Security Scan Report: separate-apricot-hbdffwuz.edgeone.dev

Submitted: Completed: publiccompleted
This website contacted 12 IPs in 2 countries across 7 domains to perform 12 HTTP transactions. The main domain is edgeone.dev and was registered 1 year 5 months ago.

Submitted URL: https://separate-apricot-hbdffwuz.edgeone.dev/

AI Security Verdict

Confirmed Scam

Confidence: 96%

10
Risk Score

Phishing kit on an edgeone.dev subdomain: e-mail/password login form disguised behind a fake 'not a robot' check, with a hard-coded Telegram bot token to exfiltrate submitted data. Domain flagged as phishing by two independent feeds.

Risk Factors (6)
Multi-feed phishing threat-intel match on the primary domain and its URL
Password + email login form on a shared hosting-platform subdomain of unknown age
Telegram bot token embedded in page script enabling exfiltration of submitted data to an attacker-controlled chat
Visitor IP harvesting via api.ipify.org
Fake human-verification checkbox ('I am not a robot') used as a lure to drive credential entry
Unranked domain with no established reputation
Domain age information unavailable

Details

Page Title

Sign In.

Scan Type

public

Domain Name Analysis

You're looking at domain 'separate-apricot-hbdffwuz.edgeone.dev' on the developer-focused generic top-level domain (.dev) and includes subdomain 'separate-apricot-hbdffwuz'. The second-level label 'edgeone' is 7 characters long containing four vowels alongside 3 consonants. Word splitting yields two words: edge, one. Median word length is 3.5 characters. No strong language cues emerged from the frequency lists.

Screenshot

Checking your browser and insight for help... lam not a robot click on the checkbox to verity if you're human.

Page Load Overview

0.82s
Total Load Time
117 KB
Total Size

Language Analysis

Primary Language

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

Detection Details

HTML Lang Attribute:en
Text Length:240 chars
Detector Agreement:100%

Website Classification

Primary Category

documentation technical58% confidence
Type: static
Method: ml+structural+ocr_tiebreaker

All Detected Categories

documentation technical
58%
technology software
56%
news media journalism
41%
adult content
38%
healthcare medical
36%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
4104.16.179.112Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
243.174.247.29Singapore
143.174.246.29Singapore
1151.101.1.229Fastly · CDNUnited States
AS54113Fastly, Inc.
1142.250.154.95Google · CDNUnited States
AS15169Google LLC
1142.251.150.119Google · CDNUnited States
AS15169Google LLC
1142.251.14.147Google · CDNUnited States
AS15169Google LLC
1142.251.110.94Google · CDNUnited States
AS15169Google LLC
1104.26.12.205Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
1142.251.152.119Google · CDNUnited States
AS15169Google LLC
1212--

Detected Technologies2

Bootstrapv5.3.0
50%

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T13432F862ABF9043D3293D0B935B5B7847E31C107DF41059A396D2A948FCAE8648777CC

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

192:w7Uq6jfD9jTZLox1JJyMZN+KJAM7R0eyimtmfEMrisLiZi4jb2UO4UWOA+:wAeX0eyiRHriyiZi4jDUW8

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:11904:CMQGaBiYwUlwAAAkiEkKcsFYDLhY4lGQURIgRNIBomgwomZk0CoPAMAAUQEaOAVoLUEEQwQAARAADdRQEIqT5EtAWBSBNsSG

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:ffc3c3ffffffffff
Perceptual Hash:b13146cece9b9931
Difference Hash:00161e0000000000
Wavelet Hash:3b03033f0f0f0f0f
Color Hash:07000000000

Other Hashes

Crop Resistant:00161e0000000000

Scan History

Scan history not available

Unable to load historical scan data