ScanMalware.com

Security Scan Report: icann.github.io

Submitted: Dec 4, 2025, 7:39:41 AMCompleted: Dec 4, 2025, 7:40:59 AMpubliccompleted

Summary

API
This view is built from:
Scan result: counts, verdicts, details, IPs, technologies, hashes/api/v1/result/32d672f6-0f2b-4f17-9fee-98037eddf29aDomain and IP registration (RDAP)/api/v1/rdap/32d672f6-0f2b-4f17-9fee-98037eddf29aCertificate Transparency/api/v1/ct/icann.github.ioHow often this domain was scanned/api/v1/domain/stats/icann.github.ioScan history for this domain/api/v1/domain/history/icann.github.io?limit=15

This website contacted 8 IPs in 1 country across 1 domain to perform 1 HTTP transaction. The main domain is icann.github.io and was registered 13 years ago.

Submitted URL: https://icann.github.io/

The Cisco Umbrella rank of the primary domain is #621,173 of the top 1 million websites

AI Security Verdict

Safe Website

Confidence: 95%

0
Risk Score

Legitimate 404 page on GitHub Pages; no security concerns.

Safety Factors
Well‑established domain
Standard GitHub Pages hosting
No forms or data collection
No malicious Indicators of Compromise
Domain age information unavailable

Details

Page Title

Site not found · GitHub Pagessecondary capture

Scan Type

public

Domain Name Analysis

The domain 'icann.github.io' uses the British Indian Ocean Territory country-code top-level domain (.io); it also runs on subdomain 'icann'. Count 6 characters in 'github' with two vowels and 4 consonants. Tokenizing the label suggests three words: g, it, hub. Median word length comes out to 2 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://icann.github.io/

Page Load Overview

0.13s
Total Load Time
5 KB
Total Size

Language Analysis

Primary Language

🇺🇸English
Code: en
Confidence:56%
Script:Latin
Direction:ltr

Detection Details

Text Length:250 chars
Detector Agreement:100%

Website Classification

Primary Category

documentation technical38% confidence
Type: static
Method: ml+structural

All Detected Categories

documentation technical
38%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
1185.199.109.153San Francisco, California, United States
AS54113FASTLY
02606:50c0:8003::153United States
AS54113FASTLY
0185.199.110.153United States
AS54113FASTLY
02606:50c0:8002::153United States
AS54113FASTLY
0185.199.108.153United States
AS54113FASTLY
0185.199.111.153United States
AS54113FASTLY
02606:50c0:8000::153United States
AS54113FASTLY
02606:50c0:8001::153United States
AS54113FASTLY
18--

Detected Technologies2

GitHub Pages
40%
Fastly
40%

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1B2126D7E19E93308D8028A1539B267993D65480F9E866E6EB9AD1351CF8FE10E1637CC

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

192:Z5wnb1iC9OA9XXMa9kukrALQDUnulGVopLAGCALQD6vnglET31iCLL3Z:ZeB8H3DUulGmmv3D6vglETliCfJ

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:9101:D0JABgEkGzS0q4xQ4k6ELXuIwDBSMm4MgATNQSAQgiYJUAoHzDEIMiCQESALE+xLNjxWggFohi2EgAzCSCZgYBxIg8SdCFvi

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

Average Hash:e7e7e781c3e7ff00
Perceptual Hash:a6f603d528dd09d9
Difference Hash:0c4c962f174c0841
Wavelet Hash:e7e7c38181e7e700
Color Hash:#3a7778

Other Hashes

Crop Resistant:0c4c962f174c0841

Scan History

Scan history not available

Unable to load historical scan data