Summary
This website contacted 13 IPs in 2 countries across 2 domains to perform 19 HTTP transactions. The main domain is stopfakes.gov and was registered NaN years ago.
Submitted URL: https://www.stopfakes.gov/
AI Security Verdict
Safe Website
Confidence: 95%
Legitimate government site with no security concerns.
Safety Factors
Details
Page Title
Home
Scan Type
public
Language
English
Category
government
(48%)Domain Information
The domain 'www.stopfakes.gov' uses the United States government-restricted top-level domain (.gov) with subdomain 'www'. Its registrable label 'stopfakes' stretches across 9 characters containing 3 vowels alongside six consonants. Tokenizing the label suggests 2 words: stop, fakes. Average segment length settles at 4.5 characters. 'stop' is most common in Chinese (Pinyin) usage. Usage also turns up in English and Danish contexts. Overall, 'www.stopfakes.gov' reads as Chinese (Pinyin).
Screenshot
Page Load Overview
Language Analysis
Primary Language
Detection Details
Website Classification
Primary Category
All Detected Categories
Detected Features
Domain & IP Information
| Requests | IP Address | Location | AS Autonomous System |
|---|---|---|---|
| 7 | 13.33.187.40 | New York, New York, United States | AS16509AMAZON-02 |
| 1 | 51.124.91.155 | Amsterdam, North Holland, Netherlands | AS8075MICROSOFT-CORP-MSN-AS-BLOCK |
| 1 | 13.33.187.64 | New York, New York, United States | AS16509AMAZON-02 |
| 1 | 2600:9000:235a:8600:a:4fc7:79c0:93a1 | Netherlands | Unknown |
| 1 | 13.33.187.48 | Netherlands | Unknown |
| 1 | 2600:9000:235a:7e00:a:4fc7:79c0:93a1 | Netherlands | Unknown |
| 1 | 2600:9000:235a:ae00:a:4fc7:79c0:93a1 | Netherlands | Unknown |
| 1 | 13.33.187.112 | Netherlands | Unknown |
| 1 | 2600:9000:235a:be00:a:4fc7:79c0:93a1 | Netherlands | Unknown |
| 1 | 2600:9000:235a:f000:a:4fc7:79c0:93a1 | Netherlands | Unknown |
| 19 | 13 | - | - |
Detected Technologies4
Content Similarity HashesFor malware variant detection
TLSH (Trend Micro Locality Sensitive Hash)
Security-focusedSpecialized for malware detection and similarity analysis
ssdeep (Context Triggered Piecewise Hashing)
Context-awareDetects similar content even with modifications
sdhash (Similarity Digest Hashing)
High-precisionHigh-precision similarity detection for forensic analysis
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
Other Hashes
Scan History
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