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Security Scan Report: sequel-abuj.web.app

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Submitted: Completed: publiccompleted

Summary

API
This view is built from:
Scan result: counts, verdicts, details, IPs, technologies, hashes/api/v1/result/c7ee5aec-8c8a-45f7-b13e-66a16f7f5217Domain and IP registration (RDAP)/api/v1/rdap/c7ee5aec-8c8a-45f7-b13e-66a16f7f5217How often this domain was scanned/api/v1/domain/stats/sequel-abuj.web.appScan history for this domain/api/v1/domain/history/sequel-abuj.web.app?limit=15
This website contacted 7 IPs in 1 country across 3 domains to perform 15 HTTP transactions. The main domain is web.app and was registered 7 years ago.

Submitted URL: https://sequel-abuj.web.app/owa/state/aHR0cHM6Ly/#[email protected]

AI Security Verdict

Moderate Risk

Confidence: 78%

6
Risk Score

Login page on generic domain with phishing lure; likely credential harvesting – avoid.

Risk Factors (2)
Credential harvesting form (email + password) on non‑brand domain
Email address in URL fragment (phishing lure technique)
Safety Factors (4)
Domain age > 2 years (established)
No malicious Indicators of Compromise detected
No payment fields present
No brand impersonation evident
Domain age information unavailable

Details

Page Title

Ancore Inspection

Scan Type

public

Domain Name Analysis

You're looking at domain 'sequel-abuj.web.app' on the application-focused generic top-level domain (.app) and includes subdomain 'sequel-abuj'. The registrable portion 'web' spans 3 characters split between one vowel and two consonants. Segmentation suggests 1 word: web. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://sequel-abuj.web.app/owa/state/aHR0cHM6Ly/#uta@giga.se

Page Load Overview

2.40s
Total Load Time
207 KB
Total Size

Language Analysis

Primary Language

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

Detection Details

HTML Lang Attribute:en
Text Length:96 chars
Detector Agreement:100%

Website Classification

Primary Category

government public service59% confidence
Type: webapp
Method: ml+structural

All Detected Categories

government public service
59%
documentation technical
52%
corporate business
51%
news media journalism
46%
technology software
37%

Detected Features

Login Form

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
313.216.152.137Ashburn, Virginia, United States
AS14618AMAZON-AES
2199.36.158.100United States
AS54113FASTLY
2104.26.12.205United States
AS13335CLOUDFLARENET
298.87.66.187Ashburn, Virginia, United States
AS14618AMAZON-AES
2172.67.74.152United States
AS13335CLOUDFLARENET
22620:0:890::100United States
AS54113FASTLY
2104.26.13.205United States
AS13335CLOUDFLARENET
157--

Detected Technologies4

PasswordField
100%
HTTP/3
40%
HSTS
40%
Firebase
40%

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T174A2B5447021D8698D3F565A12BE8E2C70BC5DA25E06CE79B1DB89082EC46FC33D7B99

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

384:uxz/Ml3fVOS4mumXmHmzrmgm8mdwoC9aI6WH1Pro8hulvdhCtba3:nymumXmHmzrmgm8mdwoC9aI6WVro8hup

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:23200:AsAAsBBzBJSjYmKgigggIAaKwZZCoiS6QxCIXQNIeF1qkijgEHAAjgSkDAOtAABImJrlxxSCDgWJB2AoxAQoV8TMQBo4CmEO

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:0000181818000000
Perceptual Hash:9999666699999966
Difference Hash:100c32b22a080400
Wavelet Hash:3f3f1b1b18003030
Color Hash:#7753ac

Other Hashes

Crop Resistant:100c32b22a080400

Scan History

Scan history not available

Unable to load historical scan data