Security Scan Report: project-dapp.vercel.app

Redirected to:
https://project-dapp.vercel.app/
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Submitted: Jul 25, 2026, 4:51:46 AMCompleted: Jul 25, 2026, 4:52:56 AMpubliccompleted

This website contacted 1 IP in 1 country across 2 domains to perform 8 HTTP transactions. The main domain is project-dapp.vercel.app and was registered 6 years ago.

Submitted URL: http://project-dapp.vercel.app

Effective URL:

https://project-dapp.vercel.app/
Redirected

AI Security Verdict

High Risk

Confidence: 65%

7
Risk Score

The site shows no credential collection or malware but has an unverified threat‑intel flag and unknown subdomain age, warranting moderate risk.

Risk Factors (3)
Unverified threat‑intel indicator
Unknown subdomain age on a hosting platform
Unranked / low‑reputation domain
Domain age information unavailable

Details

Page Title

ProjectDappsMainNet

Scan Type

public

Domain Name Analysis

Domain 'project-dapp.vercel.app' uses the application-focused generic top-level domain (.app), featuring subdomain 'project-dapp'. The second-level label 'vercel' is 6 characters long holding two vowels versus 4 consonants. Tokenizing the label suggests 2 words: ver, cel. Median word length is 3 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of http://project-dapp.vercel.app

Page Load Overview

1.26s
Total Load Time
1.3 MB
Total Size

Language Analysis

Primary Language

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

Detection Details

HTML Lang Attribute:en
Text Length:1,912 chars
Detector Agreement:100%

Website Classification

Primary Category

finance banking94% confidence
Type: static
Method: ml+structural

All Detected Categories

finance banking
94%
cryptocurrency blockchain
94%
government public service
93%
documentation technical
92%
technology software
82%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
864.29.17.3United States
AS16509Amazon.com, Inc.
81--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T196520C60B0F01B2741E3D8E2B6613766AE9FDA17C46BC015BBEC86CA4F89D50CD4F265

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

96:ngoGAdJls650KQtFls6CK2IBZliZErZ6UZO9JpZk+ZwD2m+Z8QZipZ+RZvheZ8Ra:xGCXsp9smoUandVvsV

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:14278:gCgYAEAgMMIpFAlQcQUHCakK18AGIABenhkAEAQKQECDZS0HCECcSw0KBFCgKmgNICKkioBEgAVRMIaBUECAQwASpOYMLlJA

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:ff0078797979281c
Perceptual Hash:c994b6b18cc5c1be
Difference Hash:f479e3e3e3d3d3f1
Wavelet Hash:ff00787979791911
Color Hash:#ac5365

Scan History

Scan history not available

Unable to load historical scan data