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Security Scan Report: ucaihong.pages.dev

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Submitted: Completed: publiccompleted

Summary

API
This view is built from:
Scan result: counts, verdicts, details, IPs, technologies, hashes/api/v1/result/53d619f0-74a1-438f-973c-f5434ba15176Domain and IP registration (RDAP)/api/v1/rdap/53d619f0-74a1-438f-973c-f5434ba15176How often this domain was scanned/api/v1/domain/stats/ucaihong.pages.devScan history for this domain/api/v1/domain/history/ucaihong.pages.dev?limit=15
This website contacted 27 IPs in 4 countries across 26 domains to perform 100 HTTP transactions. The main domain is pages.dev and was registered 6 years ago.

Submitted URL: https://ucaihong.pages.dev/go/trip-camping-outdoors-lead-american-leisure/

AI Security Verdict

Low Risk

Confidence: 80%

2
Risk Score

The page is an informational article with no credential collection or malicious code; risk is low.

Risk Factors (2)
Unranked domain (ucaihong.pages.dev)
Unknown subdomain creation date
Safety Factors (3)
No credential or payment collection
No malicious JavaScript or exfiltration behavior
Content is informational article with no phishing or malware indicators
Domain age information unavailable

Details

Page Title

露营和户外引领美国休闲 同志伴侣和LGBT家庭参与最活跃 - 彩虹网 | 彩虹INFO - 彩虹门户 彩虹之家

Scan Type

public

Domain Name Analysis

You're looking at domain 'ucaihong.pages.dev' on the developer-focused generic top-level domain (.dev), featuring subdomain 'ucaihong'. Its registrable label 'pages' stretches across 5 characters split between 2 vowels and 3 consonants. Word splitting yields 1 word: pages. Average segment length settles at 5 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://ucaihong.pages.dev/go/trip-camping-outdoors-lead-american-leisure/

Page Load Overview

1.92s
Total Load Time
2.0 MB
Total Size

Language Analysis

Primary Language

🇨🇳Chinese
Code: zh
Confidence:60%
Script:Han
Direction:ltr

Detection Details

HTML Lang Attribute:zh-cn
Text Length:890 chars
Detector Agreement:60%

Website Classification

Primary Category

adult content38% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

adult content
38%
news/blog
30%

Detected Features

Search
Articles
Comments
OG: article

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
22188.114.97.9Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
3142.251.110.97Google · CDNUnited States
AS15169Google LLC
3104.21.23.80Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
3142.251.110.156Google · CDNUnited States
AS15169Google LLC
337.252.171.21Frankfurt am Main, Hesse, Germany
AS29990Xandr Inc.
3143.204.181.74Cloudfront · CDNUnited States
AS16509Amazon.com, Inc.
3151.101.128.134Fastly · CDNUnited States
AS54113Fastly, Inc.
3143.204.181.26Cloudfront · CDNUnited States
AS16509Amazon.com, Inc.
3142.250.154.157Google · CDNUnited States
AS15169Google LLC
3188.114.96.9Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
10027--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T126817663D682ACCD429161A3017BB14CD13B874FD871AC7175DD11AF1FA1E21CAF3618

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

96:zE78t3+la6WSy0CurpcjsJeX+SvlSzKiXrXE:zE78clLWSy0CkJeX+SvlVErXE

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:3845:gEEQhGAAImAAAEkAoAkIBgAGBMAJhhCFQAARAAAASoBREBAgCAAAYAABOBYCAMyAAAA8UAAAkACBIAjlEEDAAAASAUASAAwI

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:ff00dfdfffffb3ff
Perceptual Hash:bc110e8ee6bcd1cc
Difference Hash:201c322636222626
Wavelet Hash:ff008a83b39f9383
Color Hash:#672dd2

Other Hashes

Crop Resistant:201c322636222626,0111c9c9c9410101

Scan History

Scan history not available

Unable to load historical scan data