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Security Scan Report: natedaleyr.pages.dev

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Submitted: Completed: publiccompleted

Summary

API
This view is built from:
Scan result: counts, verdicts, details, IPs, technologies, hashes/api/v1/result/a99d8138-bd04-4d3a-9ab1-eb10b435afbfDomain and IP registration (RDAP)/api/v1/rdap/a99d8138-bd04-4d3a-9ab1-eb10b435afbfHow often this domain was scanned/api/v1/domain/stats/natedaleyr.pages.devScan history for this domain/api/v1/domain/history/natedaleyr.pages.dev?limit=15
This website contacted 9 IPs in 1 country across 9 domains to perform 28 HTTP transactions. The main domain is pages.dev and was registered 6 years ago.

Submitted URL: https://natedaleyr.pages.dev/yvbsl-social-security-payment-schedule-may-2025-pdf-rcmdn/

AI Security Verdict

High Risk

Confidence: 95%

7
Risk Score

High risk phishing site due to malicious primary domain pages.dev.

Risk Factors (3)
Primary domain pages.dev matches malicious Indicators of Compromise
Unranked/low reputation domain in Cisco Umbrella
Threat intelligence classifies the site as clearfake (malicious)
Domain age information unavailable

Details

Page Title

Social Security Payment Schedule May 2025 Pdf - Nate Daley

Scan Type

public

Domain Name Analysis

You're looking at domain 'natedaleyr.pages.dev' on the developer-focused generic top-level domain (.dev) and includes subdomain 'natedaleyr'. The core label 'pages' covers 5 characters containing 2 vowels alongside 3 consonants. Breaking it apart gives 1 word: pages. The median word length lands at five characters. No strong language cues emerged from the frequency lists.

Screenshot

Jan 18, 2025 Nate Daley Discover and explore ideas, tips guide and info Nate Daley. [Nome MMM Abou MMEContact MMM Disclaimer MME OMCAMMEM Privacy Policy MMETermatand Conditions) Blog Social Securi...

Page Load Overview

10.61s
Total Load Time
918 KB
Total Size

Language Analysis

Primary Language

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

Detection Details

HTML Lang Attribute:en-US
Text Length:3,094 chars
Detector Agreement:100%

Website Classification

Primary Category

government public service47% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

government public service
47%
healthcare medical
42%
corporate
35%
adult content
33%
finance banking
32%

Detected Features

Search
Articles
OG: website
Schema.org

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
18172.66.44.235United States
AS13335CLOUDFLARENET
2150.171.28.10UnknownUnknown
2104.21.69.200United States
AS13335CLOUDFLARENET
1172.66.169.241UnknownUnknown
1172.240.127.244UnknownUnknown
1142.250.184.225UnknownUnknown
1104.20.23.96United States
AS13335CLOUDFLARENET
1209.59.168.98UnknownUnknown
1142.251.141.97UnknownUnknown
09--

Detected Technologies5

WordPressv6.4.3
100%
Open-Graph-Protocolvwebsite
100%
MetaGenerator
100%
JQueryv3.7.1
100%
Bootstrapv1.0.0
100%

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T150E2D732A0AD10377E9F93EC81A17318EA9DE511CA039B3975FC31949F91EFA01AB15D

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

768:kTbZdapNLTWZgM/O8h5IBaITij43kF6TiU7QjIZ5WJ:Gap5TWOM/baB4j486TiU7QjIrWJ

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:34123:BkiOYCaCgQvsgEqRBjMCAgECJRKofkAAoBNiYgACJLRkAJAIhoYQCyeAADSeFoGhJRCSiJgwIE0FrsBMBSsS2EEcogzExIQC

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:ff0000ffffc787cf
Perceptual Hash:b84736b4cdb2cd0c
Difference Hash:084d730b321f1f1e
Wavelet Hash:e70019fbcbc383c3
Color Hash:N/A

Other Hashes

Crop Resistant:084d730b321f1f1e,48a8d8e4a4584848,000387b1796b1322

Scan History

Scan history not available

Unable to load historical scan data