This document describes the security implementation for Marvis Vault, focusing on protecting against real-world attacks while maintaining usability through a gradual migration approach.

Vulnerability: String trustScores like "80" behave differently than numeric values in comparisons.

# INSECURE - String comparison
"80" > "9"   # False (lexicographic comparison)

# SECURE - Numeric comparison  
80 > 9       # True (numeric comparison)

Attack Vector: Attackers submit string values to bypass numeric threshold checks.

Solution: All trustScores are normalized to float values, preventing type confusion.

Vulnerability: Infinity, NaN, and boolean values can bypass security checks.

# Attack examples
trustScore = float('inf')  # Always passes > X checks
trustScore = float('nan')  # Makes all comparisons false
trustScore = True          # Treated as 1 in numeric context

Solution: Explicit validation rejects Infinity, NaN, and boolean values.

Vulnerability: Unvalidated input could contain malicious payloads.

Attack Vectors:

• SQL Injection: role = "admin'; DROP TABLE users;--"
• XSS: name = "<script>alert(document.cookie)</script>"
• Command Injection: dept = "IT; rm -rf /"
• Path Traversal: file = "../../../etc/passwd"

Solution: Input validation rejects patterns matching known attack vectors.

Vulnerability: Large or deeply nested JSON can exhaust resources.

Attack Vectors:

• Oversized payloads (>1MB)
• Deeply nested JSON (>100 levels)
• Extremely long strings

Solution: Size and depth limits with early rejection.

Vulnerability: Agents claiming high-privilege roles without verification.

Attack Vector: role = "admin" or role = "doctor" to gain elevated access.

Solution: Role validation with logging of high-privilege role claims.

vault/
├── utils/
│   ├── security/
│   │   ├── __init__.py
│   │   ├── validators.py      # Core validation logic
│   │   ├── runtime_bypass.py  # Emergency bypass API
│   │   └── monitoring.py      # Performance tracking
│   └── security_validators.py  # Legacy compatibility layer

1. New Module: Create vault.utils.security with proper validation
2. Compatibility Layer: Existing code continues to work during migration
3. Feature Flags: Runtime configuration for validation behavior
4. Monitoring: Track validation performance and failures

For critical situations requiring validation bypass:

from vault.utils.security import bypass_validation

# Temporary bypass with reason logging
with bypass_validation(reason="Emergency fix for production issue #123"):
    # Validation is relaxed here
    result = process_agent_context(context)

Located in tests/security/:

• test_type_confusion.py - String vs numeric attacks
• test_injection_attacks.py - SQL, XSS, command injection
• test_dos_attacks.py - Large payload, deep nesting
• test_special_values.py - Infinity, NaN, boolean attacks
• test_role_impersonation.py - Privilege escalation attempts

# Run all security tests
pytest tests/security/ -v

# Run specific attack category
pytest tests/security/test_injection_attacks.py -v

# Run with performance monitoring
MONITOR_PERFORMANCE=1 pytest tests/security/ -v

• Validation time per request
• Memory usage for large payloads
• Cache hit rates
• Rejection rates by attack type

from vault.utils.security import get_validation_metrics

metrics = get_validation_metrics()
print(f"Average validation time: {metrics['avg_time_ms']}ms")
print(f"Requests rejected: {metrics['rejection_rate']}%")

1. String trustScores: Now converted to float

   • Before: {"trustScore": "80"} returns "80"
   • After: {"trustScore": "80"} returns 80.0

2. Invalid Input: Now rejected instead of logged

   • Before: SQL injection logged but processed
   • After: SQL injection causes validation error

3. Error Messages: More specific for security

   • Before: "role must be a string"
   • After: "role is required" or "role must be string type"

# Old code expecting string trustScore
if context['trustScore'] > "70":  # BROKEN

# New code with numeric trustScore  
if context['trustScore'] > 70:    # CORRECT

# Handle validation errors
try:
    validated = validate_agent_context(context)
except SecurityValidationError as e:
    # Handle validation failure
    log.error(f"Validation failed: {e}")

1. Fail Secure: When in doubt, reject the input
2. Defense in Depth: Multiple validation layers
3. Least Privilege: Default to minimal permissions
4. Audit Everything: Log security-relevant events
5. Performance Matters: Security shouldn't break usability

1. Machine Learning: Detect anomalous patterns
2. Rate Limiting: Prevent brute force attacks
3. Cryptographic Signatures: Verify agent identity
4. Zero Trust: Validate every request fully

For security concerns or questions, contact the Marvis Vault security team.