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Security Scan Report: www.triplog.net

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Submitted: Oct 1, 2025, 10:46:27 PMCompleted: Oct 1, 2025, 10:47:50 PMpubliccompleted
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Summary

This website contacted 147 IPs in 2 countries across 39 domains to perform 98 HTTP transactions. The main domain is triplog.net and was registered NaN years ago.

Submitted URL: https://www.triplog.net/blog/how-does-doordash-work

The Cisco Umbrella rank of the primary domain is #561,117 of the top 1 million websites

AI Security Verdict

Low Risk

Confidence: 80%

2
Risk Score

The site appears legitimate but has low reputation; proceed cautiously.

Risk Factors
Domain is not listed in Cisco Umbrella top 1M (low reputation)
Domain is relatively new (<2 years)
Page mentions a well‑known brand (DoorDash) on a non‑official domain
Safety Factors
No malicious Indicators of Compromise detected
No password or payment fields present
Form includes reCAPTCHA, reducing automated abuse
Content appears genuine and educational
Domain age information unavailable

Details

Page Title

What is DoorDash? | How Does DoorDash Work? | TripLog

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

technology software

(88%)

Screenshot

Security scan screenshot of https://www.triplog.net/blog/how-does-doordash-work

Page Load Overview

26.90s
Total Load Time
98
HTTP Requests
39
Domains
2.4 MB
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:14,823 chars
Detector Agreement:100%

Website Classification

Primary Category

technology software88% confidence
Type: spa
Method: ml+structural

All Detected Categories

technology software
88%
documentation technical
63%
government public service
43%
cryptocurrency blockchain
38%
healthcare medical
38%

Detected Features

OG: website

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
0142.250.186.67United States
AS15169GOOGLE
0104.17.175.201United States
AS13335CLOUDFLARENET
0142.250.186.131United States
AS15169GOOGLE
013.226.244.30United States
AS16509AMAZON-02
0142.250.185.200United States
AS15169GOOGLE
0216.58.206.67United States
AS15169GOOGLE
034.117.162.98Kansas City, Missouri, United States
AS396982GOOGLE-CLOUD-PLATFORM
013.226.244.55United States
AS16509AMAZON-02
013.226.247.67United States
AS16509AMAZON-02
0104.18.40.240United States
AS13335CLOUDFLARENET
98147--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T18F544BA6B66521B0810393F8E66B772875276097AB03C588F6FC8744BFC1CDC5899EC7

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

1536:sDboFw0CDRjlzDlQy1EEKgJyHoYz9pu0+l4fq1kEKgJyHoYz9pu0+lA2pXlpLJmi:eZfyIyHmyIyb2RLJmQq9zHBmWuZgkJN5

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:282054:ITYkCh0NCQVikOLkD4cAiBpiB9ACTCoAB6AAAQBgAqLEJEITNgAOigQkcMlUASggAIQCwIfsUEpsTFAyIlsoBKDByR8OBxmw

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:ffffff9b99c3c7e7
Perceptual Hash:fc89f32c0fa2d42a
Difference Hash:0022142b33964d4c
Wavelet Hash:fefefe9880c0c0e0
Color Hash:#4d3a78

Other Hashes

Crop Resistant:0022142b33964d4c,d4d4693333960e4d

Scan History

Scan history not available

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