graph TD
A[企业办公网络] --> B(IP隔离网关)
B --> C{智能调度引擎}
C --> D[住宅IP池]
C --> E[云服务商IP池]
C --> F[移动基站IP池]
G[业务终端] -->|RDP over TLS| B

# 谷咕云动态路由脚本（v3.2）
#!/bin/bash
AWS_REGION=$(curl -s 169.254.169.254/latest/meta-data/placement/region)
IP_POOL_SELECTOR --region=$AWS_REGION \
                 --protocol=tcp_udpc_mix \
                 --bandwidth=50M \
                 --session_ttl=1800
iptables -t nat -A POSTROUTING -o eth0 -j MASQUERADE --random

class ConsumptionSimulator:
    def __init__(self, business_type):
        self.pattern = load_business_profile(business_type)
        self.credits = CreditManager()
    
    def generate_traffic(self):
        while True:
            # 基于马尔可夫链的状态转移模型
            current_state = self.pattern.get_state()
            action = self.policy_network.predict(current_state)
            execute_aws_action(action)
            self.credits.adjust(action.cost)
            time.sleep(self.pattern.get_interval())

graph LR
A[营业执照扫描件] --> B(OCR识别引擎)
B --> C[工商数据库核验]
D[对公账户凭证] --> E(数字签名验证)
E --> F[SWIFT流水分析]
G[法人身份证明] --> H(活体检测+Liveness检测)
H --> I[跨库身份比对]
C --> J{综合评分}
F --> J
I --> J
J --> K[资质档案生成]

class RiskEarlyWarning:
    def __init__(self):
        self.aws_health = AWSHealthMonitor()
        self.credit_flow = CreditAnalyzer()
    
    def monitor(self):
        while True:
            risk_score = 0.4 * self.aws_health.get_risk() + \
                          0.6 * self.credit_flow.get_anomaly()
            if risk_score > 0.75:
                self.trigger_failover()
                self.rotate_credentials()
            time.sleep(300)  # 5分钟检测周期