Security Scan Report: which.lol

Redirected to: https://s0cial.com/?utm_source=which.lol&utm_medium=referral&utm_campaign=lol_network

Submitted: Jan 23, 2026, 9:41:16 PMCompleted: Jan 23, 2026, 9:41:43 PMpubliccompleted
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Summary

This website contacted 3 IPs in 2 countries across 3 domains to perform 1 HTTP transaction. The main domain is s0cial.com and was registered NaN years ago.

Submitted URL: https://which.lol/

Effective URL: https://s0cial.com/?utm_source=which.lol&utm_medium=referral&utm_campaign=lol_networkRedirected

AI Security Verdict

Safe Website

Confidence: 95%

0
Risk Score

No security concerns detected; site appears legitimate.

Safety Factors
Well‑established domain with long registration history
No forms collecting sensitive data
No malicious Indicators of Compromise
No detected malware or suspicious scripts
Meta information consistent with a non‑commercial movement site
Domain age information unavailable

Details

Website Access Blocked

This website blocked our scanner, likely using AWS WAF, Cloudflare, or similar bot protection. The page may show differently for regular users.

Page Title

Attention Required! | Cloudflare

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

social media network

(99%)

Domain Information

Within the .lol top-level domain, 'which.lol' is registered and has no subdomain. The registrable portion 'which' spans 5 characters containing 1 vowel alongside 4 consonants. Splitting it apart reveals 1 word: which. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://which.lol/

Page Load Overview

6.90s
Total Load Time
64
HTTP Requests
12
Domains
115 KB
Total Size

Language Analysis

Primary Language

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

Detection Details

Language Code:en
Detection Confidence:80%
Script Type:Latin
HTML Lang Attribute:en
Text Length:4,985 chars
Detector Agreement:100%

Website Classification

Primary Category

social media network99% confidence
Type: static
Method: ml+structural

All Detected Categories

social media network
99%
entertainment media
86%
adult content
73%
education learning
51%
documentation technical
50%

Detected Features

OG: website

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
2254.215.31.113San Jose, California, United States
AS16509AMAZON-02
21188.114.97.3Germany
21104.18.68.40United States
AS13335CLOUDFLARENET
643--

Detected Technologies1

40%

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1A6B17276BEBD213E00A391A226FDA3483AB0D113DB67019072ACC1391F5EF96FD1B594

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

96:ljHjCIjuTkDa/D+DMF+C8pZqXKHvpIkdNunRnvPaQxJbKRnx/Iq:ljHjDjusa/So+n6aHvFdNunBvieJ4nxJ

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:5542:RAIkFkiCBABCInIBQxADABABICBXkCAQAIoCAaIFJKAkMDMCBTRBkAAAgmgwgAKKJjkFk8CABIgEAK4QBAACBERkAgQCBIAE

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:c780002424fec3ff
Perceptual Hash:b722bcb492bccc2c
Difference Hash:1c1e50684870161c
Wavelet Hash:c7c2202424fec3ff
Color Hash:#2dd232

Other Hashes

Crop Resistant:1c1e50684870161c

Scan History

Scan history not available

Unable to load historical scan data