Security Scan Report: jup-rewards.vercel.app

Submitted: Jul 2, 2026, 1:50:09 AMCompleted: Jul 2, 2026, 1:51:43 AMpubliccompleted
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Summary

This website contacted 1 IP in 1 country across 1 domain to perform 2 HTTP transactions. The main domain is jup-rewards.vercel.app and was registered NaN years ago.

Submitted URL: https://jup-rewards.vercel.app/

AI Security Verdict

Safe Website

Confidence: 99%

0
Risk Score

AI analysis skipped: HTTP 451 error page with no meaningful content to analyze.

Safety Factors
Error/status page with no actionable content
No forms, scripts, or interactive elements detected
Domain age information unavailable

Details

Page Title

Deployment Unavailable

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

government public service

(56%)

Domain Information

The domain 'jup-rewards.vercel.app' uses the application-focused generic top-level domain (.app), featuring subdomain 'jup-rewards'. The core label 'vercel' covers 6 characters holding 2 vowels versus 4 consonants. It segments into two words: ver, cel. Median word length comes out to three characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://jup-rewards.vercel.app/

Page Load Overview

0.31s
Total Load Time
2
HTTP Requests
1
Domains
2 KB
Total Size

Language Analysis

Primary Language

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

Detection Details

Language Code:en
Detection Confidence:80%
Script Type:Latin
HTML Lang Attribute:en
Text Length:92 chars
Detector Agreement:50%

Website Classification

Primary Category

government public service56% confidence
Type: static
Method: ml+structural

All Detected Categories

government public service
56%
news media journalism
54%
cryptocurrency blockchain
54%
real estate property
53%
healthcare medical
53%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
2216.198.79.67United States
AS16509Amazon.com, Inc.
21--

Detected Technologies2

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1133194B745B1702EF23B88FE34E633686244811BC0920F59B658AFF8E2D7CA65023645

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

48:TGepXZ9S3dGNGDY7nnrm+AgJJ8EYpz7L0:TGi9ScnwEYL0

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:1651:AAAQAAAgQCIAJABAAEQAgAAAmAAAAAAAAAAAgCAgAgAAIAADAASACAAAAAAgACAAEAAQAAABAAAAGAAAQIBEAAgIggAIAIAB

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:ffffffe7e7ffffe7
Perceptual Hash:e699989966999999
Difference Hash:0000000c0c00000c
Wavelet Hash:3f3f3f27041c0c04
Color Hash:#d27991

Other Hashes

Crop Resistant:0000000c0c00000c

Scan History

Scan history not available

Unable to load historical scan data