taxonomy - Security Assumptions

Overview

This document outlines the security assumptions and risk considerations for the Stellar RPC failure taxonomy implementation in Revora-Backend.

Security Model

Threat Model

  • External attackers attempting to exploit error information leakage
  • Internal threats from compromised error handling or logging systems
  • Denial of service through error-based resource exhaustion
  • Information disclosure via detailed error responses

Security Boundaries

Client-Facing API Boundary

  • Raw upstream error strings are NEVER exposed to clients
  • Internal system details (stack traces, internal paths) are sanitized
  • Sensitive configuration (API keys, secrets) is filtered from logs
  • Network topology information is abstracted

Logging Boundary

  • PII and sensitive data must be explicitly redacted before logging
  • Error sanitization removes potentially sensitive fields
  • Development vs Production behavior differs for stack trace inclusion

Security Assumptions

1. Error Sanitization

Assumption: The sanitizeError() function properly removes all sensitive data before logging or client exposure.

Implementation:

// Only allowed fields are preserved
const allowedKeys = ['status', 'statusText', 'code', 'message', 'result_xdr'];

Risk: If new sensitive fields are added to error objects, they must be explicitly added to the denylist.

2. Retry Logic Security

Assumption: Retry logic does not expose timing attacks or create resource exhaustion vectors.

Implementation:

  • Exponential backoff with maximum caps
  • Maximum retry attempts (3)
  • Retry delays are deterministic and predictable

Risk: Sophisticated attackers could potentially infer system state from retry patterns.

3. Rate Limit Handling

Assumption: Rate limit errors are handled securely without exposing internal rate limits.

Implementation:

  • Respects upstream retry-after headers
  • Falls back to safe default (60s) if header missing
  • Does not expose internal rate limit configurations

Risk: Attackers could potentially infer rate limit configurations from response patterns.

4. Error Classification

Assumption: Error classification does not leak sensitive system information.

Implementation:

  • Generic error messages for client responses
  • Detailed classification only used internally and in logs
  • No exposure of internal error codes or system states

Risk: Error patterns could potentially reveal system architecture or dependencies.

Risk Assessment

High Risk Items

  1. Information Disclosure: Raw error messages containing internal system details
  2. Timing Attacks: Retry patterns revealing system state
  3. Log Injection: Unsanitized error data in log files

Medium Risk Items

  1. Resource Exhaustion: Excessive retry attempts
  2. Rate Limit Discovery: Inferring rate limit configurations
  3. Error Pattern Analysis: Revealing system dependencies

Low Risk Items

  1. Generic Error Messages: Client-facing error responses
  2. Structured Logging: Properly sanitized log entries
  3. Retry Logic: Predictable and capped retry behavior

Security Controls

Input Validation

  • All error inputs are validated and sanitized
  • Type checking prevents injection attacks
  • Field filtering removes sensitive data

Output Sanitization

  • Client responses use generic, pre-defined messages
  • Internal error details are never exposed
  • Stack traces only included in development mode

Logging Security

  • Sensitive fields are explicitly filtered
  • PII is redacted before logging
  • Log levels are appropriate for sensitivity

Rate Limiting

  • Retry attempts are capped at maximum
  • Exponential backoff prevents resource exhaustion
  • Retry delays have maximum limits

Testing Security

Security Test Coverage

  • Error sanitization is tested with malicious inputs
  • Retry logic is tested for resource exhaustion
  • Rate limiting is tested for information disclosure

Integration Security Tests

  • End-to-end error handling preserves security boundaries
  • Concurrent request handling maintains security guarantees
  • Error logging does not expose sensitive information

Monitoring and Alerting

Security Monitoring

  • Unusual error patterns are logged for security analysis
  • High retry rates trigger alerts for potential attacks
  • Error classification anomalies indicate potential issues

Incident Response

  • Error handling failures are immediately visible
  • Security boundary violations trigger alerts
  • Log analysis tools detect suspicious patterns

Compliance Considerations

Data Privacy

  • No PII is logged or exposed in error responses
  • Error data retention follows company policies
  • Log access is controlled and audited

Security Standards

  • Error handling follows OWASP guidelines
  • Information disclosure is minimized
  • Security boundaries are clearly defined

Future Security Enhancements

Planned Improvements

  1. Enhanced Sanitization: More sophisticated sensitive data detection
  2. Rate Limit Discovery Protection: Add jitter to retry delays
  3. Error Pattern Obfuscation: Randomize some error responses
  4. Advanced Monitoring: ML-based anomaly detection for error patterns

Security Review Process

  1. Code Review: All error handling code is security reviewed
  2. Penetration Testing: Regular testing for information disclosure
  3. Security Audits: Periodic review of error handling security
  4. Threat Modeling: Ongoing analysis of potential attack vectors

Conclusion

The RPC failure taxonomy implementation maintains strong security boundaries while providing comprehensive error handling. The security assumptions are well-defined and the implementation includes appropriate controls to mitigate identified risks.

Regular security reviews and monitoring ensure that the security posture remains strong as the system evolves.