Security Scan Report: realistic-salmon-jcwrstgb.edgeone.app

Submitted: Sep 25, 2026, 9:50:04 AMCompleted: Sep 25, 2026, 9:50:37 AMpubliccompleted

AI Security Verdict

Confirmed Scam

Confidence: 88%

9
Risk Score

Fake 'Login to Mail' page on an unknown-age edgeone.app subdomain whose JavaScript exfiltrates entered email and password to a Telegram endpoint — a credential-phishing kit. Do not enter credentials.

Risk Factors
JavaScript sends password/email to an external server (credential exfiltration)
Credential-harvesting login form (email + password) on a non-official, randomized subdomain
Unknown-age subdomain on a free/instant hosting platform with no domain reputation
Domain age information unavailable

Details

Page Title

Mail

Scan Type

public

Domain Name Analysis

Within the application-focused generic top-level domain (.app), 'realistic-salmon-jcwrstgb.edgeone.app' is registered, featuring subdomain 'realistic-salmon-jcwrstgb'. Count 7 characters in 'edgeone' split between four vowels and 3 consonants. Word splitting yields 2 words: edge, one. Average segment length settles at 3.5 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://realistic-salmon-jcwrstgb.edgeone.app/

Page Load Overview

1.44s
Total Load Time
3 KB
Total Size

Language Analysis

Primary Language

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

Detection Details

HTML Lang Attribute:en
Text Length:69 chars
Detector Agreement:100%

Website Classification

Primary Category

news media journalism45% confidence
Type: webapp
Method: ml+structural+ocr_tiebreaker

All Detected Categories

news media journalism
45%
government public service
39%
healthcare medical
28%
e-commerce shopping
27%
finance banking
27%

Detected Features

Login Form

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
243.152.26.58Singapore
043.152.26.110Singapore
0101.33.10.10Frankfurt am Main, Hesse, Germany
23--

Detected Technologies1

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T14C516072E192643BA127C5DE7070939EB0E6C402C3976A136DFD9378CACAE939B1134C

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

48:Tm4RZc1c2IXZftTM58SVdu65WwVbqF3JqM8LbR56:Tmgkc3lXSVrhWpsMeRE

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:2544:EhIgEAACAQAEAECIIAGQgRIAgAAgIAgAAAIATYABYgAQAABEgAAAECBAAAARAAIAAgAAIAQKAAQsQGAABAIACAAAEEAGMAMF

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:ffffe7e7e7ffffff
Perceptual Hash:b326cc993366cc99
Difference Hash:0000080c0c080000
Wavelet Hash:3f3f030303270f0f
Color Hash:#79d2b2

Other Hashes

Crop Resistant:0000080c0c080000

Scan History

Scan history not available

Unable to load historical scan data