Summary
This website contacted 2 IPs in 2 countries across 2 domains to perform 2 HTTP transactions. The main domain is globalwirepress.com and was registered NaN years ago.
Submitted URL: https://globalwirepress.com/scam-alerts/darren-anthony-robinson-investment-fraud-98666f
AI Security Verdict
Low Risk
Confidence: 85%
The page appears to be a legitimate news article with no phishing or malware indicators.
Safety Factors
Details
Page Title
FBI Wanted: Darren Anthony Robinson — White-Collar Crime — GlobalWire Press
Scan Type
public
Language
English
Category
corporate
(70%)Domain Information
Domain 'globalwirepress.com' uses the commercial generic top-level domain (.com). Its registrable label 'globalwirepress' stretches across 15 characters containing five vowels alongside 10 consonants. Segmentation suggests 3 words: global, wire, press. Expect five characters per word on average. No strong language cues emerged from the frequency lists.
Screenshot

Page Load Overview
Language Analysis
Primary Language
Detection Details
Website Classification
Primary Category
All Detected Categories
Detected Features
Domain & IP Information
| Requests | IP Address | Location | AS Autonomous System |
|---|---|---|---|
| 12 | 185.158.133.1 | Frankfurt am Main, Hesse, Germany | AS13335Cloudflare, Inc. |
| 11 | 142.251.110.95Google · CDN | United States | AS15169Google LLC |
| 23 | 2 | - | - |
Page Statistics
Detected Technologies4
Content Similarity HashesFor malware variant detection
TLSH (Trend Micro Locality Sensitive Hash)
Specialized for malware detection and similarity analysis
ssdeep (Context Triggered Piecewise Hashing)
Detects similar content even with modifications
sdhash (Similarity Digest Hashing)
High-precisionHigh-precision similarity detection for forensic analysis
These hashes enable detection of similar websites and malware variants by comparing content similarity even when exact matches aren't found.
Image Hashes
Perceptual Hashes
Other Hashes
Scan History
Scan history not available
Unable to load historical scan data