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Security Scan Report: nanibneilla.pages.dev

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Submitted: Dec 27, 2025, 8:33:34 PMCompleted: Dec 27, 2025, 8:33:53 PMpubliccompleted
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Summary

This website contacted 13 IPs in 1 country across 15 domains to perform 56 HTTP transactions. The main domain is nanibneilla.pages.dev and was registered NaN years ago.

Submitted URL: https://nanibneilla.pages.dev/edvgvbg-social-security-payment-schedule-2024-dates-and-times-photos-pebwiqj/

AI Security Verdict

Moderate Risk

Confidence: 70%

5
Risk Score

Potential phishing site impersonating Netflix; limited malicious activity detected.

Risk Factors
Brand impersonation on a generic hosting subdomain
Unranked domain combined with brand misuse
Social‑security‑related content that may be used for credential harvesting
Safety Factors
Domain age > 5 years (well‑established)
No password, email, or payment fields in the form
No malicious Indicators of Compromise matches found
Domain age information unavailable

Details

Page Title

Social Security Payment Schedule 2024 Dates And Times - Mira Pauletta

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

entertainment media

(98%)

Domain Information

The domain name 'nanibneilla.pages.dev' uses the developer-focused generic top-level domain (.dev), featuring subdomain 'nanibneilla'. The second-level label 'pages' is 5 characters long containing two vowels alongside 3 consonants. Tokenizing the label suggests 1 word: pages. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://nanibneilla.pages.dev/edvgvbg-social-security-payment-schedule-2024-dates-and-times-photos-pebwiqj/

Page Load Overview

5.89s
Total Load Time
56
HTTP Requests
0
Domains
N/A
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:3,066 chars
Detector Agreement:100%

Website Classification

Primary Category

entertainment media98% confidence
Type: dynamic
Method: ml+structural+ocr_tiebreaker

All Detected Categories

entertainment media
98%
education learning
92%
news media journalism
81%
travel tourism
49%
gambling betting
47%

Detected Features

Search
Articles
OG: article
Schema.org

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
23172.66.45.10United States
AS13335CLOUDFLARENET
5172.240.108.84UnknownUnknown
2104.20.23.96United States
AS13335CLOUDFLARENET
1142.250.184.225UnknownUnknown
1192.0.77.2UnknownUnknown
1104.16.150.108UnknownUnknown
1150.171.28.10UnknownUnknown
1209.59.168.98UnknownUnknown
146.229.172.197UnknownUnknown
1108.167.156.41UnknownUnknown
013--

Detected Technologies5

WordPressv6.5.5
100%
Open-Graph-Protocolvarticle
100%
MetaGenerator
100%
JQueryv3.7.1
100%
Bootstrapv6.5.5
100%

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1B5133933D15914373A5F93FCE4A0BB2DA965E720CA035E6676F8B054AF80DF64523A0E

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

768:pZdapHZT4ZDDs4AmoWALthOUNQjetJt5E:Zap5T4hDs4DoWAVQjetJt5E

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:45395:KEKB2AEDjBeKlilAAQQAtAdSCMkEhS6AhSPC3AcyQmhJggo1GhgwgiYhPJUBAAB12CAoAFgUSRWEBBERFhgv1C1RiBIIQGkH

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:00ff978787878707
Perceptual Hash:be41417d2f2a2e2e
Difference Hash:ce706d5d5d4d5d4d
Wavelet Hash:00ff878787878787
Color Hash:#931f36

Other Hashes

Crop Resistant:ce706d5d5d4d5d4d,0000000000000000

Scan History

Scan history not available

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