Summary
This website contacted 3 IPs in 2 countries across 4 domains to perform 2 HTTP transactions. The main domain is seom.org and was registered NaN years ago.
Submitted URL: https://seom.org/informacion-sobre-el-cancer/que-es-el-cancer-y-como-se-desarrolla
AI Security Verdict
Low Risk
Confidence: 82%
Legitimate medical society site with a member login; no malicious signals detected.
Safety Factors
Details
Page Title
¿Qué es el cáncer y cómo se desarrolla? - SEOM: Sociedad Española de Oncología Médica © 2019
Scan Type
public
Language
Spanish
Category
healthcare medical
(65%)Domain Information
The domain name 'seom.org' uses the non-profit oriented generic top-level domain (.org). The core label 'seom' covers 4 characters holding two vowels versus two consonants. Tokenizing the label suggests 2 words: seo, m. Expect two 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 |
|---|---|---|---|
| 24 | 192.178.183.97Google · CDN | United States | AS15169Google LLC |
| 23 | 142.251.156.119Google · CDN | United States | AS15169Google LLC |
| 23 | 46.231.127.114 | Spain | AS42612DinaHosting S.L. |
| 70 | 3 | - | - |
Detected Technologies9
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