Security Scan Report: amongusmod.kesug.com

Redirected to: https://amongusmod.kesug.com/?i=2&cookies_checked=1

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Submitted: Feb 27, 2026, 6:31:21 PMCompleted: Feb 27, 2026, 6:32:44 PMpubliccompleted
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Summary

This website contacted 17 IPs in 3 countries across 14 domains to perform 33 HTTP transactions. The main domain is amongusmod.kesug.com and was registered NaN years ago.

Submitted URL: https://amongusmod.kesug.com/?i=1&cookies_checked=1

Effective URL: https://amongusmod.kesug.com/?i=2&cookies_checked=1Redirected

The Cisco Umbrella rank of the primary domain is #562,189 of the top 1 million websites

AI Security Verdict

Moderate Risk

Confidence: 72%

4
Risk Score

Site uses Amazon branding on an unrelated domain; no malicious code detected but the brand mismatch warrants caution.

Risk Factors
Brand impersonation (Amazon branding on non‑Amazon domain)
Low Cisco Umbrella ranking for a major brand
Potential typo‑squatting / brand mismatch
Safety Factors
No login, password, or payment forms
No malicious Indicators of Compromise detected
No JavaScript malware patterns found
No network IDS alerts
Domain is over 2 years old
Domain age information unavailable

Details

Page Title

Among Us Mod Menu - Free Download

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

technology software

(62%)

Domain Information

Within the commercial generic top-level domain (.com), 'amongusmod.kesug.com' is registered, featuring subdomain 'amongusmod'. Count 5 characters in 'kesug' holding 2 vowels versus three consonants. Word splitting yields 2 words: kes, ug. Expect 2.5 characters per word on average. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://amongusmod.kesug.com/?i=1&cookies_checked=1

Page Load Overview

2.90s
Total Load Time
33
HTTP Requests
14
Domains
1.2 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:1,157 chars
Detector Agreement:100%

Website Classification

Primary Category

technology software62% confidence
Type: static
Method: ml+structural

All Detected Categories

technology software
62%
entertainment media
52%
cryptocurrency blockchain
50%
documentation technical
47%
government public service
46%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
17142.251.38.68United States
AS15169Google LLC
1216.58.210.142United States
AS15169Google LLC
1216.58.210.129United States
AS15169Google LLC
1216.58.209.163United States
AS15169Google LLC
118.165.140.37United States
AS16509Amazon.com, Inc.
1185.27.134.230United Kingdom
AS34119Wildcard UK Limited
1172.67.71.120United States
AS13335Cloudflare, Inc.
1142.251.38.74United States
AS15169Google LLC
1216.58.209.194United States
AS15169Google LLC
118.165.140.102United States
AS16509Amazon.com, Inc.
3317--

Detected Technologies2

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T191C2F927366341352A97A1E46BA7438F36718403E607C96D39FD4198CFCDEE8C4B62D9

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

768:XewnHCA80ei98lcGCm1c512ThLuJbKCvFI6K:XeoHCA8Li9EcGC8xuJbI6K

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:26119:GXmhIKiAGYARIw9BoM4bQHE5gJDwkLeRFAHBog9YzwQCgB1BESAAChjAEIxMDgRWCEAFySSRgDOyQGFSwBMDUkISikCZb4jh

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:ff00111919191919
Perceptual Hash:88f5f1f1c4e3e2c0
Difference Hash:35b1b1b1b1b1b1b1
Wavelet Hash:ff19191919191b1f
Color Hash:#862d7e

Other Hashes

Scan History

Scan history not available

Unable to load historical scan data