Security Scan Report: www.pep.ph

Submitted: Nov 25, 2025, 9:27:43 AMCompleted: Nov 25, 2025, 9:30:51 AMpubliccompleted
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Summary

This website contacted 273 IPs in 8 countries across 121 domains to perform 615 HTTP transactions. The main domain is pep.ph.

Submitted URL: https://www.pep.ph/news/foreign/189818/olivia-yace-resigns-as-miss-universe-africa-oceania-a712-20251124

The Cisco Umbrella rank of the primary domain is #232,755 of the top 1 million websites

AI Security Verdict

Safe Website

Confidence: 92%

0
Risk Score

Legitimate news article with no security concerns.

Safety Factors
Established domain with legitimate content
No forms collecting sensitive data
No known malicious Indicators of Compromise
Domain age information unavailable

Details

Page Title

Olivia Yace resigns as Miss Universe Africa & Oceania | PEP.ph

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

social media network

(52%)

Domain Information

Within the Philippine country-code top-level domain (.ph), 'www.pep.ph' is registered, featuring subdomain 'www'. Count 3 characters in 'pep' split between 1 vowel and two consonants. Segmentation suggests one word: pep. Median word length comes out to 3 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://www.pep.ph/news/foreign/189818/olivia-yace-resigns-as-miss-universe-africa-oceania-a712-20251124

Page Load Overview

5.61s
Total Load Time
615
HTTP Requests
121
Domains
16.2 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:66,171 chars
Detector Agreement:100%

Website Classification

Primary Category

social media network52% confidence
Type: static
Method: ml+structural

All Detected Categories

social media network
52%
entertainment media
39%
forum
35%
government public service
26%
social_media
25%

Detected Features

Search
Comments
OG: article

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
79146.75.121.44Frankfurt am Main, Hesse, Germany
AS54113FASTLY
7152.223.40.198United States
AS16509AMAZON-02
53108.138.26.62United States
AS16509AMAZON-02
40157.240.0.63Frankfurt am Main, Hesse, Germany
AS32934FACEBOOK
3552.76.240.107Singapore, Singapore
AS16509AMAZON-02
2554.192.35.40United States
AS16509AMAZON-02
21172.217.23.99United States
AS15169GOOGLE
1913.226.244.127United States
AS16509AMAZON-02
18141.226.228.48Netherlands
AS200478Taboola.com ltd
15157.240.253.63Frankfurt am Main, Hesse, Germany
AS32934FACEBOOK
615273--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1A2A44B3270D4251542A7B1E6A6E977097A22D093E9034EC9F1EE1F6C8F86FD725932CC

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

6144:0dDKGF7dzdrxtcFqWTupHu1r+kYIxb7WSJZW2kRhUPIQJfq22Ieysnd/VZcInfDH:kKGFhVxWp4S+kYYH9JZW2p1www

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:486563:Bng0ACSVAeoQMCEEpCYVQD0+mgCJyhYAGFGUhXwgRQPFplHWAFi7EABQsBEIgBDQhUjDUWxBPTj0bAFIOgPUBXBCCAjFaoAi

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:91fbffc381c1c081
Perceptual Hash:fb854c7b2c528556
Difference Hash:3333342b2b0b292b
Wavelet Hash:81ffffc38183c0c1
Color Hash:#2d3a86

Scan History

Scan history not available

Unable to load historical scan data