ScanMalware.com

Security Scan Report: trez-soite-learn.zapier.app

Submitted: Completed: publiccompleted

Summary

API
This view is built from:
Scan result: counts, verdicts, details, IPs, technologies, hashes/api/v1/result/be704fea-52b2-4b78-a4ee-53481efe1214Domain and IP registration (RDAP)/api/v1/rdap/be704fea-52b2-4b78-a4ee-53481efe1214How often this domain was scanned/api/v1/domain/stats/trez-soite-learn.zapier.appScan history for this domain/api/v1/domain/history/trez-soite-learn.zapier.app?limit=15
This website contacted 11 IPs in 1 country across 1 domain to perform 1 HTTP transaction. The main domain is zapier.app and was registered 4 years 1 month ago.

Submitted URL: https://trez-soite-learn.zapier.app/help

The Cisco Umbrella rank of the primary domain is #78,534 of the top 1 million websites

AI Security Verdict

Safe Website

Confidence: 96%

0
Risk Score

No security concerns detected; site appears legitimate.

Safety Factors (5)
Well-established domain (>3 years)
Top 100k Cisco Umbrella ranking
Hosted on standard infrastructure (no IPFS or cloud storage)
No forms or data collection
No malicious Indicators of Compromise
Domain age information unavailable

Details

Page Title

Trézor Suite®|Get Started Trézorother network

Scan Type

public

Domain Name Analysis

The domain 'trez-soite-learn.zapier.app' uses the application-focused generic top-level domain (.app) with subdomain 'trez-soite-learn'. Its registrable label 'zapier' stretches across 6 characters with three vowels and 3 consonants. Tokenizing the label suggests two words: za, pier. The median word length lands at three characters. No strong language cues emerged from the frequency lists.

Screenshot

My Accounts if fase 00:40; * = = : —___—_, 2 Sond: 7 Rac. | *ageeaias are, 5381 935.36 KE ‘Soom ete $i 498.72 | RE.

Page Load Overview

8.17s
Total Load Time
N/A
Total Size

Language Analysis

Primary Language

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

Detection Details

HTML Lang Attribute:en
Text Length:777 chars
Detector Agreement:67%

Website Classification

Primary Category

technology software81% confidence
Type: static
Method: ml+structural

All Detected Categories

technology software
81%
documentation technical
59%
adult content
48%
education learning
34%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
1146.75.122.208United States
AS16509Amazon.com, Inc.
0172.217.16.195United States
AS16509Amazon.com, Inc.
0142.251.127.106United States
AS16509Amazon.com, Inc.
0216.58.206.74United States
AS16509Amazon.com, Inc.
03.174.46.85United States
AS16509Amazon.com, Inc.
013.33.187.12United States
AS16509Amazon.com, Inc.
064.239.123.193United States
AS16509Amazon.com, Inc.
0142.251.141.131United States
AS16509Amazon.com, Inc.
065.8.131.119United States
AS16509Amazon.com, Inc.
076.76.21.21United States
AS16509Amazon.com, Inc.
111--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T12A133A42BA1D21685E1797CDE4D2673EA017B053ADE2456DF24D005DB2C3BFB1ABAEC0

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

768:noPyKqn5Ocxksc64Jysq7v7dcISv0KrS9F57wdnukWW9+sBAukWW9+sB53u3WmL:o7Ax/c64Jysq7vunGt7YnLfhBALfhBRm

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:45563:IsJ8FDiigJIAwKBAFZEigQYBagoSsgQSY0tDWAGQCU0BHBJQcwWUhMDtIRkZGiRMlEUhAKSmoEyUuSjgRBAlAYBBh6sgR4IN

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:81010f0f0f070707
Perceptual Hash:b7496ee4d8b18195
Difference Hash:635d5a583c6d4c6d
Wavelet Hash:ff010f0f8f870707
Color Hash:N/A

Other Hashes

Crop Resistant:635d5a583c6d4c6d,991d593393d226a7,36274b72624c6636,c1d9d858bcadccec

Scan History

Scan history not available

Unable to load historical scan data