Security Scan Report: rafsan-vai-personal-power-full-dkwin-ai-hack-dp3d3ykg4hjv.edgeone.dev

Submitted: Oct 6, 2026, 7:54:16 PMCompleted: Oct 6, 2026, 7:54:57 PMpubliccompleted

AI Security Verdict

High Risk

Confidence: 68%

7
Risk Score

Bare password-only page on a free edgeone.dev subdomain, labelled 'HACK LOGIN'/'HIDE', whose scripts talk cross-origin to an unranked .top host flagged as hostile by IDS. Consistent with credential harvesting; do not enter any password.

Risk Factors (6)
Password input with no accompanying username/email field β€” a credential-harvesting shape
Cross-origin XHR to an unranked '.top' host (dkwin2.top) related to the subdomain's own naming
IDS alerts tagging '.top' DNS/HTTP traffic as likely hostile (HIGH severity)
Telegram auth-cookie and Telegram domain traffic observed alongside the page
'HACK LOGIN' / 'HIDE' button pair with no legitimate site purpose or disclosed owner
Free hosting-platform subdomain with unknown creation date
Domain age information unavailable

Details

Page Title

𝐎𝐰𝐧𝐞𝐫 π‘πšπŸπ¬πšπ§ π•π€πˆ

Scan Type

public

Domain Name Analysis

The domain name 'rafsan-vai-personal-power-full-dkwin-ai-hack-dp3d3ykg4hjv.edgeone.dev' uses the developer-focused generic top-level domain (.dev); it also runs on subdomain 'rafsan-vai-personal-power-full-dkwin-ai-hack-dp3d3ykg4hjv'. Its registrable label 'edgeone' stretches across 7 characters split between 4 vowels and three consonants. Splitting it apart reveals two words: edge, one. Median word length is 3.5 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://rafsan-vai-personal-power-full-dkwin-ai-hack-dp3d3ykg4hjv.edgeone.dev/

Page Load Overview

7.92s
Total Load Time
5.3 MB
Total Size

Language Analysis

Primary Language

πŸ‡ΊπŸ‡ΈEnglish
Code: en
Confidence:56%
Script:Latin
Direction:ltr

Detection Details

HTML Lang Attribute:bn
Text Length:147 chars
Detector Agreement:100%
Language mismatch: Declared as bn but detected as en

Website Classification

Primary Category

technology software76% confidence
Type: static
Method: ml+structural

All Detected Categories

technology software
76%
cryptocurrency blockchain
69%
documentation technical
66%
healthcare medical
65%
phishing scam
50%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
2143.174.246.29Singapore
2142.251.127.95Google Β· CDNUnited States
AS15169Google LLC
2142.251.14.94Google Β· CDNUnited States
AS15169Google LLC
2195.154.239.27Paris, Île-de-France, France
AS12876Scaleway SAS
245.43.142.7United Kingdom
AS16276OVH SAS
2104.21.51.186Cloudflare Β· WAFUnited States
AS13335Cloudflare, Inc.
2142.251.20.94Google Β· CDNUnited States
AS15169Google LLC
2108.181.20.35Los Angeles, California, United States
AS40676Psychz Networks
2142.251.14.95Google Β· CDNUnited States
AS15169Google LLC
2195.154.239.26Paris, Île-de-France, France
AS12876Scaleway SAS
5920--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1C503C5A756F310355917A1D86FA7470A2339E003E507CC293BDD93858F8B8EAD997B8C

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

768:9U/DD+yF8pLRJF1FUeoWoFbFHFTM7FFS7wcM+mNCiTT/SPOu:K/DD+yOpLRJXal55YuV

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:40717:QIIGB2SIOBaIBGQIIKJJBQNQAUAuEhiggSQACihAACUMzFZ2RAljH2KzI7F9hABAaBJiCMCjQNAUKBaMEnMoFYgMECIFmxgG

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:0303010000000000
Perceptual Hash:ababa95555545652
Difference Hash:030b030001000000
Wavelet Hash:0f0f0f0f00000000
Color Hash:#d2692d

Other Hashes

Crop Resistant:030b030001000000

Scan History

Scan history not available

Unable to load historical scan data