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Security Scan Report: tronsca-n.github.io

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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/1b148586-e49f-4ee9-964b-e19a682d3790Domain and IP registration (RDAP)/api/v1/rdap/1b148586-e49f-4ee9-964b-e19a682d3790How often this domain was scanned/api/v1/domain/stats/tronsca-n.github.ioScan history for this domain/api/v1/domain/history/tronsca-n.github.io?limit=15
This website contacted 6 IPs in 1 country across 3 domains to perform 13 HTTP transactions. The main domain is github.io and was registered 13 years ago.

Submitted URL: https://tronsca-n.github.io/

AI Security Verdict

High Risk

Confidence: 72%

7
Risk Score

Typosquatted github.io subdomain (tronsca-n) reproducing TRONSCAN's official title and meta branding without affiliation. No forms, malware or Indicators of Compromise found, but the deceptive hostname supports brand impersonation.

Risk Factors (4)
Typosquatted hostname (tronsca-n) imitating the TRONSCAN brand on a non-official domain
Copied official title/meta branding with no affiliation disclosure
Free hosting-platform subdomain (github.io) whose actual creation date is unknown
Impermissible brand claim — the page styles itself as the official explorer
Domain age information unavailable

Details

Page Title

TRONSCAN | TRON BlockChain Explorer | 波场区块链浏览器

Scan Type

public

Domain Name Analysis

Within the British Indian Ocean Territory country-code top-level domain (.io), 'tronsca-n.github.io' is registered with subdomain 'tronsca-n'. The registrable portion 'github' spans 6 characters holding two vowels versus 4 consonants. Segmentation suggests three words: g, it, hub. Expect two characters per word on average. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://tronsca-n.github.io/

Page Load Overview

0.78s
Total Load Time
386 KB
Total Size

Language Analysis

Primary Language

🇺🇸English
Code: en
Confidence:50%
Script:Latin
Direction:ltr

Detection Details

Text Length:11,596 chars
Detector Agreement:100%

Website Classification

Primary Category

cryptocurrency blockchain93% confidence
Type: static
Method: ml+structural

All Detected Categories

cryptocurrency blockchain
93%
technology software
87%
cryptocurrency
30%
education learning
29%

Detected Features

Articles

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
3185.199.108.153Fastly · CDNUnited States
AS54113Fastly, Inc.
2185.199.110.153Fastly · CDNUnited States
AS54113Fastly, Inc.
2142.251.110.95Google · CDNUnited States
AS15169Google LLC
2192.178.183.94Google · CDNUnited States
AS15169Google LLC
2185.199.109.153Fastly · CDNUnited States
AS54113Fastly, Inc.
2185.199.111.153Fastly · CDNUnited States
AS54113Fastly, Inc.
136--

Detected Technologies8

X-UA-Compatible
100%
MetaGenerator
100%
Mobirisev6.1.12
50%
Bootstrap
50%
Varnish
40%
HSTS
40%
GitHub Pages
40%
Fastly
40%

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1C8C25122D8F3661A0E9448133D514B5E1F19900F661E17D1BBADC13CBF8A4D9AAB3B4F

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

768:SnCBD1x844GLS5g7po4Y5c1aWhSUXwIW1HgaTO90qe8iB:SnwkgUq8

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:26570:ugk4WgxEEUJoZsgFgcnWAuFBMKGHhIEIKAIwHEiFokBKwBCUsCB2mGToSIAQ8AQAkyMEAAqAGnST8cYEqDqEmEiQCAgx+AVC

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:010107f7070700ff
Perceptual Hash:a26adb15e464955d
Difference Hash:85893fa7ae3e3f4e
Wavelet Hash:c10107f7070f07ff
Color Hash:#40acbf

Other Hashes

Crop Resistant:85893fa7ae3e3f4e,3168c48282c46831,05897da7ae3e3e0e

Scan History

Scan history not available

Unable to load historical scan data