Security Scan Report: rstatic.restaurants.applebees.com

Submitted: Jan 12, 2026, 2:16:34 PMCompleted: Jan 12, 2026, 2:18:24 PMpubliccompleted
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Summary

This website contacted 1 IP in 1 country across 1 domain to perform 1 HTTP transaction. The main domain is rstatic.restaurants.applebees.com and was registered NaN years ago.

Submitted URL: https://rstatic.restaurants.applebees.com

The Cisco Umbrella rank of the primary domain is #63,353 of the top 1 million websites

AI Security Verdict

Safe Website

Confidence: 95%

0
Risk Score

Legitimate site with no detected security concerns.

Safety Factors
Well-established domain with long registration history
Hosted on standard infrastructure, not IPFS or cloud storage
Subdomain belongs to a known legitimate brand
No suspicious content or phishing indicators
Domain age information unavailable

Details

Page Title

Test Page for the Apache HTTP Server

Scan Type

public

Language

🇺🇸

English

(59% confidence)

Category

unknown

(0%)

Domain Information

Domain 'rstatic.restaurants.applebees.com' uses the commercial generic top-level domain (.com) with subdomain 'rstatic.restaurants'. The core label 'applebees' covers 9 characters containing 4 vowels alongside 5 consonants. Tokenizing the label suggests two words: apple, bees. Expect 4.5 characters per word on average. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://rstatic.restaurants.applebees.com

Page Load Overview

26.89s
Total Load Time
3
HTTP Requests
1
Domains
8 KB
Total Size

Language Analysis

Primary Language

🇺🇸English
Code: en
Confidence:59%
Script:Latin
Direction:ltr

Detection Details

Language Code:en
Detection Confidence:59%
Script Type:Latin
Text Length:1,242 chars
Detector Agreement:100%

Website Classification

Primary Category

unknown0% confidence
Type: static
Method: structural

All Detected Categories

No categories detected

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
318.213.140.159Ashburn, Virginia, United States
AS14618AMAZON-AES
31--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1EE7161E65F8C0626020D90D6F5A877D4522EC076CB678AA7FE1EA235C7C591C06BA3E4

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

48:zDhhv1h0aK+0abqa8Iw29aQWCaEkaZv1CaBka4aKhTfTCKp8LAJNLhPA099pG3qf:hzUIw2PxzGTxNPA0pGaf

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:3619:AAGDgTYAEBAQiwBAAAGAQgAAhgIFgEAAggAQQCAAmIYoQAAAEGAAAUAAoAiAAACAApYAAgAAQAACEgNBBSEgIBYBAAASAJUA

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:00fb1bffffffffff
Perceptual Hash:ad2d2d7676505919
Difference Hash:5677f30002000000
Wavelet Hash:000009ff00000000
Color Hash:#d27a2d

Other Hashes

Scan History

Scan history not available

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