Security Scan Report: askocblog-dptdxwy2odnr.edgeone.app

Site favicon
Submitted: Jun 25, 2026, 8:35:53 AMCompleted: Jun 25, 2026, 8:37:03 AMpubliccompleted

Summary

This website contacted 8 IPs in 3 countries across 13 domains to perform 2 HTTP transactions. The main domain is askocblog-dptdxwy2odnr.edgeone.app and was registered 3 years 3 months ago.

Submitted URL: https://askocblog-dptdxwy2odnr.edgeone.app/ana-huang-upcoming-books.html

AI Security Verdict

Low Risk

Confidence: 75%

3
Risk Score

The site hosts an article without credential or payment forms; high JS obfuscation and unknown subdomain age raise moderate concern but no concrete malicious signals are present.

Risk Factors
Critical JavaScript obfuscation score
Subdomain on a hosting platform with unknown age
Unranked domain (not in Cisco Umbrella top 1M)
Safety Factors
Page type is an article (og:type=article) – no credential collection intent
No external credential exfiltration or cross‑origin form submissions
No malicious IDS alerts or Safe Browsing threats
No brand impersonation or phishing‑related meta tags
Verdict cited a credential/login form, but DOM analysis found no password field (real or disguised) or payment field, and no other hard signal — credential-phishing framing unsupported; risk adjusted from 4 to 3
Domain age information unavailable

Details

Page Title

Ana Huang's Upcoming Books: What to Expect from the Bestselling Author

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

government public service

(50%)

Domain Information

Within the application-focused generic top-level domain (.app), 'askocblog-dptdxwy2odnr.edgeone.app' is registered, featuring subdomain 'askocblog-dptdxwy2odnr'. The registrable portion 'edgeone' spans 7 characters containing 4 vowels alongside 3 consonants. Splitting it apart reveals two words: edge, one. The median word length lands at 3.5 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of accedelid.com

Page Load Overview

2.16s
Total Load Time
18
HTTP Requests
13
Domains
162 KB
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-US
Text Length:3,437 chars
Detector Agreement:100%

Website Classification

Primary Category

government public service50% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

government public service
50%
adult content
43%
news media journalism
38%
corporate
35%
download file sharing
34%

Detected Features

OG: article
Schema.org

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
4172.240.127.234United States
AS7979Servers.com, Inc.
243.152.26.58Singapore
218.64.210.156United States
AS16509Amazon.com, Inc.
234.49.129.249Kansas City, Missouri, United States
AS396982Google LLC
2146.75.122.152Frankfurt am Main, Hesse, Germany
AS54113Fastly, Inc.
2142.251.13.95United States
AS15169Google LLC
2104.21.0.120United States
AS13335Cloudflare, Inc.
218.64.16.183United States
AS16509Amazon.com, Inc.
188--

Page Statistics

18
Requests
13
Unique Domains
220.5 KB
Total Size

Detected Technologies2

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T173721B2BFB81221977314156E5C0B3FCBDA9841BD7828DB1B6DCB3289BC56DF2431618

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

384:KSqhnYf8zX+3J06ywmsfRYZ/zYTQ6kQHorWag4MVOy:Tqhnz+3JOwH5Y5YTQ6kQIrWag4Wx

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:17160:wgkJYgB4ASEF8CpkYahKBKIBmFDILgNiJBQQKQWY4FAhgIYBRCkCI6NDWhfQCECJj0HQAqChkqSTAkSA8QJCDGBVGFJQhSjk

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:197901017d217d7d
Perceptual Hash:8a3cc9dc9c3c3c9c
Difference Hash:f1c10521c1c1c9c9
Wavelet Hash:197d01017d317d7d
Color Hash:#783a5b

Other Hashes

Scan History

Scan history not available

Unable to load historical scan data