Security Scan Report: coinsbcaeprolognim.gitbook.io

Submitted: Oct 31, 2025, 10:20:47 AMCompleted: Oct 31, 2025, 10:21:36 AMpubliccompleted
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Summary

This website contacted 12 IPs in 1 country across 4 domains to perform 44 HTTP transactions. The main domain is coinsbcaeprolognim.gitbook.io.

Submitted URL: https://coinsbcaeprolognim.gitbook.io/us/

AI Security Verdict

High Risk

Confidence: 92%

8
Risk Score

Phishing page impersonating Coinbase Pro on an unranked GitBook subdomain; high risk.

Risk Factors
Brand impersonation of Coinbase Pro on a non‑official, unranked domain
Social engineering detection by Google Safe Browsing
Unranked domain (not in Cisco Umbrella top 1 M) used for a login‑style page
Absence of legitimate login forms suggests hidden or malicious credential harvesting
Suspicious subdomain (coinsbcaeprolognim) with no established reputation
Domain age information unavailable

Details

Bot Protection Detected

This website is protected by Cloudflare bot protection. Our scanner was challenged or blocked during access.

Page Title

Çoinbase Pro @ Login | Çoinbase Pro @ Login

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

technology software

(64%)

Domain Information

The domain 'coinsbcaeprolognim.gitbook.io' uses the British Indian Ocean Territory country-code top-level domain (.io) and includes subdomain 'coinsbcaeprolognim'. Count 7 characters in 'gitbook' split between three vowels and four consonants. Word splitting yields three words: g, it, book. Median word length comes out to two characters. The linguistic tilt is English for 'g'. Secondary signals appear in Chinese (Pinyin) and Chinese (Zhuyin).

Screenshot

Security scan screenshot of https://coinsbcaeprolognim.gitbook.io/us/

Page Load Overview

8.29s
Total Load Time
44
HTTP Requests
4
Domains
1.4 MB
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:175 chars
Detector Agreement:67%

Website Classification

Primary Category

technology software64% confidence
Type: spa
Method: ml+structural

All Detected Categories

technology software
64%
documentation technical
54%
cryptocurrency blockchain
49%
healthcare medical
35%
news media journalism
34%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
3172.64.147.209United States
AS13335CLOUDFLARENET
3104.18.40.47United States
AS13335CLOUDFLARENET
3104.18.41.89United States
AS13335CLOUDFLARENET
3104.18.40.68United States
AS13335CLOUDFLARENET
3172.64.146.167United States
AS13335CLOUDFLARENET
3172.64.147.188United States
AS13335CLOUDFLARENET
32606:4700:4404::6812:2959United States
AS13335CLOUDFLARENET
32606:4700:4407::6812:282fUnited States
AS13335CLOUDFLARENET
32606:4700:4408::6812:2844United States
AS13335CLOUDFLARENET
32a06:98c1:310d::ac40:92a7United States
AS13335CLOUDFLARENET
4412--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T183C3FC19A100F6065DB2DE14333ABE3E80CED61797B9C5BEF24EDAD50B8813B17E2855

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

1536:JfYxMAD7vvted62KoXBh+q3nRvIOuP1lJ5EaqU9wmwwGVOCXfjjRYcZfxwMBrh40:h3gOaRh3xBhSss

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:124855:QKSAEYgBUZwhiANojsURgslQoCR6aqFEKdFyAUgACAaAEgCIAk+yQADy0oKyCEEYuAQRCpBU1IpIwCMUg6o0ZxAFgBwCIQDD

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:ffc3c3c3c3ffffff
Perceptual Hash:e1619a9a279e8e65
Difference Hash:5196969686160046
Wavelet Hash:00c20000c0c0fc1c
Color Hash:#40bfae

Other Hashes

Scan History

Scan history not available

Unable to load historical scan data