Phishing Analysis: Netflix

Visual Capture

Detection Info

https://kajalkhade.github.io/Netflix-/

Detected Brand

Netflix

Country

Unknown

Confidence

100%

HTTP Status

200

Report ID

232c8531-1e2…

Analyzed

2026-04-07 18:18

Content Hashes (HTML Similarity)

Used to detect similar phishing pages based on HTML content

Algorithm	Hash Value
CONTENT TLSH	T1EE113026709064534583B1F3FB435746BAB605C8EB53070030FAC2495FE8D1EC99308E
CONTENT ssdeep	24:hR/Cn/3ObfaI4JNUQn6WqxJ/gZvB/gZxsKB:T4+bSIIND6lJ/eB/RKB

Visual Hashes (Screenshot Similarity)

Used to detect visually similar phishing pages based on screenshots

Algorithm	Hash Value
VISUAL pHash	cc3333cccc3333cc
VISUAL aHash	0100003c38000000
VISUAL dHash	01200060f0002000
VISUAL wHash	8100003c3c0c0000
VISUAL colorHash	38000000007
VISUAL cropResistant	0202826262020002,01200060f0002000

Code Analysis

Threat Level ALTO

⚠️ Phishing Confirmed

📊 Risk Score Breakdown

Total Risk Score

70/100

🔬 Comprehensive Threat Analysis

Threat Type

Netflix Phishing Landing Page

Target

Netflix users

Attack Method

Phishing webpage

Exfiltration Channel

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

Risk Assessment

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

🏢 Brand Impersonation Analysis

Impersonated Brand

Netflix

Official Website

https://www.netflix.com

Fake Service

Credential harvesting service

⚔️ Attack Methodology

Primary Method: Search Engine Manipulation

Fake Netflix site positioned to capture victims through SEO tactics, typosquatting, or paid advertising. Serves as entry point for multi-stage attacks including credential theft and malware distribution.

Secondary Method: Standard Phishing Techniques

Uses typical phishing tactics including brand impersonation, urgency tactics, and social engineering to trick victims into providing sensitive information.