Security Scan Report: escortsabahsarawak.pages.dev

Redirected to: https://escortsabahsarawak.pages.dev/lawas-escort

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Submitted: Jan 28, 2026, 4:25:27 AMCompleted: Jan 28, 2026, 4:27:01 AMpubliccompleted
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Summary

This website contacted 2 IPs in 1 country across 2 domains to perform 1 HTTP transaction. The main domain is escortsabahsarawak.pages.dev and was registered NaN years ago.

Submitted URL: https://escortsabahsarawak.pages.dev/lawas-escort.html

Effective URL: https://escortsabahsarawak.pages.dev/lawas-escortRedirected

AI Security Verdict

Safe Website

Confidence: 95%

0
Risk Score

No security threats detected; site appears legitimate.

Safety Factors
HTTPS connection
No credential or payment forms present
No malicious Indicators of Compromise detected
Domain age information unavailable

Details

Page Title

Outcall Escort Girls Lawas Sabah

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

unknown

(0%)

Domain Information

Within the developer-focused generic top-level domain (.dev), 'escortsabahsarawak.pages.dev' is registered with subdomain 'escortsabahsarawak'. Count 5 characters in 'pages' split between two vowels and 3 consonants. It segments into one word: pages. Median word length comes out to 5 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://escortsabahsarawak.pages.dev/lawas-escort.html

Page Load Overview

5.16s
Total Load Time
178
HTTP Requests
3
Domains
2.7 MB
Total Size

Language Analysis

Primary Language

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

Detection Details

Language Code:en
Detection Confidence:80%
Script Type:Latin
HTML Lang Attribute:en
Text Length:2,642 chars
Detector Agreement:80%

Website Classification

Primary Category

unknown0% confidence
Type: dynamic
Method: structural

All Detected Categories

No categories detected

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
89172.66.47.191United States
AS13335Cloudflare, Inc.
89216.58.206.40United States
1782--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T18432C622A640B137065292E87235B71DA7C7C273FB22499261F91F5C0B53F8B8C7288B

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

96:1KgiU/x/8cEi1z2BQoF4ky6JNtGS81Sa6SZDSNMPsqu+krFUVX1Dt7iev36WQEz+:1KgpDXo4kNppTgU8S+vN1tmW9kLHnx/R

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:11583:CBAxUicEEwKXAWwgk4AChFsECYCygrSJhCAiVgioQrAAtRgOGoxnXgQAAAgkDY45DDwAAhHUjZEAYrTASASEIgPAQAABBQiW

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:ff0000dfcfcf8787
Perceptual Hash:be4146b9b29ec34c
Difference Hash:6cb1c1383e1e2e2e
Wavelet Hash:230000dfcfcf8fc7
Color Hash:#d22d9b

Scan History

Scan history not available

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