Security Scan Report: fnclabs-landing.pages.dev

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https://fnclabs-landing.pages.dev/
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Submitted: Sep 29, 2026, 9:10:19 PMCompleted: Sep 29, 2026, 9:10:54 PMpubliccompleted

This website contacted 4 IPs in 1 country across 3 domains to perform 11 HTTP transactions. The main domain is fnclabs-landing.pages.dev and was registered 18 years ago.

Submitted URL: http://fnclabs-landing.pages.dev/

Effective URL:

https://fnclabs-landing.pages.dev/
Redirected

AI Security Verdict

Low Risk

Confidence: 65%

2
Risk Score

Self-branded FNC Labs WhatsApp-automation landing page on a pages.dev subdomain. No password/payment fields, no impersonation, no IoC or malware; only a standard lead/quote form via a legitimate backend.

Safety Factors (5)
Self-branding: page presents its own 'FNC Labs' brand, matching its domain
No credential or payment fields anywhere on the page
Business identity disclosed: 'FNC Labs (Pty) Ltd' with a South African company registration number and a Cape Town location
Legitimate, well-known form backend (formsubmit.co) rather than an off-site credential sink
HTTPS form submission from the site's own domain; no third-party scripts
Domain age information unavailable

Details

Page Title

FNC Labs | WhatsApp automation for South African businesses

Scan Type

public

Domain Name Analysis

The domain name 'fnclabs-landing.pages.dev' uses the developer-focused generic top-level domain (.dev) and includes subdomain 'fnclabs-landing'. The second-level label 'pages' is 5 characters long holding 2 vowels versus three consonants. Segmentation suggests one word: pages. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of http://fnclabs-landing.pages.dev/

Page Load Overview

0.45s
Total Load Time
376 KB
Total Size

Language Analysis

Primary Language

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

Detection Details

HTML Lang Attribute:en-ZA
Text Length:2,920 chars
Detector Agreement:100%

Website Classification

Primary Category

government public service69% confidence
Type: static
Method: ml+structural+ocr_tiebreaker

All Detected Categories

government public service
69%
social media network
66%
technology software
66%
finance banking
47%
documentation technical
46%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
5172.66.47.156Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
2142.250.154.95Google · CDNUnited States
AS15169Google LLC
2142.251.14.94Google · CDNUnited States
AS15169Google LLC
2172.66.44.100Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
114--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T14D82E92351F22135880351D17FA6675E7BA0E107C805CA68BEDE4B88CFDEAD9D97321C

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

384:zRV98bkymUl5N98QKwsidm/oVU9vI+XTL1gzojM21bY:b2bl5N98QKwsUH+NrDL2042NY

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:17928:HWkAwcgQEjZKhAACNKEEqNnIyC2ACJYYpEQWgIBASchSEIYBCqRECDVB7VigowDsUUsAj1N0ICGCEIMRIiRskDAhFFxAA/BR

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:06257d6c6c203c7c
Perceptual Hash:82b76c7c92346cd3
Difference Hash:15c9c9c9c9e7c9d1
Wavelet Hash:072d7d0d6d21353d
Color Hash:#783a55

Other Hashes

Scan History

Scan history not available

Unable to load historical scan data