/api/anomaly_graph

Header

POST https://api.Fluxrails.app/api/v1/ai/anomaly_graph
X-Customer-Api-Id: <uuid>
X-Secret: <secret>
Content-Type: application/json

Request Body Schema

// Request Body Schema
{
  "contamination": number,   // fraction of nodes to flag (0–1)
  "edges": [
    {
      "src": "string",        // origin node ID
      "dst": "string",        // destination node ID
      "weight": number|null   // optional interaction strength (default=1)
    }
  ]
}

Example Request Body

// Example Request Body
{
  "contamination": 0.10,
  "edges": [
    { "src": "acct-001", "dst": "acct-002", "weight": 1 },
    { "src": "acct-002", "dst": "acct-003", "weight": 1 },
    { "src": "acct-003", "dst": "acct-004", "weight": 5 },
    { "src": "acct-003", "dst": "acct-005", "weight": 4 },
    { "src": "acct-004", "dst": "acct-006", "weight": 3 },
    { "src": "acct-004", "dst": "acct-007", "weight": 3 },
    { "src": "acct-004", "dst": "acct-008", "weight": 3 },
    { "src": "acct-002", "dst": "acct-008", "weight": 1 },
    { "src": "acct-007", "dst": "acct-001", "weight": 1 }
  ]
}

Example Response Body

// Example Response Body
{
  "details": [
    { "node": "acct-001", "anomaly_score": 2.0,  "flag": false },
    { "node": "acct-002", "anomaly_score": 3.0,  "flag": false },
    { "node": "acct-003", "anomaly_score": 10.0, "flag": false },
    { "node": "acct-004", "anomaly_score": 14.0, "flag": true },
    { "node": "acct-005", "anomaly_score": 4.0,  "flag": false },
    { "node": "acct-006", "anomaly_score": 3.0,  "flag": false },
    { "node": "acct-007", "anomaly_score": 4.0,  "flag": false },
    { "node": "acct-008", "anomaly_score": 4.0,  "flag": false }
  ],
  "interpretation": "1 nodes flagged (threshold 11.20, contamination=0.1)."
}

Description

• Flags the top-N most connected “hub” nodes in any undirected interaction graph. • Computes each node’s weighted degree (sum of edge weights) and marks the top `contamination` fraction. • Returns per-node `anomaly_score` and boolean `flag`. • Provides a human summary of how many nodes crossed the threshold.

Business Usage

• Submit device↔account, IP↔email, wallet↔merchant edge lists to catch mule-account rings or botnet controllers. • Sort `details` by `anomaly_score` to investigate the most over-connected nodes first. • Adjust `contamination` for stricter (e.g. 0.02) or broader (e.g. 0.20) review scopes. • Enrich edge weights with transaction counts or data volumes for finer-grained detection. • Combine with `/api/anomaly_accounts` to blend graph-based signals with profile anomalies.

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