Security Scan Report: eoknglwe.an.r.appspot.com

Redirected to:
https://33d699cc.f00ae5aa62a9700f3d7a1922.workers.dev/
Submitted: Completed: publiccompleted
This website contacted 4 IPs in 1 country across 8 domains to perform 18 HTTP transactions. The main domain is appspot.com and was registered 21 years ago.

Submitted URL: https://eoknglwe.an.r.appspot.com/

Effective URL:
https://33d699cc.f00ae5aa62a9700f3d7a1922.workers.dev/
Redirected

AI Security Verdict

AI analysis unavailable for this scan

Details

Page Title

Worker threw exception | 33d699cc.f00ae5aa62a9700f3d7a1922.workers.dev | Cloudflare

Scan Type

public

Domain Name Analysis

Within the commercial generic top-level domain (.com), 'eoknglwe.an.r.appspot.com' is registered, featuring subdomain 'eoknglwe.an.r'. The second-level label 'appspot' is 7 characters long containing 2 vowels alongside five consonants. It segments into 2 words: app, spot. Median word length is 3.5 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://eoknglwe.an.r.appspot.com/

Page Load Overview

1.73s
Total Load Time
226 KB
Total Size

Language Analysis

Primary Language

🇺🇸English
Code: en
Confidence:80%
Script:Latin
Direction:ltr

Detection Details

HTML Lang Attribute:en-US
Text Length:662 chars
Detector Agreement:100%

Website Classification

Primary Category

technology software55% confidence
Type: static
Method: ml+structural

All Detected Categories

technology software
55%
documentation technical
36%
cryptocurrency blockchain
31%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
6188.114.96.3Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
416.182.69.209Aws · CLOUDAshburn, Virginia, United States
AS16509Amazon.com, Inc.
4142.251.127.153Google · CDNUnited States
AS15169Google LLC
4104.20.41.165Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
184--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T149915136BAFD507F006392A266AE630D79A1D023CAB7059037AD82751F9AE16FD13280

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

96:ljQDa/D+DMFGakaUE9xr4eyFOQnRC3vaQxnby:lj0a/SoGjaUE9tyOQnM3Ceby

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:4414:IGIAhACggGYQCIQAQFACBAAxQQEoAUAAAACwAAMJEgFMAEiQAwIACIAADIKAwAUECKMKYEAgRkGEBAgBQIDFJQAJAYAgAAAA

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:87c783e7ffffffff
Perceptual Hash:bc38389b93636c6c
Difference Hash:3c34361c00000000
Wavelet Hash:808480c0f0f0f0f0
Color Hash:#59d22d

Other Hashes

Crop Resistant:3c34361c00000000

Scan History

Scan history not available

Unable to load historical scan data