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Security Scan Report: howabetcoffee.site

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Submitted: Dec 9, 2025, 6:10:24 PMCompleted: Dec 9, 2025, 6:10:58 PMpubliccompleted
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Summary

This website contacted 49 IPs in 4 countries across 11 domains to perform 27 HTTP transactions. The main domain is howabetcoffee.site and was registered NaN years ago.

Submitted URL: https://howabetcoffee.site/north-forsyth-stabbing/

AI Security Verdict

Low Risk

Confidence: 75%

2
Risk Score

New, unranked site with minimal risk; no malicious indicators detected.

Risk Factors
Very new, brand‑new domain (<7 days) often used for spam or malicious sites
Unranked domain with no established reputation
Safety Factors
No password or payment fields present
No malicious Indicators of Compromise detected
Content appears to be a news article, not a credential‑harvesting page
Domain age information unavailable

Details

Page Title

North Forsyth Stabbing: One Student Died, Another Injured, Lockdown at North Forsyth High School in Winston-Salem, N.C. – How Bet Coffee

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

unknown

(0%)

Domain Information

The domain name 'howabetcoffee.site' uses the .site top-level domain without a subdomain. The core label 'howabetcoffee' covers 13 characters holding 6 vowels versus 7 consonants. Segmentation suggests 3 words: how, abet, coffee. Average segment length settles at 4 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://howabetcoffee.site/north-forsyth-stabbing/

Page Load Overview

15.36s
Total Load Time
27
HTTP Requests
11
Domains
450 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-US
Text Length:3,415 chars
Detector Agreement:100%

Website Classification

Primary Category

unknown0% confidence
Type: dynamic
Method: structural

All Detected Categories

No categories detected

Detected Features

Articles
Comments

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
2752.222.136.119United States
AS16509AMAZON-02
0192.178.170.95United States
AS15169GOOGLE
013.35.58.85United States
AS16509AMAZON-02
013.35.58.60United States
AS16509AMAZON-02
0192.0.73.2San Francisco, California, United States
AS2635AUTOMATTIC
03.160.150.115United States
AS16509AMAZON-02
0184.94.213.242United States
AS22612NAMECHEAP-NET
0172.240.127.244United States
AS7979SERVERS-COM
0192.0.76.3San Francisco, California, United States
AS2635AUTOMATTIC
013.35.58.112United States
AS16509AMAZON-02
2749--

Detected Technologies6

WordPressv6.9
100%
MetaGenerator
100%
PHP
50%
MySQL
50%
Litespeed Cache
40%
LiteSpeed
40%

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T17CC36CE1BA6419362F6B42F1F06B220BB5F1D9379B858061F16DC8A81F58CA700F7B5D

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

3072:SdkRaBAe/n+k1nrDD44OqCf2ifqippxZfrXF3ft72297CKJas9gj+w6fV5CKk:8B/GEDD44ofF5ppxZTXF3ft17CKgs9rA

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:122152:wAVS8YrIaHABBJroAgIGEGAQqDCAsBDAIATKCRHqKHaEcEPASiDApwWiAgQDCMFqUHzAkBGb60APoOINkdGEAgg0wAUEDmDC

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:ffffdf878787c7ff
Perceptual Hash:b6cdc9323aa1cccc
Difference Hash:2016362d2d2d0f33
Wavelet Hash:df8383878787c383
Color Hash:#a1c587

Other Hashes

Crop Resistant:2016362d2d2d0f33,28e1c07d79dff0e9

Scan History

Scan history not available

Unable to load historical scan data