Security Scan Report: deborahthessem.pages.dev

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Submitted: Jan 8, 2026, 11:11:56 PMCompleted: Jan 8, 2026, 11:13:18 PMpubliccompleted
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Summary

This website contacted 14 IPs in 3 countries across 16 domains to perform 61 HTTP transactions. The main domain is deborahthessem.pages.dev and was registered NaN years ago.

Submitted URL: https://deborahthessem.pages.dev/kqgio-social-security-for-2025-increase-haaah/

AI Security Verdict

High Risk

Confidence: 85%

7
Risk Score

Site mimics Social Security on an unrelated domain; likely a phishing page.

Risk Factors
Brand impersonation of Social Security on a non‑official domain
Unranked/low‑reputation domain used for government‑related content
Presence of a form (potential data collection) despite no credential fields
Domain age information unavailable

Details

Page Title

Social Security For 2025 Increase - Irena Lyndsie

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

government public service

(48%)

Domain Information

Domain 'deborahthessem.pages.dev' uses the developer-focused generic top-level domain (.dev) with subdomain 'deborahthessem'. The registrable portion 'pages' spans 5 characters holding 2 vowels versus three consonants. Tokenizing the label suggests one word: pages. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://deborahthessem.pages.dev/kqgio-social-security-for-2025-increase-haaah/

Page Load Overview

8.77s
Total Load Time
57
HTTP Requests
16
Domains
895 KB
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-US
Text Length:3,497 chars
Detector Agreement:100%

Website Classification

Primary Category

government public service48% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

government public service
48%
adult content
47%
news media journalism
41%
healthcare medical
30%
news/blog
20%

Detected Features

Comments
OG: article
Schema.org

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
591.108.107.115Mumbai, Maharashtra, India
AS47583Hostinger International Limited
4192.0.73.2San Francisco, California, United States
AS2635AUTOMATTIC
4104.17.158.22United States
AS13335CLOUDFLARENET
4104.19.154.92United States
AS13335CLOUDFLARENET
4104.20.23.96United States
AS13335CLOUDFLARENET
492.204.80.11Strasbourg, Grand Est, France
AS21499Host Europe GmbH
4150.171.28.10United States
AS8075MICROSOFT-CORP-MSN-AS-BLOCK
4172.66.47.198United States
AS13335CLOUDFLARENET
4172.217.23.118UnknownUnknown
4188.114.96.3UnknownUnknown
5714--

Detected Technologies13

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1F123183254DD053B6A5F53CEE5A1B31CE9AAAA11CA034E2773FC22686FC0EF6446314D

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

768:yHCwC2CRCnnLZdapzq/FrAZkLRWL74mSTIZHDdN2sedAxLZACHedFUOPR9SEMrwQ:yHCwC2CRCn7ap5ETIJDdN2sMyOCHevRU

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:47619:AcJjigkosN4oIA3nAgThQMYGIxQoCgMEO4CCT8iUGiIBgCqDgFNAUXBJ5IccoESWCEAApMKw4AME5BQRUiCZ1SAaSg1IwomM

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:ff0000ffffffc7c7
Perceptual Hash:b24f30cdcfb0c532
Difference Hash:0cc1cd32328f8f8f
Wavelet Hash:ef0000bf8fc3c3c7
Color Hash:#d2cd2d

Scan History

Scan history not available

Unable to load historical scan data