Phishing Analysis: Meta

Visual Capture

Detection Info

http://tomolaoke.github.io/aboutmeta

Detected Brand

Content Hashes (HTML Similarity)

Used to detect similar phishing pages based on HTML content

Algorithm	Hash Value
CONTENT TLSH	T1D2F1CC235084B5B7019391D1AA37BBD6F7D08300DE669B0615FA834EBFD6C85CC3762A
CONTENT ssdeep	96:T7oour7PcIeMrZL6tHXTf3cySPXg7SEwGT6bUzTMoZZpxgQw0v2eO4uI:fUrbcIfZAcySPQGEKoXZZpnr2eO5I

Visual Hashes (Screenshot Similarity)

Used to detect visually similar phishing pages based on screenshots

Algorithm	Hash Value
VISUAL pHash	d4f6992d9ce29e80
VISUAL aHash	ffecf4f432006018
VISUAL dHash	880c4c4466c4c0f8
VISUAL wHash	fffef4f432006018
VISUAL colorHash	07e00000000
VISUAL cropResistant	d8080c4c44446466,c9c1c1c09edab69e,080c444466c4c0f8

Code Analysis

Threat Level ALTO

⚠️ Phishing Confirmed

📊 Risk Score Breakdown

Total Risk Score

40/100

🔬 Comprehensive Threat Analysis

Threat Type

Meta Phishing Landing Page

Target

Meta 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

⚔️ Attack Methodology

Primary Method: Brand Impersonation Redirect

Impersonates Meta to build victim trust through search engine manipulation or malicious advertisements. Often redirects to credential theft pages or serves malware disguised as legitimate software.

Secondary Method: Standard Phishing Techniques

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

🌐 Infrastructure Indicators of Compromise

Domain Information

Domain

tomolaoke.github.io

Registered

Unknown

Registrar

Unknown

Status

Hosting platform (subdomain)

Hosting Information

Provider

Unknown

ASN

🤖 AI-Extracted Threat Intelligence

😰

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