Security Scan Report: bscscan-usdt-security2353.vercel.app

Submitted: Completed: publiccompleted
This website contacted 10 IPs in 1 country across 4 domains to perform 12 HTTP transactions. The main domain is vercel.app and was registered 6 years ago.

Submitted URL: https://bscscan-usdt-security2353.vercel.app/

AI Security Verdict

Confirmed Scam

Confidence: 90%

9
Risk Score

Wallet-drainer page impersonating BscScan/Trust Wallet on a throwaway vercel.app subdomain; a reported drainer domain that also embeds a Telegram bot token for exfiltration. Do not connect a wallet.

Risk Factors (6)
Wallet drainer reported on the primary domain (single-source, unverified but consistent with page content)
Impersonation of BscScan/Trust Wallet branding on a mismatched vercel.app subdomain
Telegram bot token embedded in inline script — exfiltration channel for harvested data
Wallet-address entry flow (Paste/Max/Next) designed to capture a user's USDT wallet details
Shared hosting platform tenant with unknown creation date and no domain reputation
Trust-building claims (“Trusted by 100K+ users”) on an anonymous subdomain
Domain age information unavailable

Details

Page Title

Transfer Trust Wallet

Scan Type

public

Domain Name Analysis

The domain 'bscscan-usdt-security2353.vercel.app' uses the application-focused generic top-level domain (.app); it also runs on subdomain 'bscscan-usdt-security2353'. Its registrable label 'vercel' stretches across 6 characters split between two vowels and four consonants. Tokenizing the label suggests 2 words: ver, cel. The median word length lands at 3 characters. No strong language cues emerged from the frequency lists.

Screenshot

BscScan Check About HowitWorks FAQ Scan Original * Trusted by 100K+ users worldwide Check Your USDT Wallet Security ‚Advanced blockchain analysis using official BSC Scan data to determine if your...

Page Load Overview

1.52s
Total Load Time
415 KB
Total Size

Language Analysis

Primary Language

🇺🇸English
Code: en
Confidence:54%
Script:Latin
Direction:ltr

Detection Details

Text Length:538 chars
Detector Agreement:75%

Website Classification

Primary Category

cryptocurrency blockchain53% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

cryptocurrency blockchain
53%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
3216.198.79.67Aws · CLOUDUnited States
AS16509Amazon.com, Inc.
1216.198.79.195Aws · CLOUDUnited States
AS16509Amazon.com, Inc.
1142.250.154.95Google · CDNUnited States
AS15169Google LLC
1104.16.179.112Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
1142.251.110.94Google · CDNUnited States
AS15169Google LLC
1216.198.79.3Aws · CLOUDUnited States
AS16509Amazon.com, Inc.
1142.251.20.95Google · CDNUnited States
AS15169Google LLC
1104.16.180.112Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
164.29.17.3Aws · CLOUDUnited States
AS16509Amazon.com, Inc.
1142.250.154.94Google · CDNUnited States
AS15169Google LLC
1210--

Detected Technologies3

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1CE32D43A20F51A2A501383A66BA6373B6EA5D107E60F8158B1EC03E14FC3F95DC6319C

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

192:zbJZpur2IIQSBmhxCsW7EL5s7TDY4EF0BNj:3pur2IIbqBeTc4Ek

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:11615:AAwAKQAiQhBgAgFhc0A5yAhiC5HKMHnHXAEICoCJAgOlqq6wkIoEBBMMDPZWEgxgBYSGHooBBQEYBFJAZAQAQBID4uaIYr0V

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:0018181800181800
Perceptual Hash:cc6373c862d9c966
Difference Hash:d432b23014b2b20c
Wavelet Hash:7a18ff3f18183c18
Color Hash:N/A

Scan History

Scan history not available

Unable to load historical scan data