Security Scan Report: es-empresas.cc

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Submitted: Completed: publiccompleted
This website contacted 3 IPs in 1 country across 4 domains to perform 14 HTTP transactions. The main domain is es-empresas.cc and was registered 6 days ago.

Submitted URL: https://es-empresas.cc/adobe.products-lista.cc/

AI Security Verdict

Moderate Risk

Confidence: 72%

5
Risk Score

Day-old throwaway domain serving a 'KMSpico' branded 404 page that links to and submits searches to activator-kmspico.com, a phishing-flagged domain; pirated activation content plus Spamhaus IDS alert makes this unsafe.

Risk Factors (5)
Brand name 'KMSpico'/'KMS Activator' displayed on a mismatched, day-old domain
External link and form target activator-kmspico.com flagged as phishing (single-source, unverified)
Network IDS HIGH severity alert: Spamhaus DROP-listed traffic
Facilitates pirated software activation (KMS crack) distribution
Registry-critical domain age (≤1 day)
Safety Factors (5)
No password, credential or payment fields present (verified form facts: 0 password, 0 payment)
No JavaScript malware (YARA) patterns detected
No cross-origin credential exfiltration detected
No known malicious kit in the analyst-vetted kit roster
No concrete malicious signal: the threat-feed matches name third-party or shared hosts, or rest on a single feed or a reputation label, so they were not counted; no YARA / Safe-Browsing / IDS / credential form / brand impersonation either. Elevated risk rested on domain age or reputation alone; clamped from 7 to 5
Domain age information unavailable

Details

Page Title

Page not found - KMSpico

Scan Type

public

Domain Name Analysis

The domain name 'es-empresas.cc' uses the .cc country-code top-level domain with no subdomain. The core label 'es-empresas' covers 11 characters with 4 vowels and 6 consonants, along with one hyphen. Breaking it apart gives 4 words: es, emp, res, as. Expect 2.5 characters per word on average. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://es-empresas.cc/adobe.products-lista.cc/

Page Load Overview

4.90s
Total Load Time
302 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:668 chars
Detector Agreement:67%

Website Classification

Primary Category

technology software65% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

technology software
65%
documentation technical
48%
cryptocurrency blockchain
42%
government public service
36%
news media journalism
34%

Detected Features

Search
Schema.org

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
666.198.225.66New Castle, Pennsylvania, United States
AS402253SKN Subnet & Telecom Ltd
4142.251.110.95Google · CDNUnited States
AS15169Google LLC
4142.251.13.94Google · CDNUnited States
AS15169Google LLC
143--

Detected Technologies8

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1ED23E632F08C40367B6F5BE99058BB18B19AB925FF065AF5B1F65018CAD5DE301A730E

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

384:+wioERoU4dNJ6Ih7a4r+ZdSZUaAhtkWZntEqwJhfrIecxEH7pEs3fESV+WVMwLCm:+zJ4KZdypaDZntEqwEe+IfrXI9bf0bt

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:47102:EQCpFw0hSL1BEHhZNwEWpx5Kn6ACgKXIAHgQEkdEIQ0KkQCAJAEgAACDOMtgltIIBCaQEMIgnCEAUCdZQpQ7wyDwsm/ANEY1

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:e7ffe7e7e7e7ffe7
Perceptual Hash:b3cccc3333cc3323
Difference Hash:0e00080c0c0c000c
Wavelet Hash:00302424e7e7ffc3
Color Hash:#50931f

Other Hashes

Crop Resistant:0e00080c0c0c000c

Scan History

Scan history not available

Unable to load historical scan data