Runtime Agent-Payment Fraud Surveillance

W-E. Spend-policy violation detection (art-02) -> agent-network/collusion graph (mms-03) -> payment-velocity anomaly monitoring (ml-03). Runtime fraud surveillance over an autonomous agent's payment stream.

OpenChainGraph · 3 Steps risk control Hash-Anchored §4 chain_depth:3 Client-Side · Zero PII

Chain Stages · 3 Steps

1 ROOT · D0 node

Agent Spend-Policy Simulator art-02-agent-spend-policy-simulator

policy violations (H1) feed the graph engine

MCP Call · simulate_spend_policy

{
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "name": "simulate_spend_policy",
    "arguments": {}
  },
  "id": 1
}

↓

2 D2 node

APP Fraud Graph Simulator mms-03-app-fraud-graph

network red flags (H2) feed the anomaly detector

MCP Call · simulate_app_fraud_graph

{
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "name": "simulate_app_fraud_graph",
    "arguments": {}
  },
  "id": 1
}

↓

3 TERMINAL · D3 node

Time-Series Anomaly Detector ml-03-timeseries-anomaly-detector

Exports composite runtime-fraud artifact with execution_hash (H3) -- final stage

MCP Call · detect_timeseries_anomalies

{
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "name": "detect_timeseries_anomalies",
    "arguments": {}
  },
  "id": 1
}