rate-limiting-security-research.py•10.1 kB
#!/usr/bin/env python3
"""
Research script to identify potential security issues with current rate limiting implementation
"""
import json
import time
import subprocess
from typing import Dict, Any, List
class RateLimitingSecurityResearch:
"""Research potential security issues with rate limiting"""
def __init__(self):
self.findings = []
def research_current_implementation(self):
"""Analyze current implementation for security issues"""
print("\n=== Rate Limiting Security Research ===\n")
# 1. Memory-based storage vulnerabilities
print("1. Memory-based storage analysis:")
print(" - Current: Using in-memory array to store timestamps")
print(" - Risk: Memory exhaustion attack by making many requests")
print(" - Finding: Array grows with each request, cleaned up only on next check")
self.findings.append({
"issue": "Memory exhaustion vulnerability",
"severity": "Medium",
"description": "Attacker could fill memory by making requests just under limit",
"mitigation": "Add maximum array size limit or periodic cleanup"
})
# 2. Per-instance limitation
print("\n2. Per-instance rate limiting:")
print(" - Current: Each server instance has separate rate limiter")
print(" - Risk: Multiple instances bypass rate limits")
print(" - Finding: No distributed rate limiting")
self.findings.append({
"issue": "Per-instance bypass",
"severity": "High",
"description": "Multiple MCP clients can bypass rate limits",
"mitigation": "Consider distributed rate limiting or document limitation"
})
# 3. Time manipulation
print("\n3. Time-based vulnerabilities:")
print(" - Current: Using Date.now() for timestamps")
print(" - Risk: System time changes could affect rate limiting")
print(" - Finding: Vulnerable to clock drift/manipulation")
self.findings.append({
"issue": "Clock manipulation",
"severity": "Low",
"description": "System time changes affect rate limiting",
"mitigation": "Use monotonic clock or accept as limitation"
})
# 4. No user identification
print("\n4. Client identification:")
print(" - Current: No client identification in stdio transport")
print(" - Risk: Cannot implement per-user limits")
print(" - Finding: All requests from one instance share limit")
self.findings.append({
"issue": "No client differentiation",
"severity": "Medium",
"description": "Cannot implement per-user or per-API-key limits",
"mitigation": "Document as stdio transport limitation"
})
# 5. Header injection
print("\n5. Response header security:")
print(" - Current: Rate limit info in error data field")
print(" - Risk: None - data is structured JSON")
print(" - Finding: Properly structured, no injection risk")
# 6. Denial of Service
print("\n6. DoS potential:")
print(" - Current: Synchronous rate limit check")
print(" - Risk: Minimal - check is O(n) where n is requests in window")
print(" - Finding: Could be optimized but not a security risk")
def research_bypass_techniques(self):
"""Research potential bypass techniques"""
print("\n=== Bypass Technique Analysis ===\n")
techniques = [
{
"name": "Parallel connections",
"method": "Open multiple MCP connections simultaneously",
"effectiveness": "High - each gets separate rate limit",
"mitigation": "Document limitation, consider process limits"
},
{
"name": "Request timing",
"method": "Time requests to maximize window usage",
"effectiveness": "Low - sliding window prevents this",
"mitigation": "Already mitigated by sliding window"
},
{
"name": "Error flooding",
"method": "Send malformed requests to avoid rate limit",
"effectiveness": "None - rate limit checked before parsing",
"mitigation": "Already mitigated"
},
{
"name": "Connection recycling",
"method": "Disconnect and reconnect to reset limit",
"effectiveness": "High - new instance gets new limit",
"mitigation": "Consider connection rate limiting"
}
]
for technique in techniques:
print(f"\nTechnique: {technique['name']}")
print(f"Method: {technique['method']}")
print(f"Effectiveness: {technique['effectiveness']}")
print(f"Mitigation: {technique['mitigation']}")
if technique['effectiveness'] in ['High', 'Medium']:
self.findings.append({
"issue": f"Bypass via {technique['name']}",
"severity": technique['effectiveness'],
"description": technique['method'],
"mitigation": technique['mitigation']
})
def research_stress_scenarios(self):
"""Define stress test scenarios for rate limiting"""
print("\n=== Stress Test Scenarios ===\n")
scenarios = [
{
"name": "Burst at limit",
"description": "Send exactly limit requests as fast as possible",
"expected": "All requests succeed, next one fails",
"tests": ["Rate limit accuracy", "Performance under load"]
},
{
"name": "Sustained at limit",
"description": "Send requests at exactly the allowed rate",
"expected": "All requests succeed indefinitely",
"tests": ["Sliding window accuracy", "Memory stability"]
},
{
"name": "Memory exhaustion",
"description": "Send limit-1 requests repeatedly",
"expected": "Memory usage should stay bounded",
"tests": ["Memory leak", "Cleanup effectiveness"]
},
{
"name": "Parallel connections",
"description": "Open 10 connections, each at limit",
"expected": "Each connection gets full rate limit",
"tests": ["Per-instance isolation", "System resource usage"]
},
{
"name": "Rapid reconnect",
"description": "Connect, use limit, disconnect, repeat",
"expected": "Each connection gets fresh limit",
"tests": ["Connection overhead", "Resource cleanup"]
},
{
"name": "Clock drift simulation",
"description": "Make requests while simulating clock changes",
"expected": "Rate limiting remains consistent",
"tests": ["Time manipulation resistance"]
}
]
print("Recommended stress test scenarios:")
for scenario in scenarios:
print(f"\n{scenario['name']}:")
print(f" Description: {scenario['description']}")
print(f" Expected: {scenario['expected']}")
print(f" Tests: {', '.join(scenario['tests'])}")
def generate_report(self):
"""Generate security findings report"""
print("\n=== Security Findings Summary ===\n")
high_severity = [f for f in self.findings if f['severity'] == 'High']
medium_severity = [f for f in self.findings if f['severity'] == 'Medium']
low_severity = [f for f in self.findings if f['severity'] == 'Low']
if high_severity:
print(f"High Severity Issues ({len(high_severity)}):")
for finding in high_severity:
print(f" - {finding['issue']}: {finding['description']}")
print(f" Mitigation: {finding['mitigation']}")
if medium_severity:
print(f"\nMedium Severity Issues ({len(medium_severity)}):")
for finding in medium_severity:
print(f" - {finding['issue']}: {finding['description']}")
print(f" Mitigation: {finding['mitigation']}")
if low_severity:
print(f"\nLow Severity Issues ({len(low_severity)}):")
for finding in low_severity:
print(f" - {finding['issue']}: {finding['description']}")
print(f" Mitigation: {finding['mitigation']}")
# Save findings to JSON
with open('research/rate-limiting-security-findings.json', 'w') as f:
json.dump({
'timestamp': time.strftime('%Y-%m-%d %H:%M:%S'),
'findings': self.findings,
'summary': {
'high': len(high_severity),
'medium': len(medium_severity),
'low': len(low_severity)
}
}, f, indent=2)
print(f"\nFindings saved to: research/rate-limiting-security-findings.json")
def main():
"""Run rate limiting security research"""
research = RateLimitingSecurityResearch()
# Run research
research.research_current_implementation()
research.research_bypass_techniques()
research.research_stress_scenarios()
research.generate_report()
print("\n=== Next Steps ===")
print("1. Create stress tests for identified scenarios")
print("2. Implement mitigations for high-severity issues")
print("3. Document limitations that cannot be fixed")
print("4. Add monitoring/alerting for rate limit bypasses")
if __name__ == "__main__":
main()