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

Redirected to:
https://33d699cc.f00ae5aa62a9700f3d7a1922.workers.dev/
Site favicon
Submitted: Completed: publiccompleted
This website contacted 10 IPs in 1 country across 9 domains to perform 20 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

Moderate Risk

Confidence: 60%

4
Risk Score

Broken unknown-age Cloudflare Worker page with no forms or impersonation; only a single-source unverified phishing report on a third-party resource. Moderate risk, no credential theft observed.

Risk Factors (3)
Single-source unverified phishing report for third-party qr.codes resource
Unknown-age free workers.dev subdomain reached via cross-domain redirect
Cloudflare Worker exception and scanner-client mismatch on an unranked host
Safety Factors (5)
No credential, password, or payment forms detected
No brand impersonation detected
No JavaScript YARA malware matches
No known malicious kit or high-precision YARA hits
No cross-origin credential exfiltration detected
Domain age information unavailable

Details

Page Title

Mutifactor Auth

Scan Type

public

Domain Name Analysis

The domain name 'eoknglwe.an.r.appspot.com' uses the commercial generic top-level domain (.com); it also runs on subdomain 'eoknglwe.an.r'. The registrable portion 'appspot' spans 7 characters split between 2 vowels and five consonants. Breaking it apart gives 2 words: app, spot. The median word length lands at 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

1.51s
Total Load Time
238 KB
Total Size

Language Analysis

Primary Language

🏳️UNKNOWN
Code: unknown
Confidence:0%

Detection Details

Text Length:15 chars
Detector Agreement:0%

Website Classification

Primary Category

technology software40% confidence
Type: static
Method: ml+structural+ocr_tiebreaker

All Detected Categories

technology software
40%
documentation technical
27%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
2142.251.14.153Google · CDNUnited States
AS15169Google LLC
2188.114.96.9Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
2104.20.41.165Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
252.216.54.73Aws · CLOUDAshburn, Virginia, United States
AS16509Amazon.com, Inc.
2142.251.110.153Google · CDNUnited States
AS15169Google LLC
2188.114.97.9Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
2172.66.172.247Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
252.216.214.129Aws · CLOUDAshburn, Virginia, United States
AS16509Amazon.com, Inc.
2142.250.154.95Google · CDNUnited States
AS15169Google LLC
2142.251.110.94Google · CDNUnited States
AS15169Google LLC
2010--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T15C21AAB310B1440A23016141FD95F02DCCAEE10B8AE96C61F4DA123E6FE4EE1459FA9E

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

24:kEwZruGY9PhOh3y3AWgGTRHiNiPMbVZaiPABqaiPWRaiP1ino0VG:wr2/ECZDUikbbai4BqaieRait0or

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:1412:gBAAAABEAAAAAAQBhAAAEAAAEAAAAACAACAEAAAAAAACAAAAAAAAAABBAAABAAAQAAEAACAWCAAhAAgAgAAAAAAIAAgBACAA

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:3c34360c00000000
Wavelet Hash:838783c3f0f0f0f0
Color Hash:#1f8293

Other Hashes

Crop Resistant:3c34360c00000000

Scan History

Scan history not available

Unable to load historical scan data