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Security Scan Report: www.campustimes.org

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Submitted: Oct 12, 2025, 8:11:50 AMCompleted: Oct 12, 2025, 8:13:28 AMpubliccompleted
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Summary

This website contacted 1 IP in 1 country across 1 domain to perform 3 HTTP transactions. The main domain is campustimes.org and was registered NaN years ago.

Submitted URL: https://www.campustimes.org/2025/02/11/michael-che-announces-his-exit-from-snl/

AI Security Verdict

Safe Website

Confidence: 92%

0
Risk Score

The site shows no security threats and is considered legitimate.

Safety Factors
Long‑standing domain with minimal reputation risk
Absence of suspicious forms or redirects
Domain age information unavailable

Details

Page Title

500 Internal Server Error

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

news/blog

(35%)

Domain Information

The domain name 'www.campustimes.org' uses the non-profit oriented generic top-level domain (.org); it also runs on subdomain 'www'. The registrable portion 'campustimes' spans 11 characters with four vowels and 7 consonants. Word splitting yields 2 words: campus, times. Median word length comes out to 5.5 characters. The linguistic tilt is English for 'campus'. Usage also turns up in Chinese (Pinyin) and Sinhala contexts. Taken together, it feels English.

Screenshot

Security scan screenshot of https://www.campustimes.org/2025/02/11/michael-che-announces-his-exit-from-snl/

Page Load Overview

35.14s
Total Load Time
3
HTTP Requests
1
Domains
5 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
Text Length:7,030 chars
Detector Agreement:100%

Website Classification

Primary Category

news/blog35% confidence
Type: spa
Method: ml+structural

All Detected Categories

news/blog
35%
entertainment media
31%
forum
20%
news
15%

Detected Features

Articles
OG: article
Schema.org

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
3128.151.77.207Rochester, New York, United States
31--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T12283923390E45426135BD2D9A93E631BEF62C20BDB439E5070FD826CAFD1DA6095392F

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

1536:H3+QR0+ipapowoyb3cVxgLtRTfU4YY7nMnJ2RfHWEEF+Yu:X9R0+PywbbsUA4YY7nMnJ2RfHKF+Yu

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:82080:hwStoChQhCACTwYABgBsio0cQICLFPAALFADCAgMgSkEgAQ9OID6I4hTiTJFsIjc0BBHolICCAGB+hFRqABABM8GgEoAUDR6

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:070fffffffffffff
Perceptual Hash:87070707070fcfcf
Difference Hash:ec68000000000000
Wavelet Hash:071fffff00000000
Color Hash:#1f2d93

Other Hashes

Crop Resistant:ec68000000000000

Scan History

Scan history not available

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