Security Scan Report: stanislauscountyredkettle.org

Redirected to:
https://give-gs.salvationarmy.org/campaign/838727/donate
Submitted: Sep 17, 2026, 3:14:00 AMCompleted: Sep 17, 2026, 3:14:56 AMpubliccompleted

This website contacted 67 IPs in 6 countries across 54 domains to perform 202 HTTP transactions. The main domain is give-gs.salvationarmy.org and was registered 3 years 5 months ago.

Submitted URL: https://stanislauscountyredkettle.org/

Effective URL:

https://give-gs.salvationarmy.org/campaign/838727/donate
Redirected

AI Security Verdict

Safe Website

Confidence: 95%

0
Risk Score

Legitimate Salvation Army donation page reached via a campaign redirect. No phishing, credential harvesting, malware, or threat-intelligence hits detected.

Safety Factors (4)
Final destination is the official Salvation Army domain.
Established charity with physical address and phone number visible.
Donation forms are normal for a charity fundraising page and do not capture passwords or card data directly.
No credential exfiltration, malware, phishing indicators, or threat-intelligence matches.
Domain age information unavailable

Details

Page Title

Donate to Stanislaus County Virtual Red Kettle 2026

Scan Type

public

Domain Name Analysis

The domain name 'stanislauscountyredkettle.org' uses the non-profit oriented generic top-level domain (.org) and has no subdomain. The second-level label 'stanislauscountyredkettle' is 25 characters long holding nine vowels versus 16 consonants. Segmentation suggests four words: stanislaus, county, red, kettle. Expect 6 characters per word on average. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://stanislauscountyredkettle.org/

Page Load Overview

8.80s
Total Load Time
4.9 MB
Total Size

Language Analysis

Primary Language

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

Detection Details

HTML Lang Attribute:en
Text Length:3,430 chars
Detector Agreement:100%

Website Classification

Primary Category

technology software47% confidence
Type: spa
Method: ml+structural+ocr_tiebreaker

All Detected Categories

technology software
47%
government public service
34%
documentation technical
26%

Detected Features

OG: website
Schema.org

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
4104.18.197.95Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
3172.67.134.166Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
3104.18.124.73Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
3104.18.40.238Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
3104.16.79.73Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
3104.21.25.206Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
3172.64.147.18Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
3151.101.2.133Fastly · CDNUnited States
AS54113Fastly, Inc.
3143.204.181.67Cloudfront · CDNUnited States
AS16509Amazon.com, Inc.
3104.26.10.27Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
20267--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T11B444B8E6130243D57870AE731C6E92B33B9E095F90648ACE8BD94BC13DB9A1533735B

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

1536:QHgUBK4xIKPwe8VyX908IiAAZpv6S7MhyX/OmtOyXrtZ7QwXC+eiFGLUjJp8y7Cs:QHgeBbyVyX908t0yXGyXr1XRwoprQmJV

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:259488:YMbD0gkgQgOKRFjQlCCNw+yGBCkMRRygQNAA1AASwJMQAwYAESK4GgCAkDUFYCRUcuLAKyTwAOSEBqWTQIwGBMmwoClQ2pIY

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:0074747070303c3c
Perceptual Hash:c7e738386c393919
Difference Hash:47ecc9cdc1c96969
Wavelet Hash:207e7c74707c3c3c
Color Hash:#add279

Scan History

Scan history not available

Unable to load historical scan data