Security Scan Report: natalie.mu

Bot Protection Detected

This website is protected by AWS WAF bot protection. The page may show differently for regular users.

Submitted: Oct 11, 2026, 4:50:50 AMCompleted: Oct 11, 2026, 4:51:37 AMpubliccompleted

This website contacted 12 IPs in 2 countries across 4 domains to perform 13 HTTP transactions. The main domain is natalie.mu and was registered 11 years ago.

Submitted URL: https://natalie.mu

The Cisco Umbrella rank of the primary domain is #775,438 of the top 1 million websites

AI Security Verdict

Safe Website

Confidence: 80%

1
Risk Score

AWS WAF human-verification page on the 20-year-old Japanese site natalie.mu. No credentials, payment fields, brand impersonation or malicious indicators; classifier phishing label is a CAPTCHA false positive.

Safety Factors (4)
Domain established for ~20 years with continuous registration
Challenge page is Google/AWS-style anti-bot verification, with no credential or payment collection
No threat-intelligence, YARA, IDS or behavioral malicious signals
Cross-origin requests limited to the CAPTCHA provider's own infrastructure
Domain age information unavailable

Details

Page Title

Human Verificationother network

Scan Type

public

Domain Name Analysis

The domain name 'natalie.mu' uses the Mauritian country-code top-level domain (.mu) without a subdomain. Count 7 characters in 'natalie' containing four vowels alongside three consonants. Splitting it apart reveals one word: natalie. Median word length is 7 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://natalie.mu

Page Load Overview

9.83s
Total Load Time
507 KB
Total Size

Language Analysis

Primary Language

🇺🇸English
Code: en
Confidence:80%
Script:Latin
Direction:ltr

Detection Details

HTML Lang Attribute:en
Text Length:651 chars
Detector Agreement:67%

Website Classification

Primary Category

documentation technical72% confidence
Type: static
Method: ml+structural+ocr_tiebreaker

All Detected Categories

documentation technical
72%
phishing scam
68%
finance banking
55%
adult content
41%
news media journalism
39%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
213.193.6.236Aws · CLOUDTokyo, Tokyo, Japan
AS16509Amazon.com, Inc.
118.66.122.111Cloudfront · CDNUnited States
AS16509Amazon.com, Inc.
199.84.152.126Cloudfront · CDNUnited States
AS16509Amazon.com, Inc.
165.8.131.119Cloudfront · CDNUnited States
AS16509Amazon.com, Inc.
118.179.100.228Aws · CLOUDTokyo, Tokyo, Japan
AS16509Amazon.com, Inc.
118.66.122.78Cloudfront · CDNUnited States
AS16509Amazon.com, Inc.
199.84.152.75Cloudfront · CDNUnited States
AS16509Amazon.com, Inc.
165.8.131.123Cloudfront · CDNUnited States
AS16509Amazon.com, Inc.
118.66.122.121Cloudfront · CDNUnited States
AS16509Amazon.com, Inc.
118.66.122.25Cloudfront · CDNUnited States
AS16509Amazon.com, Inc.
1312--

Detected Technologies3

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T14912F85368264407905B189DAA73A24D768AC207810E88DDFFAF5BF4CFDF6BC412369C

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

192:CJGfbp4UD1wCF+qaLv0X2ZzUhfOFgTm0DKDnBQfmW1qaRCVXUuziEsmw9oj:yBaff9wnBi31qaRcFG4wc

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:9567:7MeIhY6pY5YnACBMATAgeJlARSNPEAQEHgTURR1EFBRVREOS6gJVKcACZBiBQiChAB4IlAYKkgicEQIZR9c8ZQBQCBJBQMCS

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:e6e6e6eefefefefe
Perceptual Hash:f73322cc8ccca633
Difference Hash:0c0c0c0800000000
Wavelet Hash:262626260e0e0e0e
Color Hash:#2dd29e

Other Hashes

Crop Resistant:0c0c0c0800000000

Scan History

Scan history not available

Unable to load historical scan data