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Security Scan Report: app.pdf.net

Redirected to: https://app.pdf.net/login

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Submitted: Dec 24, 2025, 8:25:13 PMCompleted: Dec 24, 2025, 8:25:58 PMpubliccompleted
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Summary

This website contacted 23 IPs in 3 countries across 23 domains to perform 81 HTTP transactions. The main domain is app.pdf.net and was registered NaN years ago.

Submitted URL: https://app.pdf.net

Effective URL: https://app.pdf.net/loginRedirected

The Cisco Umbrella rank of the primary domain is #308,945 of the top 1 million websites

AI Security Verdict

High Risk

Confidence: 85%

7
Risk Score

Site mimics Google login on a low‑rank domain, likely a phishing page.

Risk Factors
Brand impersonation/typosquatting detected
Low ranking for brand claim (rank > 100k) on Cisco Umbrella
Domain age information unavailable

Details

Page Title

pdf.net

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

technology software

(45%)

Domain Information

The domain name 'app.pdf.net' uses the network infrastructure generic top-level domain (.net); it also runs on subdomain 'app'. The second-level label 'pdf' is 3 characters long with 0 vowels and 3 consonants. Segmentation suggests one word: pdf. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://app.pdf.net

Page Load Overview

6.99s
Total Load Time
68
HTTP Requests
23
Domains
1.9 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-US
Text Length:194 chars
Detector Agreement:100%

Website Classification

Primary Category

technology software45% confidence
Type: spa
Method: ml+structural

All Detected Categories

technology software
45%
news media journalism
29%
government public service
26%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
24188.114.97.3Sweden
AS54113
2216.58.206.67United States
AS15169
266.33.60.34Ireland
AS8075
235.241.1.16Kansas City, Missouri, United States
AS396982GOOGLE-CLOUD-PLATFORM
234.54.197.252Kansas City, Missouri, United States
AS396982GOOGLE-CLOUD-PLATFORM
234.49.44.84Kansas City, Missouri, United States
AS396982GOOGLE-CLOUD-PLATFORM
22.22.50.134Unknown
AS16509
2146.75.122.132UnknownUnknown
234.49.181.76Kansas City, Missouri, United States
AS396982GOOGLE-CLOUD-PLATFORM
2150.171.27.10UnknownUnknown
6823--

Detected Technologies2

Vercel
40%
HSTS
40%

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1FB032CE96962221C511784F67B15F21CE11AC293FE27ECF5EAEC4578FFC19E69883048

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

768:KkGhh4E+7BUF0LCMkD8BYIuYqLt0zGWxg/Garx7/qT7T:KJ/QBUUCLAm37/+

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:39938:wpQrhaIHCIF0cxChhKIjIAVJQoRAi+AaQHwboBGkMUisAAMQmhJjCBG0FRSkHBAoDQEKAwAB3gQJVgpJHxAC6GboQokFD1Ap

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:ffffe7ffe7ffffe7
Perceptual Hash:b3cccc3333cc9926
Difference Hash:100808284d08000c
Wavelet Hash:f0e0e0f8e0e8f0e0
Color Hash:#78673a

Other Hashes

Crop Resistant:100808284d08000c

Scan History

Scan history not available

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