Security Scan Report: yoman168.net

Redirected to: blob:https://yoman168.net/dab96f40-1c9d-495e-8479-1ed7ae5b54ce

Submitted: Nov 2, 2025, 7:08:15 PMCompleted: Nov 2, 2025, 7:09:12 PMpubliccompleted
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Summary

This website contacted 33 IPs in 3 countries across 4 domains to perform 8 HTTP transactions. The main domain is .

Submitted URL: https://yoman168.net/wp-includes/Cappo25.html

Effective URL: blob:https://yoman168.net/dab96f40-1c9d-495e-8479-1ed7ae5b54ceRedirected

AI Security Verdict

Confirmed Scam

Confidence: 95%

10
Risk Score

High‑risk phishing site impersonating Capital One; do not enter any credentials.

Risk Factors
Impersonation of a well‑known financial brand on a low‑reputation domain
Compromised WordPress site path indicating a hacked site
Credential‑harvesting login forms with password fields
Disguised password fields (type='text' with password placeholders)
Unicode character mixing to evade detection
Domain age unknown/very new, increasing suspicion
Domain age information unavailable

Details

Page Title

Sign In

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

finance banking

(55%)

Domain Information

Within the network infrastructure generic top-level domain (.net), 'yoman168.net' is registered while skipping any subdomain. The second-level label 'yoman168' is 8 characters long with 2 vowels and three consonants, plus three digits. Segmentation suggests three words: yom, an, 168. Median word length comes out to 3 characters. Most frequently, 'an' shows up in Breton. It also appears in Chinese (Pinyin) and English contexts.

Screenshot

Security scan screenshot of https://yoman168.net/wp-includes/Cappo25.html

Page Load Overview

26.31s
Total Load Time
8
HTTP Requests
4
Domains
81 KB
Total Size

Language Analysis

Primary Language

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

Detection Details

Language Code:en
Detection Confidence:80%
Script Type:Latin
HTML Lang Attribute:en
Text Length:1,461 chars
Detector Agreement:67%

Website Classification

Primary Category

finance banking55% confidence
Type: webapp
Method: ml+structural

All Detected Categories

finance banking
55%
government public service
40%
documentation technical
37%
corporate business
33%
adult content
31%

Detected Features

Login Form

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
8142.250.184.234United States
AS15169GOOGLE
063.176.8.218Frankfurt am Main, Hesse, Germany
AS16509AMAZON-02
035.157.26.135Frankfurt am Main, Hesse, Germany
AS16509AMAZON-02
0151.101.66.137San Francisco, California, United States
AS54113FASTLY
0154.205.158.24Jakarta, Jakarta, Indonesia
AS138915Kaopu Cloud HK Limited
0142.250.185.74United States
AS15169GOOGLE
0142.250.186.74United States
AS15169GOOGLE
02a00:1450:4001:812::200aFrankfurt am Main, Hesse, Germany
AS15169GOOGLE
02a05:d014:58f:6200::259Frankfurt am Main, Hesse, Germany
AS16509AMAZON-02
0142.250.185.138United States
AS15169GOOGLE
833--

Detected Technologies4

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T14343553661A341BADDB3CAC857EB2A463E849887E0C9C12477AC9AD44F838D5D47D3DC

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

768:e7FSF3FuWFzF+fs8utovi8utovWX9FTHQrCt1WtjL/plyA7qvE6mw:0Ql0WxMTv9vQsCt1WtjLRlyA7q86mw

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:57145:EAARahhFDghEMQgFEZQVgg1AKFMgFhgYEYjCQU0hMKMS2A9IJqDOEQwTO7gNaugQQrvAYhjKkCIkINwkkhgISEoAgoAgKwU/

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:7fa5bde7c3ffcfff
Perceptual Hash:b38f8c27239d89b1
Difference Hash:e869704c4d2a2c00
Wavelet Hash:7f343c2c0424df0d
Color Hash:#40bfae

Other Hashes

Crop Resistant:e869704c4d2a2c00

Scan History

Scan history not available

Unable to load historical scan data