Security Scan Report: topstarjeff.github.io

Redirected to:
https://topstarjeff.github.io/Mic/Microsoft.html
Submitted: Completed: publiccompleted
This website contacted 10 IPs in 2 countries across 6 domains to perform 10 HTTP transactions. The main domain is github.io and was registered 13 years ago.

Submitted URL: http://topstarjeff.github.io/Mic/Microsoft.html

Effective URL:
https://topstarjeff.github.io/Mic/Microsoft.html
Redirected

AI Security Verdict

Confirmed Scam

Confidence: 98%

10
Risk Score

Microsoft-branded credential phishing hosted on a github.io subdomain, with a password-harvesting form and Telegram exfiltration; Safe Browsing flags it twice for social engineering. Do not enter credentials.

Risk Factors (5)
Credential phishing kit cloned from Microsoft's sign-in flow
Brand impersonation of Microsoft on a non-Microsoft, unranked github.io host
Telegram-bot exfiltration channel in inline JavaScript
Google Safe Browsing Social Engineering detections (2)
Shared-hosting subdomain with unknown creation date, no legitimate association with the impersonated brand
Domain age information unavailable

Details

Page Title

Security verification - Microsoft account

Scan Type

public

Domain Name Analysis

The domain 'topstarjeff.github.io' uses the British Indian Ocean Territory country-code top-level domain (.io) with subdomain 'topstarjeff'. The second-level label 'github' is 6 characters long with 2 vowels and 4 consonants. Word splitting yields three words: g, it, hub. Median word length is 2 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of http://topstarjeff.github.io/Mic/Microsoft.html

Page Load Overview

0.91s
Total Load Time
71 KB
Total Size

Language Analysis

Primary Language

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

Detection Details

HTML Lang Attribute:en
Text Length:515 chars
Detector Agreement:100%

Website Classification

Primary Category

technology software71% confidence
Type: static
Method: ml+structural

All Detected Categories

technology software
71%
documentation technical
37%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
1185.199.109.153Fastly · CDNUnited States
AS54113Fastly, Inc.
1185.199.110.153Fastly · CDNUnited States
AS54113Fastly, Inc.
1192.178.183.95Google · CDNUnited States
AS15169Google LLC
123.194.190.161Akamai · CDNFrankfurt am Main, Hesse, Germany
AS20940Akamai International B.V.
1104.16.79.73Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
123.52.181.212Akamai · CDNFrankfurt am Main, Hesse, Germany
AS16625Akamai Technologies, Inc.
1172.67.69.226Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
1185.199.111.153Fastly · CDNUnited States
AS54113Fastly, Inc.
1142.251.110.95Google · CDNUnited States
AS15169Google LLC
1184.24.77.15Akamai · CDNFrankfurt am Main, Hesse, Germany
AS20940Akamai International B.V.
1010--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T10072C53D69753A117423E06C777A93053677B203D506C62378ED4688CF4AA9EAEB339C

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

192:EiBIG3DxgN5Ps1PbOX8BwduJ/z2SXdor1w2LH/5u6yH7Q9MPwg9PtyJYbBi+LJJf:BIeScPbB/JJixvA+Qj1i1qgWm0V2W

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:16732:CJISAjcZvQElEo0iRgYaFIAYJSLIhgJFgAFTIwVFyRBoEFVAPENCEl+gAAANAgRWRwKFEBBwIRAmpQSqMTsDwikaX4wcNGAA

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:ffffffffe7e7ffe7
Perceptual Hash:b399cc2693cc6633
Difference Hash:0010282a4d4c3008
Wavelet Hash:0f0f1f0f07070f0f
Color Hash:#797bd2

Other Hashes

Crop Resistant:0010282a4d4c3008

Scan History

Scan history not available

Unable to load historical scan data