Security Scan Report: www.stat.berkeley.edu

Submitted: Mar 17, 2026, 9:27:36 AMCompleted: Mar 17, 2026, 9:29:41 AMpubliccompleted
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Summary

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

Submitted URL: https://www.stat.berkeley.edu/~brill/Stat248/ensoseriesnewer.pdf

The Cisco Umbrella rank of the primary domain is #29,723 of the top 1 million websites

AI Security Verdict

Safe Website

Confidence: 96%

0
Risk Score

Legitimate academic PDF; no security concerns detected.

Safety Factors
Established academic domain with high Cisco Umbrella ranking (29723)
No malicious Indicators of Compromise
No credential or payment collection mechanisms
Content is a static PDF about ENSO, no interactive elements
Domain age information unavailable

Details

Page Title

N/A

Scan Type

public

Language

🇧🇩

BN

(43% confidence)

Category

unknown

(0%)

Domain Information

You're looking at domain 'www.stat.berkeley.edu' on the sponsored educational top-level domain (.edu) and includes subdomain 'www.stat'. The second-level label 'berkeley' is 8 characters long containing 3 vowels alongside five consonants. Segmentation suggests one word: berkeley. Median word length comes out to eight characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://www.stat.berkeley.edu/~brill/Stat248/ensoseriesnewer.pdf

Page Load Overview

3.12s
Total Load Time
2
HTTP Requests
1
Domains
607 KB
Total Size

Language Analysis

Primary Language

🇧🇩Bengali
Code: bn
Confidence:43%
Script:Unknown
Direction:ltr

Detection Details

Language Code:bn
Detection Confidence:43%
Script Type:Unknown
Text Length:10,000 chars
Detector Agreement:100%

Website Classification

Primary Category

unknown0% confidence
Type: unknown
Method: ML-based

All Detected Categories

No categories detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
2128.32.135.2Oakland, California, United States
AS25University of California at Berkeley
21--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T15F15A53BC8E912BE7BDC42AFA7885DA71391330C95B31D6930913B954A5C59F0F223B6

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

24576:IKJyhPJyhvRUYWMDjV/lH9kuMHkuHHEDThFiJPt9HBAFiJPt9HB2G5k1eN+LbJW:IKJyhPJyhvRUYWM/V/ldkuMHkuHHEXha

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:930249:XjWIcQrkAIqWqGHUkYBOwwEIKxEhQFrxnABEGGkBARECQAFBSEZMVIBgAQCBLwKwVKqBcQldL7QKkMUUkEkQDBHDaCMjjAZC

These hashes enable detection of similar websites and malware variants by comparing content similarity even when exact matches aren't found.

Scan History

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