Security Scan Report: igit.me

Redirected to:
https://webmail-spectrum-net-login1.framer.website/
Submitted: Oct 6, 2026, 6:32:37 AMCompleted: Oct 6, 2026, 6:33:11 AMpubliccompleted

This website contacted 15 IPs in 3 countries across 8 domains to perform 32 HTTP transactions. The main domain is webmail-spectrum-net-login1.framer.website and was registered 14 years ago.

Submitted URL: https://igit.me/DJbZm

Effective URL:

https://webmail-spectrum-net-login1.framer.website/
Redirected

AI Security Verdict

High Risk

Confidence: 84%

8
Risk Score

Flagged shortener redirects to a Framer-hosted page masquerading as an ISP 'webmail' sign-in; the destination domain and entry URL both carry phishing threat-intel hits. Do not enter any account details.

Risk Factors (5)
Content-malware (phishing) threat-intel match on the scanned page's primary domain
Multi-source phishing reports on the redirector domain and the exact entry URL
Deceptive hostname mimicking a named ISP webmail sign-in on a free Framer subdomain
Off-domain redirect from a flagged shortener straight into a 'Sign into Webmail' page
Scanner-vs-real-client content mismatch: datacenter scanners were served a bot-protection page while residential clients got the real 'Sign into Webmail' content (evasion consistent with a phishing kit)
Domain age information unavailable

Details

Page Title

https://igit.me/DJbZm

Scan Type

public

Domain Name Analysis

The domain 'igit.me' uses the Montenegrin country-code top-level domain (.me) and has no subdomain. Count 4 characters in 'igit' with two vowels and 2 consonants. Word splitting yields two words: ig, it. Expect 2 characters per word on average. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://igit.me/DJbZm

Page Load Overview

1.45s
Total Load Time
399 KB
Total Size

Language Analysis

Primary Language

🇺🇸English
Code: en
Confidence:55%
Script:Latin
Direction:ltr

Detection Details

Text Length:156 chars
Detector Agreement:100%

Website Classification

Primary Category

technology software59% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

technology software
59%
documentation technical
25%
corporate
25%

Detected Features

OG: website

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
4184.174.39.202Lauterbourg, Grand Est, France
AS51167Contabo GmbH
2192.178.183.97Google · CDNUnited States
AS15169Google LLC
231.43.160.6Aws · CLOUDNetherlands
AS16509Amazon.com, Inc.
218.64.211.76Cloudfront · CDNUnited States
AS16509Amazon.com, Inc.
265.9.130.75Cloudfront · CDNUnited States
AS16509Amazon.com, Inc.
265.9.130.22Cloudfront · CDNUnited States
AS16509Amazon.com, Inc.
265.8.131.73Cloudfront · CDNUnited States
AS16509Amazon.com, Inc.
265.9.130.59Cloudfront · CDNUnited States
AS16509Amazon.com, Inc.
265.9.130.25Cloudfront · CDNUnited States
AS16509Amazon.com, Inc.
265.9.130.107Cloudfront · CDNUnited States
AS16509Amazon.com, Inc.
3215--

Detected Technologies5

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T18081318B29F340017D5394A81BF77B09766AE003D00BCD693FCDA288CF8569A499279C

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

96:T50FZvrhfkEDY1n6n1PfKZLSqYXkEVmupi:t0bvrhfkv41PfmLSqYLdpi

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:4197:QFAAgAIQrQA0AACEDIAQIBAACwCAQDEAFA2gRQAAQSUABgyKgCgCAIQIIaJQggAAQAECYCBkCACgAAAFKZIAYAAAGNgAIUAg

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:ffffffe7c3ffffff
Perceptual Hash:b389cc663399cc66
Difference Hash:0000000c0c000000
Wavelet Hash:0f0f2f0303030f0f
Color Hash:#40bf51

Other Hashes

Crop Resistant:0000000c0c000000

Scan History

Scan history not available

Unable to load historical scan data