Security Scan Report: graph-fallback.oculus.com

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Submitted: Dec 5, 2025, 5:43:11 AMCompleted: Dec 5, 2025, 5:44:49 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-fallback.oculus.com and was registered NaN years ago.

Submitted URL: https://graph-fallback.oculus.com/

The Cisco Umbrella rank of the primary domain is #12,854 of the top 1 million websites

AI Security Verdict

Safe Website

Confidence: 96%

0
Risk Score

No security concerns detected; the site appears legitimate.

Safety Factors
Well‑established domain
High Cisco Umbrella ranking
No forms collecting credentials or payment data
No phishing or malware indicators
Domain age information unavailable

Details

Page Title

N/A

Scan Type

public

Language

🇺🇸

English

(66% confidence)

Category

suspicious phishing

(50%)

Domain Information

The domain 'graph-fallback.oculus.com' uses the commercial generic top-level domain (.com) with subdomain 'graph-fallback'. The second-level label 'oculus' is 6 characters long split between three vowels and 3 consonants. Word splitting yields 1 word: oculus. The median word length lands at six characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://graph-fallback.oculus.com/

Page Load Overview

0.15s
Total Load Time
2
HTTP Requests
1
Domains
0 KB
Total Size

Language Analysis

Primary Language

🇺🇸English
Code: en
Confidence:66%
Script:Latin
Direction:ltr

Detection Details

Language Code:en
Detection Confidence:66%
Script Type:Latin
Text Length:211 chars
Detector Agreement:100%

Website Classification

Primary Category

suspicious phishing50% confidence
Type: static
Method: ml+structural+ocr_tiebreaker

All Detected Categories

suspicious phishing
50%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
257.144.223.141Amsterdam, North Holland, Netherlands
AS32934FACEBOOK
12a03:2880:f36f:18d:face:b00c:0:32c2Amsterdam, North Holland, Netherlands
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

T1A0E0C032C4A00E135163A4EC58D1A100AAD1711B4C305D857ECCA06C9FDEC2ACC132C4

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

6:qzxV/5VHHQYk/B96AAD/YIqkVg5YaidyeREH+8fAzDMBY0YNdxELa:kxV7HfAAEISeREHKMBzY7xELa

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:1:0:752001611a9ad28681d62fff117ab024

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:83030303077f7e7f
Difference Hash:c0c0000000000000
Wavelet Hash:003ff0f000000000
Color Hash:#2d5b86

Other Hashes

Crop Resistant:c0c0000000000000

Scan History

Scan history not available

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