Security Scan Report: session-check.vercel.app

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Submitted: Aug 23, 2026, 1:45:08 PMCompleted: Aug 23, 2026, 1:46:31 PMpubliccompleted

AI Security Verdict

Moderate Risk

Confidence: 72%

5
Risk Score

The page impersonates Facebook in meta tags but lacks credential collection; treat as moderate risk and avoid providing personal data.

Risk Factors (3)
Brand impersonation without matching domain
Unranked / low‑reputation domain
Unknown subdomain creation date on shared hosting platform
Safety Factors (4)
No credential or payment collection forms
No IoC matches or malicious YARA detections
No critical IDS alerts (only informational)
Content appears to be a generic marketing description of a React component library
Domain age information unavailable

Details

Page Title

Official Notice from Facebook

Scan Type

public

Domain Name Analysis

The domain name 'session-check.vercel.app' uses the application-focused generic top-level domain (.app), featuring subdomain 'session-check'. The second-level label 'vercel' is 6 characters long with 2 vowels and 4 consonants. Splitting it apart reveals two words: ver, cel. Median word length comes out to three characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://session-check.vercel.app/accounts-center

Page Load Overview

2.21s
Total Load Time
1.5 MB
Total Size

Language Analysis

Primary Language

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

Detection Details

HTML Lang Attribute:en
Text Length:634 chars
Detector Agreement:100%

Website Classification

Primary Category

technology software74% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

technology software
74%
social media network
44%
documentation technical
41%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
2464.29.17.3United States
AS16509Amazon.com, Inc.
241--

Detected Technologies2

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T14E815367EE0CCE5B0421A9ADD05B72ADC017883EDD78EC20E1DD425C2661FE947A3DE2

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

48:bUiNWcNiG2AGHQa/WGWE/EflUFu1Tipilp/S5W2C9qJO2jiW2C9qJOM7W2C9qJfs:QZtAYZuJfBD/SnUfFa5xnvmvg9

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:3969:bCBAQgKAQAAAAgOAEQBDAACAwgDUCgQAAIQIAgABAABQITgAAEBgIAIAgBgGQQKBAkhQAAGEANxIgIwEAIEEAAAGADJQhgBA

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:0001039fffffffff
Perceptual Hash:bc3823633c3c3ec3
Difference Hash:3fdf3f3730200000
Wavelet Hash:00000001dfffffff
Color Hash:#ac53a2

Other Hashes

Crop Resistant:3fdf3f3730200000

Scan History

Scan history not available

Unable to load historical scan data