Summary
This website contacted 2 IPs in 2 countries across 2 domains to perform 2 HTTP transactions. The main domain is 1001crash.com and was registered NaN years ago.
Submitted URL: https://www.1001crash.com/transport-page-tenerife-lg-2-numpage-2.html
AI Security Verdict
Low Risk
Confidence: 80%
The site appears to be a legitimate informational page with no phishing or malware indicators, but the unranked domain and IP threat‑intel match suggest moderate caution.
Risk Factors
Safety Factors
Details
Page Title
The Tenerife disaster - Two Boeing 747 collided - 1001 Crash
Scan Type
public
Language
English
Category
unknown
(0%)Domain Information
The domain name 'www.1001crash.com' uses the commercial generic top-level domain (.com) with subdomain 'www'. Count 9 characters in '1001crash' holding one vowel versus 4 consonants, along with four digits. Segmentation suggests 2 words: 1001, crash. Average segment length settles at 4.5 characters. 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 |
|---|---|---|---|
| 14 | 213.186.33.19 | France | AS16276OVH SAS |
| 13 | 142.251.110.132Google · CDN | United States | AS15169Google LLC |
| 27 | 2 | - | - |
Detected Technologies3
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