Security Scan Report: mol.gov.qa

Redirected to: https://www.mol.gov.qa/ar/pages/default.aspx

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Submitted: Feb 25, 2026, 3:19:09 AMCompleted: Feb 25, 2026, 3:20:51 AMpubliccompleted
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Summary

This website contacted 4 IPs in 1 country across 6 domains to perform 1 HTTP transaction. The main domain is mol.gov.qa.

Submitted URL: https://mol.gov.qa

Effective URL: https://www.mol.gov.qa/ar/pages/default.aspxRedirected

The Cisco Umbrella rank of the primary domain is #859,726 of the top 1 million websites

AI Security Verdict

Safe Website

Confidence: 92%

1
Risk Score

Legitimate government site with no malicious indicators detected.

Safety Factors
HTTPS connection
Official government domain (mol.gov.qa)
No suspicious redirects or URL manipulation
No cross‑origin credential submissions
Domain age information unavailable

Details

Page Title

الرئيسية | وزارة العمل

Scan Type

public

Language

🇸🇦

Arabic

(80% confidence)

Category

government public service

(98%)

Domain Information

You're looking at domain 'mol.gov.qa' on the Qatari country-code top-level domain (.gov.qa) and has no subdomain. The registrable portion 'mol' spans 3 characters split between one vowel and two consonants. Tokenizing the label suggests 1 word: mol. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://mol.gov.qa

Page Load Overview

9.45s
Total Load Time
141
HTTP Requests
7
Domains
3.2 MB
Total Size

Language Analysis

Primary Language

🇸🇦Arabic
Code: ar
Confidence:80%
Script:Arabic
Direction:rtl

Detection Details

Language Code:ar
Detection Confidence:80%
Script Type:Arabic
HTML Lang Attribute:ar-QA
Text Length:13,540 chars
Detector Agreement:75%

Website Classification

Primary Category

government public service98% confidence
Type: spa
Method: ml+structural

All Detected Categories

government public service
98%
corporate business
96%
technology software
77%
news media journalism
72%
adult content
59%

Detected Features

Search

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
3613.107.213.44Netherlands
35151.101.193.229Netherlands
35172.217.168.72Netherlands
3551.105.107.140Amsterdam, North Holland, Netherlands
AS8075Microsoft Corporation
1414--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1CD34526105F4687B00A395E1AE72AF4AAFE1E937C60B5E0072ED0B941FD3F469D1722D

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

3072:/kR5y2VuMr83/9os4VJeLyKVqXJzBmDdNri0f0AXFZulqIoqoZMwKTTjaXYA51ca:3UU0AXF2qIoqoZMw+jaXYA51b

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:249089:HhCEgCKdmFJIAQABAlgCgJBUrAhUagFQmGcg9EhBMxKWgA4JBIhSCAIZATJY+/jELYLA3EAFiBwwIBFFejG1swIAAhQgJCAp

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:ff247e7e7e7e7e7e
Perceptual Hash:d5eaabfaada081c0
Difference Hash:02ccd4d4d4d4d4d4
Wavelet Hash:ff003c547e5c5c54
Color Hash:#40bfa2

Scan History

Scan history not available

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