Security Scan Report: metamask-docs-75mpj2s96-consensys-ddffed67.vercel.app

Site favicon
Submitted: Completed: publiccompleted
This website contacted 36 IPs in 3 countries across 21 domains to perform 461 HTTP transactions. The main domain is vercel.app and was registered 6 years ago.

Submitted URL: https://metamask-docs-75mpj2s96-consensys-ddffed67.vercel.app/smart-accounts-kit/get-started/use-skills/

AI Security Verdict

High Risk

Confidence: 74%

7
Risk Score

Unofficial vercel.app clone of MetaMask developer docs with four single-source phishing reports against the host. No credential forms found, but brand impersonation plus threat-intel matches make it unsafe to trust.

Risk Factors (4)
Brand impersonation of MetaMask documentation on a non-official Vercel subdomain
Multiple single-source phishing threat-intelligence reports on the primary domain and its URLs
Unknown creation date for the subdomain on an instant-publish hosting platform, with a randomized opaque hostname
Circular redirect observed during the capture
Domain age information unavailable

Details

Page Title

Use skills | MetaMask developer documentation

Scan Type

public

Domain Name Analysis

Within the application-focused generic top-level domain (.app), 'metamask-docs-75mpj2s96-consensys-ddffed67.vercel.app' is registered with subdomain 'metamask-docs-75mpj2s96-consensys-ddffed67'. The second-level label 'vercel' is 6 characters long split between two vowels and four consonants. It segments into 2 words: ver, cel. Average segment length settles at three characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://metamask-docs-75mpj2s96-consensys-ddffed67.vercel.app/smart-accounts-kit/get-started/use-skills/

Page Load Overview

8.94s
Total Load Time
3.4 MB
Total Size

Language Analysis

Primary Language

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

Detection Details

HTML Lang Attribute:en
Text Length:4,496 chars
Detector Agreement:60%

Website Classification

Primary Category

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

All Detected Categories

technology software
62%
documentation technical
59%
cryptocurrency blockchain
50%
corporate
35%

Detected Features

OG: website
Schema.org

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
4164.29.17.131Aws · CLOUDUnited States
AS16509Amazon.com, Inc.
1264.29.17.195Aws · CLOUDUnited States
AS16509Amazon.com, Inc.
12104.17.208.5Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
1264.239.109.193Aws · CLOUDUnited States
AS16509Amazon.com, Inc.
12142.251.20.97Google · CDNUnited States
AS15169Google LLC
12146.75.121.55Fastly · CDNFrankfurt am Main, Hesse, Germany
AS54113Fastly, Inc.
123.174.47.131Cloudfront · CDNUnited States
AS16509Amazon.com, Inc.
12104.18.31.173Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
12104.16.140.209Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
12104.17.223.152Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
46136--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1C1C3D8399160487E182B7BC3AD55A3F8E147728EC53592B4F3BD4B39AF41F9241278A3

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

1536:C/H58CTs9OUSa90Gr7wUewYz7Z7LHPDzuKPDsTVM:CP58CTsn7wPDdPDcVM

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:118193:iRkRFJGEJkSUEB00yhCACHdwUKaICGESCxU1QIEEICAEQABHjIpPFOA+AkKwKAUBEkjQGAmJkRISIggGDE2MKAkjapQlABnu

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:7effff8383ffff83
Perceptual Hash:bcc2d2c27d82d393
Difference Hash:e8b3b02626dc2c36
Wavelet Hash:241f9f038387ff82
Color Hash:#61d22d

Other Hashes

Scan History

Scan history not available

Unable to load historical scan data