Security Scan Report: niah.science

Redirected to:
https://login.microsoftonline.com/common/oauth2/v2.0/authorize?client_...
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Submitted: Feb 21, 2026, 1:38:56 PMCompleted: Feb 21, 2026, 1:40:04 PMpubliccompleted
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Summary

This website contacted 1 IP in 1 country across 1 domain to perform 3 HTTP transactions. The main domain is login.microsoftonline.com and was registered NaN years ago.

Submitted URL: https://niah.science/auth/microsoft

Effective URL: https://login.microsoftonline.com/common/oauth2/v2.0/authorize?client_id=&prompt=&redirect_uri=https%3A%2F%2Fniah.science%2Fauth%2Fmicrosoft%2Fcallback&response_type=code&scope=https%3A%2F%2Fgraph.microsoft.com%2FUser.Read&state=9ioSfqDNzuOt5dnxIgGS9IIDRedirected

AI Security Verdict

Low Risk

Confidence: 85%

2
Risk Score

The site impersonates Microsoft on an unranked domain, presenting a login‑like page without real credential fields, indicating high phishing risk.

Risk Factors
Brand impersonation on unranked domain
Login‑style UI without actual credential fields
Excessive use of Function() constructor (potential code generation)
Unranked domain despite old registration age
Safety Factors
Domain age 8749 days (well‑established)
No Indicators of Compromise matches
No JavaScript malware YARA patterns detected
No network IDS alerts
No credential exfiltration observed
Page served from an identity-provider sign-in endpoint (login.microsoftonline.com); a relying-party brand and login form here are normal SSO, not impersonation — risk clamped from 7 to 2
Domain age information unavailable

Details

Page Title

niah.science

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

documentation technical

(36%)

Domain Information

Within the .science top-level domain, 'niah.science' is registered and has no subdomain. The registrable portion 'niah' spans 4 characters with 2 vowels and 2 consonants. Breaking it apart gives two words: nia, h. Median word length comes out to 2 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://niah.science/auth/microsoft

Page Load Overview

1.13s
Total Load Time
20
HTTP Requests
3
Domains
372 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
Text Length:764 chars
Detector Agreement:100%

Website Classification

Primary Category

documentation technical36% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

documentation technical
36%
government public service
34%
technology software
29%
healthcare medical
26%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
20188.114.96.3Netherlands
201--

Detected Technologies4

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T16D048F773296063986558498F05B43099F20B143F50AC9BCB9BCBAD9BFDED06107BB78

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

3072:tfQho9PKBb9Js3q9Jzbs6tlg3SBKwdQWgceIszS2bMy8Oldz:ahoC9JSqzzbs6o3Sj3gcrsu2eAF

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:184493:MRYAFAAASCRBI9AgeJDYgJlBgweDRAgTWgBuDkCY2uAw0NMM4AQFCkIIGYAL1J5OTQFKoU+cKCJIACwAIJBIhEamQXGg0UEz

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:ffcfc7c7ffffffff
Perceptual Hash:b331cccccc633333
Difference Hash:00180c1400000000
Wavelet Hash:fcdcc0cc00000000
Color Hash:#2dd23d

Other Hashes

Crop Resistant:00180c1400000000

Scan History

Scan history not available

Unable to load historical scan data