SafeMode - Analysis: bagyalakshmi-velu.github.io

Visual Capture

Screenshot of bagyalakshmi-velu.github.io

Detection Info

http://bagyalakshmi-velu.github.io/amazon

Detected Brand

Amazon

Country

Unknown

Confidence

100%

HTTP Status

200

Report ID

cb5b6b1c-a8e…

Analyzed

2026-05-06 10:22

Final URL (after redirects)

https://bagyalakshmi-velu.github.io/amazon/

Content Hashes (HTML Similarity)

Used to detect similar phishing pages based on HTML content

Algorithm	Hash Value
CONTENT TLSH	T1D8022AA0C8B5D6B714D361B4D3752ED53FC1934282670E1453F99349BEAADCACE23938
CONTENT ssdeep	96:TwJLidPIM4PHWR4MV57wcLJiJ/JEJpJOJLJAJFJpJEJoV57wctKm:YLHeUIJiJ/JEJpJOJLJAJFJpJEJAUAKm

Visual Hashes (Screenshot Similarity)

Used to detect visually similar phishing pages based on screenshots

Algorithm	Hash Value
VISUAL pHash	f94f134813875b4e
VISUAL aHash	00fbf8ffc0c0ffcf
VISUAL dHash	e11702b295959b9d
VISUAL wHash	00d1f0ffc0c0ff4e
VISUAL colorHash	07401010000
VISUAL cropResistant	808082c2c2c28080,9313629695979b9d,e9c1236397176222,1c3d4cd6699d8503,981f3ba1c5c5b909,0f4e4c4e0616c667,41694d6c5e5e7e3e

Code Analysis

Risk Score 50/100

Threat Level ALTO

⚠️ Phishing Confirmed

🎣 Credential Harvester

🎯 Kit Endpoints

./login.html

📡 API Calls Detected

./product.json

📊 Risk Score Breakdown

Total Risk Score

70/100

Contributing Factors

Active Phishing Kit

Detected kit types: Credential Harvester

🔬 Comprehensive Threat Analysis

Threat Type

Credential Harvesting Kit

Target

Amazon users

Attack Method

Phishing webpage

Exfiltration Channel

Form submission (backend endpoint not detected - likely JavaScript-based)

Risk Assessment

MEDIUM - Automated credential harvesting with Form submission (backend endpoint not detected - likely JavaScript-based)

⚠️ Indicators of Compromise

Kit types: Credential Harvester

🏢 Brand Impersonation Analysis

Impersonated Brand

Amazon

Official Website

https://www.amazon.com

Fake Service

Credential harvesting service

⚔️ Attack Methodology

Primary Method: Credential Harvesting

Victim enters username and password into fake login form. Credentials are captured via JavaScript and exfiltrated to attacker's server in real-time.

Secondary Method: Client-Side Form Interception

JavaScript intercepts form submissions before they reach the fake backend. This allows real-time credential harvesting and validation without server round-trips.