Security Scan Report: www.celistacabinetryproject.vercel.app

Redirected to:
https://celistacabinetryproject.vercel.app/
Submitted: Completed: publiccompleted
This website contacted 8 IPs in 1 country across 5 domains to perform 5 HTTP transactions. The main domain is vercel.app and was registered 6 years ago.

Submitted URL: https://www.celistacabinetryproject.vercel.app/

Effective URL:
https://celistacabinetryproject.vercel.app/
Redirected

AI Security Verdict

High Risk

Confidence: 78%

8
Risk Score

Fake 'DocuSign for Microsoft' page on a vercel.app subdomain that impersonates DocuSign/Microsoft and runs a device-code sign-in lure ('copy code', 'paste and sign in') to steal account access.

Risk Factors (4)
Impersonation of DocuSign and Microsoft brands on a non-official hosting subdomain
No legitimate page asks a user to copy an authentication code and paste it into a Microsoft sign-in prompt to 'view a document' — this is a device-authorisation credential/session theft pattern
Hosted on the free vercel.app platform, a namespace frequently abused for phishing lures (flagged by IDS abused-services rules)
Unranked, unknown-age subdomain presenting itself as a trusted document-signing service
Domain age information unavailable

Details

Page Title

DocuSign for Microsoft

Scan Type

public

Domain Name Analysis

Domain 'www.celistacabinetryproject.vercel.app' uses the application-focused generic top-level domain (.app) with subdomain 'www.celistacabinetryproject'. The core label 'vercel' covers 6 characters holding two vowels versus 4 consonants. Word splitting yields 2 words: ver, cel. Median word length is three characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://www.celistacabinetryproject.vercel.app/

Page Load Overview

1.20s
Total Load Time
59 KB
Total Size

Language Analysis

Primary Language

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

Detection Details

HTML Lang Attribute:en
Text Length:472 chars
Detector Agreement:100%

Website Classification

Primary Category

technology software66% confidence
Type: static
Method: ml+structural

All Detected Categories

technology software
66%
documentation technical
53%
government public service
44%
adult content
34%
healthcare medical
32%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
564.29.17.3Aws · CLOUDUnited States
AS16509Amazon.com, Inc.
064.29.17.131Aws · CLOUDUnited States
AS16509Amazon.com, Inc.
0142.251.20.95Google · CDNUnited States
AS15169Google LLC
0104.17.24.14Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
0172.67.69.135Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
0216.198.79.131Aws · CLOUDUnited States
AS16509Amazon.com, Inc.
0216.198.79.3Aws · CLOUDUnited States
AS16509Amazon.com, Inc.
0104.26.9.218Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
58--

Detected Technologies2

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T194B2969BAAF70011A913B4B56BEB071A362AA00BD507CE183FDC5348CFC67D599627DC

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

192:U03F9ZIbuyrGc8cH1cW84PjanhYbQ9uj+ODpjcI9JaKDaXMpoBakLNyJRIIIVUlk:519ZIHOsIIIVUl010IW9KFdz

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:23886:YQoCAA5MADAEJAAiClIBgbZCFEIF9FFwCxKS5CJFAnagUhhDdNAEFgCoYA6pAQmiAgCKSAICoEY8BgE02AZkDGiEBDSEAgJZ

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:ffffe7efe7e7ffff
Perceptual Hash:b38ccc3333cc6633
Difference Hash:0010082a4c4c3008
Wavelet Hash:f0f0c8c0c0c0f0f0
Color Hash:#d0e06c

Other Hashes

Crop Resistant:0010082a4c4c3008

Scan History

Scan history not available

Unable to load historical scan data