Security Scan Report: precip.ai

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Submitted: Dec 27, 2025, 11:06:01 AMCompleted: Dec 27, 2025, 11:06:43 AMpubliccompleted
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Summary

This website contacted 16 IPs in 2 countries across 18 domains to perform 143 HTTP transactions. The main domain is precip.ai and was registered NaN years ago.

Submitted URL: https://precip.ai/snow-totals/zipcode/07871

The Cisco Umbrella rank of the primary domain is #999,480 of the top 1 million websites

AI Security Verdict

Safe Website

Confidence: 92%

1
Risk Score

Legitimate site providing snow totals with minimal risk

Safety Factors
Established domain age
No malicious Indicators of Compromise
No credential or payment forms
Domain age information unavailable

Details

Page Title

Sparta, NJ (07871) Snow Totals & Accumulation - Precip

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

documentation technical

(47%)

Domain Information

Within the Anguillan country-code top-level domain (.ai), 'precip.ai' is registered. Count 6 characters in 'precip' split between 2 vowels and 4 consonants. Breaking it apart gives three words: pre, c, ip. Median word length is two characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://precip.ai/snow-totals/zipcode/07871

Page Load Overview

5.52s
Total Load Time
87
HTTP Requests
18
Domains
838 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
Text Length:2,551 chars
Detector Agreement:100%

Website Classification

Primary Category

documentation technical47% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

documentation technical
47%
healthcare medical
42%
government public service
37%
corporate
35%
adult content
33%

Detected Features

OG: website
Schema.org

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
12104.18.29.238United States
AS13335CLOUDFLARENET
52.18.64.212Frankfurt am Main, Hesse, Germany
AS20940Akamai International B.V.
5142.250.185.195United States
AS15169GOOGLE
513.35.58.77United States
AS16509AMAZON-02
5104.18.28.238United States
AS13335CLOUDFLARENET
551.77.64.70Germany
AS16276OVH SAS
5216.239.32.36United States
AS15169GOOGLE
5104.16.80.73United States
AS13335CLOUDFLARENET
5142.251.141.100United States
AS15169GOOGLE
566.102.1.156United StatesUnknown
8716--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1C544F8BCDB8088F877EF879C9E22169D2D2E106BE11027AEECF996651C7335C9415C87

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

3072:0rdLqUitNJR4fr3eVIS4cEL5nyRVJqS2P:0rdVnwB2P

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:264131:A7iWFBcABQRQ05QIAYhUEQPgSwLpWBRmQZoJEIchBtpQBkgdBYRCFCENCQjIVERBGFAiBA8MiEZgCWoqgAsIMDZgiQAAqyoG

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:4771616101010126
Perceptual Hash:a2499669b669b669
Difference Hash:8dc5d181210523cc
Wavelet Hash:ff77796101010177
Color Hash:#9179d2

Other Hashes

Scan History

Scan history not available

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