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Security Scan Report: www.institutmontaigne.org

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Submitted: Jul 5, 2026, 1:00:12 PMCompleted: Jul 5, 2026, 1:01:45 PMpubliccompleted

Summary

This website contacted 5 IPs in 3 countries across 6 domains to perform 3 HTTP transactions. The main domain is institutmontaigne.org and was registered NaN years ago.

Submitted URL: https://www.institutmontaigne.org/en/expressions/donald-trump-inevitable-winner-upcoming-midterm-elections

AI Security Verdict

Low Risk

Confidence: 85%

3
Risk Score

The site appears legitimate, showing its own brand, no credential collection, and no malicious indicators.

Safety Factors
Established domain with >25 years of age
Physical address visible on site
Self‑branding aligns with domain
No external form submissions or credential exfiltration
No IDS or network alerts
Verdict cited a credential/login form, but DOM analysis found no password field (real or disguised) or payment field, and no other hard signal — credential-phishing framing unsupported; risk adjusted from 5 to 3
Domain age information unavailable

Details

Page Title

Donald Trump, Inevitable Winner of the Upcoming Midterm Elections? | Institut Montaigne

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

corporate

(50%)

Domain Information

Domain 'www.institutmontaigne.org' uses the non-profit oriented generic top-level domain (.org), featuring subdomain 'www'. Its registrable label 'institutmontaigne' stretches across 17 characters holding seven vowels versus ten consonants. Segmentation suggests 2 words: institut, montaigne. Median word length comes out to 8.5 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://www.institutmontaigne.org/en/expressions/donald-trump-inevitable-winner-upcoming-midterm-elections

Page Load Overview

1.61s
Total Load Time
42
HTTP Requests
12
Domains
531 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:6,103 chars
Detector Agreement:100%

Website Classification

Primary Category

corporate50% confidence
Type: dynamic
Method: structural

All Detected Categories

corporate
50%
news/blog
40%

Detected Features

Articles
OG: website

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
10195.60.188.75France
AS39104Oxeva SAS
8142.251.13.97Google · CDNUnited States
AS15169Google LLC
8142.251.13.95Google · CDNUnited States
AS15169Google LLC
851.68.111.231France
AS16276OVH SAS
8184.24.77.144Frankfurt am Main, Hesse, Germany
AS20940Akamai International B.V.
425--

Page Statistics

42
Requests
12
Unique Domains
537.4 KB
Total Size

Detected Technologies8

Open-Graph-Protocolvwebsite
100%
MetaGenerator
100%
Google-AnalyticsvUniversal
100%
Drupalv11
60%
PHP
50%
Google Analytics
35%
Typekit
30%
Adobe Fonts
30%

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1FA13B63366412137421745D6B1B6E78EE3B3C14EDD9B0A51B2FCD3A80FE3D568D2268A

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

384:w2SU51QtzeY5vgR6WulejQ1K3O2TMwmoO8A7VRYcj+NJMbOVdmG11EH:wrTtzePR6WulejmK3YoAY3JLVsG11EH

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:42263:tERAELDBECGcczjRgATHAIWhgAOQBb7KMUzBJdHKFEgmhyeAEAAhxClCF2pKNAQQCRFIQqMADgiJBCDoxyECKPdwopCJqkAu

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:ff0000000a0af9ff
Perceptual Hash:8916ea15ecea91ec
Difference Hash:ced1d9b6d6da6b43
Wavelet Hash:ff0040007a0affff
Color Hash:#79d292

Other Hashes

Crop Resistant:ced1d9b6d6da6b43,c68cf0dbdae46871,c1d1d9a6d6da8a63

Scan History

Scan history not available

Unable to load historical scan data