Security Scan Report: m579c85.top

Redirected to:
https://2026-11-06.urldance.com/en?m579c85.top
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Submitted: Completed: publiccompleted
This website contacted 10 IPs in 4 countries across 8 domains to perform 17 HTTP transactions. The main domain is m579c85.top and was registered 3 days ago.

Submitted URL: http://m579c85.top/

Effective URL:
https://2026-11-06.urldance.com/en?m579c85.top
Redirected

AI Security Verdict

High Risk

Confidence: 76%

8
Risk Score

Bare 'enter the password to access links' gate on an unknown-age urldance.com subdomain, using a disguised text-masked password field, Unicode confusion and DevTools blocking. Nothing on the page justifies handing over a password.

Risk Factors (5)
Disguised password field (type='text' with password placeholder) - concealment of a credential-capture field
Password field with no username field and no account/login context - password harvesting pattern
DevTools and right-click/CTRL-U blocking combined with Unicode character confusion in the form
Password-gated link page on an unknown-age, unranked subdomain reached via a cross-domain redirect
Minimal, low-information page whose only purpose is obtaining a password from the visitor
Domain age information unavailable

Details

Page Title

Latest @ Sites

Scan Type

public

Domain Name Analysis

Within the .top top-level domain, 'm579c85.top' is registered while skipping any subdomain. The registrable portion 'm579c85' spans 7 characters holding zero vowels versus 2 consonants; bonus characters include 5 digits. Segmentation suggests four words: m, 579, c, 85. Average segment length settles at 1.5 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of http://m579c85.top/

Page Load Overview

0.75s
Total Load Time
130 KB
Total Size

Language Analysis

Primary Language

🇺🇸English
Code: en
Confidence:50%
Script:Latin
Direction:ltr

Detection Details

HTML Lang Attribute:x-default
Text Length:272 chars
Detector Agreement:100%
Language mismatch: Declared as x-default but detected as en

Website Classification

Primary Category

social media network82% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

social media network
82%
news media journalism
53%
documentation technical
50%
technology software
46%
healthcare medical
34%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
8156.225.108.43Hong Kong
AS139057Edgenext Legend Dynasty Pte. Ltd.
1188.114.97.3Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
1156.225.108.41Hong Kong
AS139057Edgenext Legend Dynasty Pte. Ltd.
143.174.246.36Singapore
1112.46.240.46China
AS9808China Mobile Communications Group Co., Ltd.
143.174.247.36Singapore
143.169.95.124Singapore
1183.240.98.228China
AS56040China Mobile communications corporation
1156.225.108.42Hong Kong
AS139057Edgenext Legend Dynasty Pte. Ltd.
1117.187.133.33China
AS138407The Internet Data Center of Guizhou Mobile Communication Company Limited
1710--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T12AC1D56A6EE54E361367C1892176F70DAAB6C40BDA0BC904B1FCA9801FCBFD54813A54

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

96:CdEnw8/0oYIiCoczNNBCLUJtZ8nDETs2gmwj:CdCYopVbcx2hwj

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:5930:cTEAoAEjcAIIAYIADAAaAkBAJBIAAG1AEACAEGoMCKQJykEECIgLAAB0QARAQoxFQABBkEjFTGIiEkCDBvAUABIEEBgAJISA

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:01091f1b1f1f1f0f
Perceptual Hash:8c1d337666cc9933
Difference Hash:fff3b3b3f3b3f3ff
Wavelet Hash:01191b1b1f1f1f1f
Color Hash:#a840bf

Other Hashes

Scan History

Scan history not available

Unable to load historical scan data