Map connections between domains, wallets, phones, and Telegram channels. Detect fraud campaigns, propagate risk, and visualize attack networks.
14 entity types (domain, wallet, phone, email, Telegram, etc.) connected by 13 relationship types.
Automatic grouping of related threats into campaigns. Track campaign evolution over time.
When one entity is flagged, risk automatically propagates to all connected entities in the graph.
Algorithmic detection of fraud networks. Identify clusters of coordinated scam operations.
Graph data formatted for D3.js/vis.js. Build interactive network maps in your UI.
Traverse the graph up to 5 hops deep. Find hidden connections between seemingly unrelated entities.
Begin from any entity: domain, wallet, phone, email, or Telegram channel.
System explores connections up to specified depth, discovering related entities and relationships.
Entities are grouped into clusters. Campaigns are identified from correlated threat patterns.
Get node/edge data for visualization, campaign summary, high-risk entities, and risk scores.
/api/v3/graph/investigateRequest
{
"start_entity": {
"type": "domain",
"value": "privatbank-ua.xyz"
},
"depth": 3,
"include_campaigns": true
}Response
{
"nodes": 28,
"edges": 41,
"clusters": 3,
"campaigns": [{
"id": "camp_001",
"name": "PrivatBank Phishing Wave",
"risk_score": 94,
"members": 15
}],
"high_risk_entities": 8,
"graph": { "nodes": [...], "edges": [...] }
}14
Entity types
13
Relation types
D3.js
Viz engine
∞
Max depth
Map the connections. Find the operators. Stop the campaigns.
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