Security Scan Report: www.invitation-on-docum-review.vercel.app

Redirected to:
https://invitation-on-docum-review.vercel.app/
Submitted: Completed: publiccompleted
This website contacted 4 IPs in 1 country across 2 domains to perform 3 HTTP transactions. The main domain is vercel.app and was registered 6 years ago.

Submitted URL: https://www.invitation-on-docum-review.vercel.app/

Effective URL:
https://invitation-on-docum-review.vercel.app/
Redirected

AI Security Verdict

High Risk

Confidence: 72%

7
Risk Score

Fake 'Adobe Document Cloud / SharePoint' file-share page on a vercel.app subdomain impersonating Adobe, luring users to click 'Download Shared File' with no legitimate affiliation or file content.

Risk Factors (4)
Brand impersonation of Adobe Document Cloud / Microsoft SharePoint on a non-official vercel.app domain
Deceptive click-to-download lure typical of malware-distribution file-sharing pages
False copyright attribution to 'Adobe system incorporated'
Free shared-hosting subdomain with unknown age and no organizational tie to the claimed brand
Domain age information unavailable

Details

Page Title

Share Point Online — Adobe Document Cloud

Scan Type

public

Domain Name Analysis

You're looking at domain 'www.invitation-on-docum-review.vercel.app' on the application-focused generic top-level domain (.app) and includes subdomain 'www.invitation-on-docum-review'. The registrable portion 'vercel' spans 6 characters containing two vowels alongside four consonants. It segments into two words: ver, cel. Median word length is three characters. No strong language cues emerged from the frequency lists.

Screenshot

© Loading shared file Page ready, Click to view file,

Page Load Overview

0.95s
Total Load Time
104 KB
Total Size

Language Analysis

Primary Language

🇺🇸English
Code: en
Confidence:80%
Script:Latin
Direction:ltr

Detection Details

HTML Lang Attribute:en
Text Length:396 chars
Detector Agreement:80%

Website Classification

Primary Category

download file sharing85% confidence
Type: static
Method: ml+structural

All Detected Categories

download file sharing
85%
technology software
61%
documentation technical
47%
government public service
37%
social media network
34%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
364.29.17.3Aws · CLOUDUnited States
AS16509Amazon.com, Inc.
0216.198.79.67Aws · CLOUDUnited States
AS16509Amazon.com, Inc.
0216.198.79.3Aws · CLOUDUnited States
AS16509Amazon.com, Inc.
064.29.17.67Aws · CLOUDUnited States
AS16509Amazon.com, Inc.
34--

Detected Technologies2

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T182644C77F4A1321DA453CA1451C0BBBA1E6F9157D2225FF6B42B3BA08BC66C70A7390D

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

6144:JoYParYoENM6HN26zUqB+rn7RzK5/7JT8QuZQKE+TI4eX8JT8QuZQKE+TI4eXV:vP15cnB0JgQuWKFJgQuWKS

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:314589:SeqQAAIcBHYcChBKCiXFQEZh2p3AaXgFHpDkDAkVAEWQCkwgSFBCVkkCkAk6pVQgnIAFZtgoCqOAISAAPAkEOAQiklRIqpGs

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:ffffc3c3c3c3c7ff
Perceptual Hash:b4c3cbc9cd366189
Difference Hash:d005161616160e2c
Wavelet Hash:fee783c2c3838386
Color Hash:N/A

Other Hashes

Crop Resistant:d005161616160e2c

Scan History

Scan history not available

Unable to load historical scan data