Security Scan Report: oauth.appf.io

Submitted: Dec 25, 2025, 1:34:45 AMCompleted: Dec 25, 2025, 1:35:48 AMpubliccompleted

Summary

This website contacted 1 IP in 1 country across 1 domain to perform 2 HTTP transactions. The main domain is oauth.appf.io and was registered NaN years ago.

Submitted URL: https://oauth.appf.io

The Cisco Umbrella rank of the primary domain is #312,758 of the top 1 million websites

AI Security Verdict

Safe Website

Confidence: 95%

0
Risk Score

No security concerns detected; site appears legitimate.

Safety Factors
Well‑established domain with minimal risk category
Absence of credential‑harvesting or payment forms
No malicious Indicators of Compromise
No redirects or external links
Page content could not be fetched but no suspicious elements reported
Domain age information unavailable

Details

Page Title

N/A

Scan Type

public

Language

🏳️

UNKNOWN

(0% confidence)

Category

unknown

(0%)

Domain Information

The domain 'oauth.appf.io' uses the British Indian Ocean Territory country-code top-level domain (.io), featuring subdomain 'oauth'. Its registrable label 'appf' stretches across 4 characters holding 1 vowel versus three consonants. It segments into 2 words: app, f. Median word length is two characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://oauth.appf.io

Page Load Overview

1.33s
Total Load Time
2
HTTP Requests
0
Domains
N/A
Total Size

Language Analysis

Primary Language

🏳️UNKNOWN
Code: unknown
Confidence:0%

Detection Details

Language Code:unknown
Detection Confidence:0%
0
Detector Agreement:0%

Website Classification

Primary Category

unknown0% confidence
Type: static
Method: structural

All Detected Categories

No categories detected

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
23.33.239.78United States
AS16509AMAZON-02
01--

Page Statistics

0
Requests
0
Unique Domains
0.0 KB
Total Size

Content Similarity HashesFor malware variant detection

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

3:qVZxQXbZ6iF4:qzxO965

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:1:0:a7fe83ec64bb23eb28090598db3d166e

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:N/A
Perceptual Hash:N/A
Difference Hash:N/A
Wavelet Hash:N/A
Color Hash:N/A

Other Hashes

Crop Resistant:N/A

Scan History

Scan history not available

Unable to load historical scan data