Security Scan Report: app.raiffeisenbank.ba

Redirected to: https://app.raiffeisenbank.ba/vijesti/raiffeisen-banka-domacin-internacionalne-konferencije-make-azure-days-happen

Submitted: Feb 25, 2026, 2:29:49 PMCompleted: Feb 25, 2026, 2:31:46 PMpubliccompleted
Loading additional data...

Summary

This website contacted 7 IPs in 3 countries across 7 domains to perform 142 HTTP transactions. The main domain is app.raiffeisenbank.ba.

Submitted URL: http://app.raiffeisenbank.ba/vijesti/raiffeisen-banka-domacin-internacionalne-konferencije-make-azure-days-happen

Effective URL: https://app.raiffeisenbank.ba/vijesti/raiffeisen-banka-domacin-internacionalne-konferencije-make-azure-days-happenRedirected

AI Security Verdict

Moderate Risk

Confidence: 68%

5
Risk Score

Likely a legitimate news article about an Azure conference; no direct threats, but unknown domain age suggests caution.

Risk Factors
Unknown domain age
Unranked domain reputation
Brand mention (Microsoft) on a non‑Microsoft domain
Safety Factors
No password or payment fields in any form
No malicious Indicators of Compromise found
No JavaScript malware patterns detected
No network IDS alerts
Served over HTTPS (assumed from URL scheme)
Domain age information unavailable

Details

Page Title

Raiffeisen banka domaćin internacionalne konferencije “Make Azure Days Happen” | Raiffeisen Bank Bosna i Hercegovina

Scan Type

public

Language

🇭🇷

HR

(35% confidence)

Category

finance banking

(61%)

Domain Information

The domain 'app.raiffeisenbank.ba' uses the Bosnian country-code top-level domain (.ba) and includes subdomain 'app'. The registrable portion 'raiffeisenbank' spans 14 characters split between 6 vowels and eight consonants. Splitting it apart reveals 4 words: r, aiff, eisen, bank. Expect four characters per word on average. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of http://app.raiffeisenbank.ba/vijesti/raiffeisen-banka-domacin-internacionalne-konferencije-make-azure-days-happen

Page Load Overview

12.44s
Total Load Time
156
HTTP Requests
11
Domains
662 KB
Total Size

Language Analysis

Primary Language

🇭🇷HR
Code: hr
Confidence:35%
Script:Unknown
Direction:ltr

Detection Details

Language Code:hr
Detection Confidence:35%
Script Type:Unknown
HTML Lang Attribute:bs
Text Length:6,867 chars
Detector Agreement:40%
Language mismatch: Declared as bs but detected as hr

Website Classification

Primary Category

finance banking61% confidence
Type: spa
Method: ml+structural

All Detected Categories

finance banking
61%
travel tourism
50%
government public service
49%
technology software
44%
cryptocurrency blockchain
39%

Detected Features

Search
OG: website

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
24104.18.87.42United States
AS13335Cloudflare, Inc.
22216.58.206.72United States
22142.251.140.170Finland
2218.66.102.11Germany
22185.172.148.132Unknown
2254.76.137.151UnknownUnknown
22217.160.200.101Germany
AS8560IONOS SE
1567--

Detected Technologies7

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1923373255C958D3782230ECCB5F2F61D206AF29EC602CE44B6FC91AE7BD9FD44C11AA5

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

1536:vx+ZJ9NITm0kK8O6gUeApSZD5d57qZH7iYiHH:5TitSZD5d57qZH7iYiHH

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:50839:NTgQAAIDEJxAAWkEpAyQBFKVMCBAgoZrl1AjsOCQkkHyABMKZjLEBCRBiAABMxA4nEKTgU0UInoihEAEAAA4AQEyxGiYYQGk

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:00e7e7ffc7e7efc7
Perceptual Hash:b52f2b0b0e0f2e6a
Difference Hash:718c8ea09e9e9696
Wavelet Hash:00c2e6fec2c6cec7
Color Hash:#ac536b

Other Hashes

Scan History

Scan history not available

Unable to load historical scan data