ScanMalware.com

Security Scan Report: jambi.sigapnews.co.id

Site favicon
Submitted: Aug 3, 2026, 8:39:00 AMCompleted: Aug 3, 2026, 8:40:23 AMpubliccompleted
Loading additional data...

Summary

This website contacted 7 IPs in 3 countries across 8 domains to perform 2 HTTP transactions. The main domain is jambi.sigapnews.co.id and was registered NaN years ago.

Submitted URL: https://jambi.sigapnews.co.id

The Cisco Umbrella rank of the primary domain is #515,830 of the top 1 million websites

AI Security Verdict

Low Risk

Confidence: 72%

3
Risk Score

The site appears to be a legitimate news outlet with no phishing or malware indicators, but limited reputation warrants moderate caution.

Safety Factors
Established domain age
Self‑branding (no brand impersonation)
Absence of malicious scripts or exfiltration behavior
Verdict cited a credential/login form, but DOM analysis found no password field (real or disguised) or payment field, and no other hard signal — credential-phishing framing unsupported; risk adjusted from 4 to 3
Domain age information unavailable

Details

Page Title

Media siber Jambi terpercaya dan terkini

Scan Type

public

Language

🇺🇸

English

(34% confidence)

Category

news media journalism

(55%)

Domain Information

Within the Indonesian country-code top-level domain (.co.id), 'jambi.sigapnews.co.id' is registered; it also runs on subdomain 'jambi'. Count 9 characters in 'sigapnews' containing three vowels alongside 6 consonants. Word splitting yields 3 words: si, gap, news. Average segment length settles at three characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://jambi.sigapnews.co.id

Page Load Overview

0.52s
Total Load Time
6
HTTP Requests
3
Domains
105 KB
Total Size

Language Analysis

Primary Language

🇺🇸English
Code: en
Confidence:34%
Script:Latin
Direction:ltr

Detection Details

Language Code:en
Detection Confidence:34%
Script Type:Latin
Text Length:65,781 chars
Detector Agreement:80%

Website Classification

Primary Category

news media journalism55% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

news media journalism
55%
government public service
53%
forum community discussion
39%
education learning
36%
healthcare medical
33%

Detected Features

OG: article

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
6103.146.203.63Indonesia
AS136052PT Cloud Hosting Indonesia
0142.251.14.97Google · CDNUnited States
AS15169Google LLC
092.113.23.62Frankfurt am Main, Hesse, Germany
AS47583Hostinger International Limited
0142.251.13.95Google · CDNUnited States
AS15169Google LLC
0142.251.110.154Google · CDNUnited States
AS15169Google LLC
0104.17.24.14Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
0104.17.198.65Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
67--

Detected Technologies4

Google-AnalyticsvUniversal
100%
WordPress
75%
Hostinger CDN
40%
HTTP/3
40%

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T15AB48231F840293F6B3B04C4E749D71A71DAA31FF4E90810E6E6476846E9E78F51E2A7

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

1536:KOrLvmW7p/Mi/Si3C/97bNDsfRSOMMZPAAukWZZ3Vvnlg/hLL/3hianxUermutW2:KOh7JMuuoyMBAOhijoXF

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:500169:QBEKJSEVBfDDBZkdoMgMQMgMBFhEAaCZAQLQFhQHRNJwAwETCnBB1KouCIEYSB+UbJhBAYCAfJAgHQpnCihgg4gCOEAFCYiE

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:00ffffcf07c7fbfb
Perceptual Hash:b05fcf3038cf3238
Difference Hash:324400be9e8e8696
Wavelet Hash:00ffff470202f2f2
Color Hash:#864f2d

Other Hashes

Crop Resistant:324400be9e8e8696,4018626262300000,d9d998989834a0a0

Scan History

Scan history not available

Unable to load historical scan data