Security Scan Report: meet.goto.com

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Submitted: Nov 5, 2025, 9:02:37 AMCompleted: Nov 5, 2025, 9:04:31 AMpubliccompleted
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Summary

This website contacted 13 IPs in 1 country across 7 domains to perform 17 HTTP transactions. The main domain is meet.goto.com and was registered NaN years ago.

Submitted URL: https://meet.goto.com/919543045

AI Security Verdict

Safe Website

Confidence: 95%

0
Risk Score

Legitimate GoTo meeting page with no security concerns.

Safety Factors
Established domain with decades of age
Official brand subdomain (meet.goto.com)
No suspicious redirects or URL manipulation
Domain age information unavailable

Details

Page Title

GoTo

Scan Type

public

Language

🇺🇸

English

(50% confidence)

Category

adult content

(55%)

Domain Information

Domain 'meet.goto.com' uses the commercial generic top-level domain (.com), featuring subdomain 'meet'. The second-level label 'goto' is 4 characters long with two vowels and two consonants. Segmentation suggests one word: goto. Average segment length settles at 4 characters. Most frequently, 'goto' shows up in English. You will also see it in French and Indonesian contexts.

Screenshot

Security scan screenshot of https://meet.goto.com/919543045

Page Load Overview

73.45s
Total Load Time
17
HTTP Requests
7
Domains
32 KB
Total Size

Language Analysis

Primary Language

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

Detection Details

Language Code:en
Detection Confidence:50%
Script Type:Latin
HTML Lang Attribute:en-US
Text Length:2,760 chars
Detector Agreement:100%

Website Classification

Primary Category

adult content55% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

adult content
55%
cryptocurrency blockchain
55%
documentation technical
54%
healthcare medical
52%
technology software
49%

Detected Features

OG: website

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
535.186.247.156United States
AS396982GOOGLE-CLOUD-PLATFORM
1150.136.248.95Ashburn, Virginia, United States
AS31898ORACLE-BMC-31898
134.120.195.249Kansas City, Missouri, United States
AS396982GOOGLE-CLOUD-PLATFORM
118.245.86.19United States
AS16509AMAZON-02
144.238.178.41Boardman, Oregon, United States
AS16509AMAZON-02
118.245.86.99United States
AS16509AMAZON-02
113.33.187.53New York, New York, United States
AS16509AMAZON-02
118.245.86.33United States
AS16509AMAZON-02
113.33.187.50New York, New York, United States
AS16509AMAZON-02
118.245.86.29United States
AS16509AMAZON-02
1713--

Detected Technologies5

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1352262B70E1560ACD7F4D39BA854B28C6026F3298583EDD96671C2EFD7D4FA32060A5C

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

96:nciioLD6bGWD4QynLN1wyG5CXtUMzoqneFvhcLxk4QgK7N6JpXrrycc8uU11vEWA:uorWGn16Edyv8ggXHVDSr

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:10397:DAEtZFCKBRW1ooABEIIu5ABVRIhA4MdCoCg1ANBGg5pCSDBAtgYqAEMhAAiIEggIpTqgcAYBIAgCWM2iFAogamRhRyACXO0h

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:0000000000000000
Perceptual Hash:a200880022008800
Difference Hash:0000000000000000
Wavelet Hash:0f0f1f07e0f8f0f0
Color Hash:#1f933a

Other Hashes

Crop Resistant:0000000000000000

Scan History

Scan history not available

Unable to load historical scan data