Security Scan Report: ajaxtipssitus-v8flsdwexl.edgeone.app

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Submitted: May 23, 2026, 6:37:23 PMCompleted: May 23, 2026, 6:40:00 PMpubliccompleted
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Summary

This website contacted 8 IPs in 2 countries across 8 domains to perform 11 HTTP transactions. The main domain is ajaxtipssitus-v8flsdwexl.edgeone.app and was registered NaN years ago.

Submitted URL: https://ajaxtipssitus-v8flsdwexl.edgeone.app/12015-how-to-write-an-application-letter-for-not-attending-an-exam-to-a-principal.html

The Cisco Umbrella rank of the primary domain is #455,732 of the top 1 million websites

AI Security Verdict

Moderate Risk

Confidence: 65%

5
Risk Score

The site shows moderate risk due to an unknown‑age subdomain and low reputation, but lacks malicious forms or malware.

Risk Factors
Unknown subdomain age
Low domain ranking
Brand mention on an unranked domain
Safety Factors
No forms or credential exfiltration
No Indicators of Compromise matches
No JavaScript malware patterns
No network IDS alerts
Domain age information unavailable

Details

Page Title

How to write an application letter for not attending an exam to a principal

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

news media journalism

(75%)

Domain Information

Within the application-focused generic top-level domain (.app), 'ajaxtipssitus-v8flsdwexl.edgeone.app' is registered with subdomain 'ajaxtipssitus-v8flsdwexl'. Its registrable label 'edgeone' stretches across 7 characters with 4 vowels and three consonants. It segments into 2 words: edge, one. Median word length comes out to 3.5 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://ajaxtipssitus-v8flsdwexl.edgeone.app/12015-how-to-write-an-application-letter-for-not-attending-an-exam-to-a-principal.html

Page Load Overview

90.15s
Total Load Time
13
HTTP Requests
10
Domains
32 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-US
Text Length:8,610 chars
Detector Agreement:100%

Website Classification

Primary Category

news media journalism75% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

news media journalism
75%
education learning
74%
government public service
57%
adult content
57%
documentation technical
53%

Detected Features

OG: article
Schema.org

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
6172.240.127.242United States
AS7979Servers.com, Inc.
1104.18.11.207United States
AS13335Cloudflare, Inc.
1142.251.110.94United States
AS15169Google LLC
1101.33.10.10Frankfurt am Main, Hesse, Germany
1142.251.13.95United States
AS15169Google LLC
1104.21.0.120United States
AS13335Cloudflare, Inc.
1172.66.169.241United States
AS13335Cloudflare, Inc.
1104.20.7.223United States
AS13335Cloudflare, Inc.
138--

Detected Technologies4

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T11492F76BEB801729136302B8B549F2FCFB3E842DD3D645E0D4D9C225338AADB5676189

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

384:brgqMZNhnYf8zX+ZbmNBex3D5J9UaQieyr1BqvKAZKOZ4LO2fD5N9gZr2i6TGs6x:bQZNhnz+ZbmNBex3D5J9UaQieyrSvfwG

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:19796:VEjAHgAQhnSIQKVFYKFQgEAlSAACFspA1ISJCmyRGyIAVzJhgIENd0gGSxhJljwSKAAsBcCgAyiToR0CIAjgEAEkidACIRKZ

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:80c7c3c3c3c3c3ff
Perceptual Hash:b457c323436b4b39
Difference Hash:0a3e161616161616
Wavelet Hash:00c7c3c3c3c3c3f7
Color Hash:#a979d2

Other Hashes

Crop Resistant:0a3e161616161616

Scan History

Scan history not available

Unable to load historical scan data