Security Scan Report: uphitoldlogin.gitbook.io

Submitted: Nov 15, 2025, 4:57:24 AMCompleted: Nov 15, 2025, 4:58:05 AMpubliccompleted
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Summary

This website contacted 12 IPs in 0 countries across 4 domains to perform 44 HTTP transactions. The main domain is uphitoldlogin.gitbook.io.

Submitted URL: https://uphitoldlogin.gitbook.io/sign-in/

AI Security Verdict

High Risk

Confidence: 88%

8
Risk Score

High‑risk phishing page impersonating Uphold login; do not trust.

Risk Factors
Brand impersonation of Uphold on a non‑official domain
Unranked and likely newly registered domain
Misleading page title and content that suggest a login portal
Use of a generic hosting platform (GitBook) for a fake login page
Domain age information unavailable

Details

Primary Scan Blocked — Fallback Capture Shown

The primary scanner could not load this page (possible bot protection). The screenshot and page details shown were captured by a fallback browser that loaded the page successfully.

Page Title

Ûphold Loℊin | Sign In 💎

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

healthcare medical

(82%)

Domain Information

Within the British Indian Ocean Territory country-code top-level domain (.io), 'uphitoldlogin.gitbook.io' is registered; it also runs on subdomain 'uphitoldlogin'. The second-level label 'gitbook' is 7 characters long split between three vowels and 4 consonants. It segments into 3 words: g, it, book. The median word length lands at 2 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://uphitoldlogin.gitbook.io/sign-in/

Page Load Overview

8.99s
Total Load Time
44
HTTP Requests
4
Domains
1.7 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:295 chars
Detector Agreement:100%

Website Classification

Primary Category

healthcare medical82% confidence
Type: spa
Method: ml+structural

All Detected Categories

healthcare medical
82%
government public service
38%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
11172.64.147.188UnknownUnknown
3172.64.147.209UnknownUnknown
3104.18.41.89UnknownUnknown
3172.64.146.167UnknownUnknown
3104.18.40.47UnknownUnknown
3104.18.40.68UnknownUnknown
32606:4700:4404::6812:2959UnknownUnknown
32a06:98c1:310d::ac40:92a7UnknownUnknown
32606:4700:4407::6812:282fUnknownUnknown
32a06:98c1:3101::ac40:93bcUnknownUnknown
4412--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T11DB3C70A5101F7069DB2DE14633A7D3D80DED7279778C4A9F20ED5A62B8813F1BE39A1

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

3072:D3gr4wyIG3x4/C3/Ion1dF41GIFqkIzaIFyvynDn:+4fL

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:117749:ClogBwJIZQSgGHE4OM0QJmYxHRVuBINUMFAGehLtA5ghAAaAIQiUX5VNEZgGgoFwooEFBCAIgECUAg4EgIhAaBF6UHCRIk3A

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:ffc7c3c3c3efffff
Perceptual Hash:b131ce8e33996c65
Difference Hash:5996969a9e1e0042
Wavelet Hash:00c30303c3c3ff3f
Color Hash:#4042bf

Other Hashes

Scan History

Scan history not available

Unable to load historical scan data