Summary
API
Submitted URL: https://phishbowl.unm.edu
The Cisco Umbrella rank of the primary domain is #60,226 of the top 1 million websites
AI Security Verdict
Safe Website
Confidence: 94%
Genuine University of New Mexico ISPO 'Phish Bowl' phishing-awareness page on unm.edu, with no credential or payment forms, no impersonation and no threat-intel hits.
Safety Factors (5)
Details
Page Title
Phish Bowl :: UNM Information Security & Privacy Office | The University of New Mexico
Scan Type
public
Domain Name Analysis
The domain 'phishbowl.unm.edu' uses the sponsored educational top-level domain (.edu) with subdomain 'phishbowl'. Its registrable label 'unm' stretches across 3 characters split between 1 vowel and 2 consonants. Segmentation suggests 2 words: un, m. Expect 1.5 characters per word on average. No strong language cues emerged from the frequency lists.
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 |
|---|---|---|---|
| 31 | 64.106.65.197 | Albuquerque, New Mexico, United States | AS3388University of New Mexico |
| 27 | 129.24.172.164 | Albuquerque, New Mexico, United States | AS3388University of New Mexico |
| 27 | 104.16.40.28Cloudflare · WAF | United States | AS13335Cloudflare, Inc. |
| 27 | 142.251.20.97Google · CDN | United States | AS15169Google LLC |
| 27 | 104.18.19.62Cloudflare · WAF | United States | AS13335Cloudflare, Inc. |
| 27 | 157.240.0.6Facebook · CDN | Frankfurt am Main, Hesse, Germany | AS32934Facebook, Inc. |
| 27 | 23.36.162.89Akamai · CDN | Frankfurt am Main, Hesse, Germany | AS20940Akamai International B.V. |
| 27 | 104.18.22.56Cloudflare · WAF | United States | AS13335Cloudflare, Inc. |
| 27 | 23.212.218.26Akamai · CDN | Frankfurt am Main, Hesse, Germany | AS16625Akamai Technologies, Inc. |
| 27 | 142.251.13.121Google · CDN | United States | AS15169Google LLC |
| 949 | 35 | - | - |
Detected Technologies7
Content Similarity HashesFor malware variant detection
TLSH (Trend Micro Locality Sensitive Hash)
Specialized for malware detection and similarity analysis
ssdeep (Context Triggered Piecewise Hashing)
Detects 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
Scan history not available
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