Original scam intelligence reports
Independent, data-driven analysis of global scam trends. Every report is based on ScamLens proprietary data from 90+ threat intelligence sources, peer-reviewed by our expert team, and published with full methodology disclosure.
Q1 2026 Global Scam Intelligence Report
Comprehensive analysis of global scam landscape: top 10 scam categories by volume and victim losses, cryptocurrency laundering pattern evolution, AI-generated scam detection rates, and country-by-country threat comparison. Based on 50M+ domain records and community intelligence.
Executive Summary
5 key findings that define the current global scam landscape
Global Threat Landscape
Regional breakdown: scam volume, victim demographics, loss distribution
Top 10 Scam Categories
Ranked by volume and financial impact, with trend comparison
Cryptocurrency Laundering Patterns
On-chain analysis of mixer evolution, peel chain tactics, cross-chain bridges
AI-Generated Scam Detection
How deepfakes, voice clones, and AI-written phishing are changing the threat model
Methodology & Data Sources
Full disclosure of data collection, scoring, and analytical methods
Published Reports
Q1 2026 Global Scam Intelligence Report
3.1M+ threat records, TLD abuse analysis, crypto fraud patterns, AI-generated scam trends. Based on 90+ sources.
Research integrity
- Every report published with full methodology and data source disclosure
- Expert-reviewed by named security researchers with verifiable credentials
- Raw datasets available for academic and research use (upon request)
- Corrections published within 48 hours of verified error reports
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