Security Scan Report: catalist-marketing-git-dev-danmalarkeys-projects.vercel.app

Redirected to:
https://vercel.com/login?next=%2Fsso-api%3Furl%3Dhttps%253A%252F%252Fc...
Site favicon
Submitted: Completed: publiccompleted
This website contacted 8 IPs in 1 country across 7 domains to perform 136 HTTP transactions. The main domain is vercel.app and was registered 6 years ago.

Submitted URL: https://catalist-marketing-git-dev-danmalarkeys-projects.vercel.app/

Effective URL:
https://vercel.com/login?next=%2Fsso-api%3Furl%3Dhttps%253A%252F%252Fc...
Redirected

AI Security Verdict

Safe Website

Confidence: 92%

0
Risk Score

Vercel's own SSO gate on vercel.com, reached via redirect from a preview deployment. Brand and domain match; no phishing, malware or credential-exfiltration signals. The two IDS hits are generic cloud-hosting abuse tags.

Safety Factors (3)
Final destination is vercel.com, the legitimate operator of the vercel.app namespace, with matching branding and standard SSO/OAuth login options.
No forms harvest credentials for a third party; no payment fields; no obfuscated or malicious JavaScript.
No Indicators of Compromise, no Safe Browsing or IDS phishing/malware alerts against the content served.
Domain age information unavailable

Details

Page Title

Login – Vercel

Scan Type

public

Domain Name Analysis

Within the application-focused generic top-level domain (.app), 'catalist-marketing-git-dev-danmalarkeys-projects.vercel.app' is registered and includes subdomain 'catalist-marketing-git-dev-danmalarkeys-projects'. Its registrable label 'vercel' stretches across 6 characters split between two vowels and four consonants. Word splitting yields 2 words: ver, cel. The median word length lands at 3 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://catalist-marketing-git-dev-danmalarkeys-projects.vercel.app/

Page Load Overview

6.95s
Total Load Time
2.1 MB
Total Size

Language Analysis

Primary Language

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

Detection Details

HTML Lang Attribute:en-US
Text Length:255 chars
Detector Agreement:100%

Website Classification

Primary Category

technology software68% confidence
Type: spa
Method: ml+structural

All Detected Categories

technology software
68%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
1764.239.123.129Aws · CLOUDUnited States
AS16509Amazon.com, Inc.
17216.198.79.67Aws · CLOUDUnited States
AS16509Amazon.com, Inc.
17142.251.127.84Google · CDNUnited States
AS15169Google LLC
1764.239.109.129Aws · CLOUDUnited States
AS16509Amazon.com, Inc.
1734.160.81.0Google · CDNKansas City, Missouri, United States
AS396982Google LLC
1764.29.17.131Aws · CLOUDUnited States
AS16509Amazon.com, Inc.
1764.239.109.65Aws · CLOUDUnited States
AS16509Amazon.com, Inc.
17142.251.14.139Google · CDNUnited States
AS15169Google LLC
1368--

Detected Technologies7

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1A2748329E105ED69ECEB6C4F227DAC3B264EA1B3DD81ECB4D4D8C91941C6075A792FC0

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

3072:mQST8+OJTgQKMQV8X79viE7Orijq6vJMNsMQurinq6PJMdE/QceY:mQSdPFuQcT

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:346496:gLQADQhnGkgwEcI0AJIFBqgIBUUkBAxAEG2AwI7WAAQJcFQ4pgmJCsVLKGUCHAhIqQELAIOIVABBYRqBwhKQaKKMaSJEggQS

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:ffffe7e7e7e7ffff
Perceptual Hash:b3268c88d9336677
Difference Hash:80284d4c080c0800
Wavelet Hash:60e0e0e0e3e3c7c7
Color Hash:#c3c587

Other Hashes

Crop Resistant:80284d4c080c0800

Scan History

Scan history not available

Unable to load historical scan data