Security Scan Report: graph.whatsapp.net

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Submitted: Dec 6, 2025, 6:43:26 AMCompleted: Dec 6, 2025, 6:45:08 AMpubliccompleted
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Summary

This website contacted 2 IPs in 1 country across 1 domain to perform 2 HTTP transactions. The main domain is graph.whatsapp.net.

Submitted URL: https://graph.whatsapp.net/

The Cisco Umbrella rank of the primary domain is #341 of the top 1 million websitesTop 1K Site

AI Security Verdict

Safe Website

Confidence: 95%

0
Risk Score

Legitimate site displaying an API error; no security concerns detected.

Safety Factors
High Cisco Umbrella ranking indicating reputable domain
Known brand (WhatsApp) domain
Absence of credential or payment collection
Domain age information unavailable

Details

Page Title

N/A

Scan Type

public

Language

🇩🇪

German

(50% confidence)

Category

suspicious phishing

(35%)

Domain Information

The domain name 'graph.whatsapp.net' uses the network infrastructure generic top-level domain (.net), featuring subdomain 'graph'. Its registrable label 'whatsapp' stretches across 8 characters containing 2 vowels alongside 6 consonants. Segmentation suggests three words: what, s, app. Median word length comes out to 3 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://graph.whatsapp.net/

Page Load Overview

0.19s
Total Load Time
2
HTTP Requests
1
Domains
0 KB
Total Size

Language Analysis

Primary Language

🇩🇪German
Code: de
Confidence:50%
Script:Latin
Direction:ltr

Detection Details

Language Code:de
Detection Confidence:50%
Script Type:Latin
Text Length:204 chars
Detector Agreement:100%

Website Classification

Primary Category

suspicious phishing35% confidence
Type: static
Method: ml+structural

All Detected Categories

suspicious phishing
35%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
2157.240.0.60Frankfurt am Main, Hesse, Germany
AS32934FACEBOOK
12a03:2880:f277:1cd:face:b00c:0:167Frankfurt am Main, Hesse, Germany
AS32934FACEBOOK
22--

Detected Technologies1

40%

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T18AE0D872C0E04D6B02B715DEAD84D24465D4B11B6C242D16BACCE19CCFCDB2AC413285

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

6:qzxV/5VHHQYk/B96AAD/Y6M7r2REEOVSAve/FpWaWA0PVbiYvY0YNdxELa:kxV7HfAAEn7r2RPpFpad+CzY7xELa

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:1:0:f4ae5766a3e85256d6293a81bf3eb5c6

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:003fffffffffffff
Perceptual Hash:83030307077f7e7e
Difference Hash:e0c0000000000000
Wavelet Hash:003fcfcf00000000
Color Hash:#2d5b86

Other Hashes

Crop Resistant:e0c0000000000000

Scan History

Scan history not available

Unable to load historical scan data