Security Scan Report: crickster.pages.dev

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Submitted: Completed: publiccompleted
This website contacted 54 IPs in 4 countries across 48 domains to perform 314 HTTP transactions. The main domain is pages.dev and was registered 6 years ago.

Submitted URL: https://crickster.pages.dev/blog/insect-travel-guide-thailand

AI Security Verdict

Safe Website

Confidence: 82%

1
Risk Score

Self-branded food/travel blog article on pages.dev with an editorial guide to edible insects in Thailand. Only form is a Mailerlite newsletter signup — no credentials or payment fields, and no threat-intel, hunting rule or IDS evidence.

Safety Factors (5)
Self-branding detected — site title/meta brand matches its own domain, so this is not a brand claim on a foreign domain
No credential or payment collection: zero password, disguised-password and payment fields
Newsletter form posts to Mailerlite, an established email-marketing service, not to a suspicious or lookalike endpoint
No IoC, hunting rule, Safe Browsing or phishing/malware IDS evidence against the page or its resources
Consistent, substantive editorial content (destinations, species, sourcing) typical of a genuine food/travel blog
Domain age information unavailable

Details

Page Title

The Ultimate Edible Insect Travel Guide - Thailand

Scan Type

public

Domain Name Analysis

The domain 'crickster.pages.dev' uses the developer-focused generic top-level domain (.dev) with subdomain 'crickster'. Count 5 characters in 'pages' with 2 vowels and three consonants. Segmentation suggests 1 word: pages. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://crickster.pages.dev/blog/insect-travel-guide-thailand

Page Load Overview

0.70s
Total Load Time
11.7 MB
Total Size

Language Analysis

Primary Language

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

Detection Details

HTML Lang Attribute:en
Text Length:14,975 chars
Detector Agreement:100%

Website Classification

Primary Category

travel tourism42% confidence
Type: spa
Method: ml+structural

All Detected Categories

travel tourism
42%
education learning
37%
corporate
25%

Detected Features

OG: website

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
49172.66.46.223Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
5142.250.154.95Google · CDNUnited States
AS15169Google LLC
518.245.60.50Cloudfront · CDNUnited States
AS16509Amazon.com, Inc.
5172.67.156.140Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
5185.15.59.224United States
AS14907Wikimedia Foundation Inc.
5104.18.10.41Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
5188.114.97.3Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
5157.240.0.174Facebook · CDNFrankfurt am Main, Hesse, Germany
AS32934Facebook, Inc.
5146.75.120.84Fastly · CDNFrankfurt am Main, Hesse, Germany
AS54113Fastly, Inc.
5157.240.0.35Facebook · CDNFrankfurt am Main, Hesse, Germany
AS32934Facebook, Inc.
31454--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T13E745C3362903748610B8D76775B328DF21AC967B19306EEE095AC19C7CB6859BF273C

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

3072:+WuVFviTD+Rgl7dG0WRmBYtvvv1dbJB8rVaaeCyjxN3xOU6w3EobLRl6:+jLn0WRmBGdbJB85aaTyJTPbz6

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:368503:GAzE7ESvYjCAADyCAcDFEkERGIyAyYgAKFApGJoVhEB3kLuIWEYkSQEKAYwgCggVAgxzUVAAAwmag4mgHsFwgAnoJAMAgwUA

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:ffff8f8fdfc90109
Perceptual Hash:bbc40fc88f38731c
Difference Hash:22c0383838513959
Wavelet Hash:bfff878f9f010100
Color Hash:07200180000

Other Hashes

Crop Resistant:22c0383838513959

Scan History

Scan history not available

Unable to load historical scan data