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Security Scan Report: pendencias-identificadas.vercel.app

Submitted: Jul 4, 2026, 12:52:02 PMCompleted: Jul 4, 2026, 12:53:35 PMpubliccompleted
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Summary

This website contacted 1 IP in 1 country across 1 domain to perform 2 HTTP transactions. The main domain is pendencias-identificadas.vercel.app and was registered NaN years ago.

Submitted URL: https://pendencias-identificadas.vercel.app/up03/index.html?name=Rafael%2520De%2520Oliveira%2520Martins%2520Dos%2520Santos&document=02561002179&[email protected]&telephone=61981437742&utm_source=organic&fbclid=PAZXh0bgNhZW0BMABhZGlkAasvqvMMh3hzcnRjBmFwcF9pZA81NjcwNjczNDMzNTI0MjcAAaeNNqclVEAXtgsjARN4qN6QWUcCKW6NTWRSoF817zSQfdBnXzwXc4VuEWrGBg_aem_ZnMWFREUAlVCbOLLEgTgJw?fbclid%3DPAT01DUAQosiBleHRuA2FlbQIxMABzcnRjBmFwcF9pZA81NjcwNjczNDMzNTI0MjcAAaemZTSBA5AXYRb5DPkWb8PBH2sIgYbmpsaqfzqG_iIQz-pp3548fJF3MZHB0w_aem_Iwo2WOHei2x1V1CEOAwVnA

AI Security Verdict

Low Risk

Confidence: 85%

2
Risk Score

The site shows no malicious activity, contains no forms, and only exhibits weak signals such as being unranked; classified as low risk.

Risk Factors
Domain is unranked in Cisco Umbrella
Domain creation date is unknown (subdomain on hosting platform)
Safety Factors
Self‑branding (no brand impersonation)
Absence of forms that collect credentials or payment data
No malicious JavaScript or external links detected
Domain age information unavailable

Details

Page Title

Deployment Unavailable

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

technology software

(75%)

Domain Information

The domain 'pendencias-identificadas.vercel.app' uses the application-focused generic top-level domain (.app); it also runs on subdomain 'pendencias-identificadas'. Count 6 characters in 'vercel' split between two vowels and 4 consonants. Tokenizing the label suggests 2 words: ver, cel. Expect three characters per word on average. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://pendencias-identificadas.vercel.app/up03/index.html?name=Rafael%2520De%2520Oliveira%2520Martins%2520Dos%2520Santos&document=02561002179&email=rafaelww1787@gmail.com&telephone=61981437742&utm_source=organic&fbclid=PAZXh0bgNhZW0BMABhZGlkAasvqvMMh3hzcnRjBmFwcF9pZA81NjcwNjczNDMzNTI0MjcAAaeNNqclVEAXtgsjARN4qN6QWUcCKW6NTWRSoF817zSQfdBnXzwXc4VuEWrGBg_aem_ZnMWFREUAlVCbOLLEgTgJw?fbclid%3DPAT01DUAQosiBleHRuA2FlbQIxMABzcnRjBmFwcF9pZA81NjcwNjczNDMzNTI0MjcAAaemZTSBA5AXYRb5DPkWb8PBH2sIgYbmpsaqfzqG_iIQz-pp3548fJF3MZHB0w_aem_Iwo2WOHei2x1V1CEOAwVnA

Page Load Overview

8.10s
Total Load Time
1
HTTP Requests
1
Domains
N/A
Total Size

Language Analysis

Primary Language

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

Detection Details

Language Code:en
Detection Confidence:80%
Script Type:Latin
HTML Lang Attribute:en
Text Length:801 chars
Detector Agreement:67%

Website Classification

Primary Category

technology software75% confidence
Type: static
Method: ml+structural

All Detected Categories

technology software
75%
documentation technical
45%
adult content
36%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
164.29.17.67United States
AS16509Amazon.com, Inc.
11--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1253174B745B1702EF23788FD34D633646244911BC0960F99B658AFB8E2D7CA65023645

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

48:TGepXZ9S3dGNGDY7nnrm+AgJJ8EYpz7s0:TGi9ScnwEYs0

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:1651:AAAQAAAgACIAJABAAEQAgAAAGAAAAAABAAAAgCAgAgAQIAADAASACAAAAAAgACAAEAAQAAABAAAAGAAAQABEAAgIggAIAIAB

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:ffffffe7e7ffffe7
Perceptual Hash:e699999966999989
Difference Hash:0000000c0c00000c
Wavelet Hash:f0f0fce4243c3c24
Color Hash:#2d90d2

Other Hashes

Crop Resistant:0000000c0c00000c

Scan History

Scan history not available

Unable to load historical scan data