Security Scan Report: automatic-palm-tree-lilac.vercel.app

Submitted: Completed: publiccompleted
This website contacted 18 IPs in 1 country across 11 domains to perform 15 HTTP transactions. The main domain is vercel.app and was registered 6 years ago.

Submitted URL: https://automatic-palm-tree-lilac.vercel.app/

AI Security Verdict

Confirmed Scam

Confidence: 93%

10
Risk Score

Anonymous vercel.app page presenting only an email/password login, flagged by Google Safe Browsing for social engineering, with a Telegram bot token in its script — a credential-harvesting phishing page. Do not enter any credentials.

Risk Factors (6)
Google Safe Browsing social engineering / phishing detection on the scanned URL
Credential (password) capture form on an unauthenticated, unattributed hosting-platform subdomain
Telegram bot token in inline JavaScript enabling out-of-band credential exfiltration
Hidden form fields matching known credential-harvesting kit structure
IDS alerts for abused cloud hosting services and abused image-proxy domains in the request chain
No branding, no title, no ownership information anywhere on the page — pure credential intake
Domain age information unavailable

Details

Page Title

N/A

Scan Type

public

Domain Name Analysis

You're looking at domain 'automatic-palm-tree-lilac.vercel.app' on the application-focused generic top-level domain (.app) with subdomain 'automatic-palm-tree-lilac'. Its registrable label 'vercel' stretches across 6 characters split between two vowels and 4 consonants. Splitting it apart reveals two words: ver, cel. The median word length lands at three characters. No strong language cues emerged from the frequency lists.

Screenshot

Email Password Forgot password? >

Page Load Overview

0.68s
Total Load Time
371 KB
Total Size

Language Analysis

Primary Language

🇺🇸English
Code: en
Confidence:53%
Script:Latin
Direction:ltr

Detection Details

HTML Lang Attribute:已下架
Text Length:219 chars
Detector Agreement:100%
Language mismatch: Declared as 已下架 but detected as en

Website Classification

Primary Category

adult content28% confidence
Type: webapp
Method: ml+structural

All Detected Categories

adult content
28%
finance banking
28%
news media journalism
28%
government public service
27%

Detected Features

Login Form

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
3151.101.65.155Fastly · CDNUnited States
AS54113Fastly, Inc.
2104.17.24.14Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
1216.198.79.3Aws · CLOUDUnited States
AS16509Amazon.com, Inc.
1104.18.11.207Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
1104.21.26.223Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
1104.18.10.207Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
135.169.185.219Aws · CLOUDAshburn, Virginia, United States
AS14618Amazon.com, Inc.
064.29.17.131Aws · CLOUDUnited States
AS16509Amazon.com, Inc.
0142.251.127.95Google · CDNUnited States
AS15169Google LLC
0151.101.129.155Fastly · CDNUnited States
AS54113Fastly, Inc.
1518--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1B04484B0E20C20DA7336C44FBF81B6A962B5F369D5514DA6F21F6C5C4EC268611E2F39

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

1536:LIlMIpu80PxXE4YXJgndFTfy9lQOw/71gIuiHlqqm68lDbNBmbhqNyH6b2Ic7c1M:Ji8Px04YXGdFTyHQ/Z6whHMk00FX

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:260810:gIYJYUEzIQEoiWITJFMWMgEDg8sMTKAQgQJUNBKICptIDMFhghkojA4BIwR4egEZEFlGKQHeiAAsMsICZkICQDPkptiiLWBC

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:0018181818000000
Perceptual Hash:88cc3333337733cc
Difference Hash:4db3b3b3b34d3101
Wavelet Hash:2f1b1b1b1b070f0f
Color Hash:070000001c0

Scan History

Scan history not available

Unable to load historical scan data