from praisonaiagents import Agent, Task, PraisonAIAgents
import time
from typing import Dict, List
import asyncio
def analyze_cryptographic_scheme():
"""Simulates cryptographic scheme analysis"""
schemes = [
{
"name": "lattice_based",
"type": "encryption",
"key_size": 2048,
"security_level": "AES-256 equivalent",
"parameters": {
"lattice_dimension": 1024,
"modulus": "q = 2^32 - 1",
"error_distribution": "discrete_gaussian"
}
},
{
"name": "multivariate",
"type": "signature",
"key_size": 4096,
"security_level": "SHA-384 equivalent",
"parameters": {
"variables": 128,
"equations": 128,
"field_size": "2^8"
}
}
]
return schemes[int(time.time()) % 2]
def simulate_quantum_attacks(scheme: Dict):
"""Simulates quantum attack scenarios"""
attacks = {
"grover_search": {
"effectiveness": "reduced",
"quantum_speedup": "quadratic",
"estimated_qubits": 2048,
"time_complexity": "O(2^n/2)"
},
"shor_algorithm": {
"effectiveness": "ineffective",
"quantum_speedup": "none",
"vulnerability": "resistant",
"classical_hardness": "maintained"
},
"quantum_hidden_subgroup": {
"effectiveness": "partial",
"applicability": "limited",
"mitigation": "parameter_adjustment"
}
}
return attacks
def benchmark_performance(scheme: Dict):
"""Benchmarks cryptographic performance"""
benchmarks = {
"key_generation": {
"time": 0.5 + (time.time() % 1) / 10,
"memory": 128 + (int(time.time()) % 64)
},
"encryption_speed": {
"small_message": 0.001 + (time.time() % 1) / 1000,
"large_message": 0.1 + (time.time() % 1) / 10
},
"decryption_speed": {
"small_message": 0.002 + (time.time() % 1) / 1000,
"large_message": 0.15 + (time.time() % 1) / 10
},
"throughput": {
"encryption": 100 + (int(time.time()) % 50),
"decryption": 80 + (int(time.time()) % 40)
}
}
return benchmarks
def assess_implementation(scheme: Dict, benchmarks: Dict):
"""Assesses implementation security"""
assessment = {
"side_channel_resistance": {
"timing_attacks": "protected",
"power_analysis": "partial_vulnerability",
"cache_attacks": "mitigated"
},
"implementation_hardening": {
"constant_time": True,
"memory_protection": True,
"error_handling": "secure"
},
"compiler_optimizations": {
"safety": "verified",
"performance_impact": -0.05 + (time.time() % 1) / 10
}
}
return assessment
def validate_compliance(scheme: Dict, assessment: Dict):
"""Validates compliance and standards"""
compliance = {
"nist_pqc": {
"status": "submitted",
"round": 3,
"requirements_met": True
},
"common_criteria": {
"evaluation_level": "EAL4+",
"protection_profile": "compliant"
},
"fips_140_3": {
"security_level": 3,
"validation_status": "in_process"
}
}
return compliance
crypto_analyzer = Agent(
name="Crypto Analyzer",
role="Cryptographic Analysis",
goal="Analyze cryptographic schemes",
instructions="Evaluate quantum-resistant cryptographic schemes",
tools=[analyze_cryptographic_scheme]
)
attack_simulator = Agent(
name="Attack Simulator",
role="Attack Simulation",
goal="Simulate quantum attacks",
instructions="Test resistance against quantum attacks",
tools=[simulate_quantum_attacks]
)
performance_benchmarker = Agent(
name="Performance Benchmarker",
role="Performance Testing",
goal="Benchmark cryptographic performance",
instructions="Measure performance metrics",
tools=[benchmark_performance]
)
implementation_assessor = Agent(
name="Implementation Assessor",
role="Implementation Assessment",
goal="Assess implementation security",
instructions="Evaluate implementation security",
tools=[assess_implementation]
)
compliance_validator = Agent(
name="Compliance Validator",
role="Compliance Validation",
goal="Validate standards compliance",
instructions="Verify compliance with standards",
tools=[validate_compliance]
)
analysis_task = Task(
name="analyze_crypto",
description="Analyze cryptographic scheme",
expected_output="Cryptographic analysis",
agent=crypto_analyzer,
is_start=True,
next_tasks=["simulate_attacks", "benchmark_performance"]
)
attack_task = Task(
name="simulate_attacks",
description="Simulate quantum attacks",
expected_output="Attack simulation results",
agent=attack_simulator,
next_tasks=["assess_implementation"]
)
benchmark_task = Task(
name="benchmark_performance",
description="Benchmark performance",
expected_output="Performance benchmarks",
agent=performance_benchmarker,
next_tasks=["assess_implementation"]
)
assessment_task = Task(
name="assess_implementation",
description="Assess implementation",
expected_output="Implementation assessment",
agent=implementation_assessor,
context=[attack_task, benchmark_task],
next_tasks=["validate_compliance"]
)
compliance_task = Task(
name="validate_compliance",
description="Validate compliance",
expected_output="Compliance validation",
agent=compliance_validator,
task_type="decision",
condition={
"compliant": "",
"non_compliant": ["assess_implementation"]
}
)
workflow = PraisonAIAgents(
agents=[crypto_analyzer, attack_simulator, performance_benchmarker,
implementation_assessor, compliance_validator],
tasks=[analysis_task, attack_task, benchmark_task,
assessment_task, compliance_task],
process="workflow",
verbose=True
)
async def main():
print("\nStarting Quantum-Resistant Cryptography Validation Workflow...")
print("=" * 50)
results = await workflow.astart()
print("\nCryptography Validation Results:")
print("=" * 50)
for task_id, result in results["task_results"].items():
if result:
print(f"\nTask: {task_id}")
print(f"Result: {result.raw}")
print("-" * 50)
if __name__ == "__main__":
asyncio.run(main())