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Security Scan Report: openam-univofphoenix-usw2.id.forgerock.io

Redirected to: https://openam-univofphoenix-usw2.id.forgerock.io/login/#/

Submitted: Feb 25, 2026, 1:08:39 AMCompleted: Feb 25, 2026, 1:10:01 AMpubliccompleted
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Summary

This website contacted 3 IPs in 2 countries across 3 domains to perform 37 HTTP transactions. The main domain is openam-univofphoenix-usw2.id.forgerock.io and was registered NaN years ago.

Submitted URL: https://openam-univofphoenix-usw2.id.forgerock.io

Effective URL: https://openam-univofphoenix-usw2.id.forgerock.io/login/#/Redirected

The Cisco Umbrella rank of the primary domain is #52,669 of the top 1 million websites

AI Security Verdict

Safe Website

Confidence: 95%

0
Risk Score

Legitimate login page for ForgeRock OpenAM with no malicious indicators.

Safety Factors
Well‑established domain
High Cisco Umbrella ranking
No malicious Indicators of Compromise
No credential exfiltration observed
Login form present on legitimate subdomain of forgerock.io
Domain age information unavailable

Details

Page Title

Login

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

technology software

(42%)

Domain Information

Within the British Indian Ocean Territory country-code top-level domain (.io), 'openam-univofphoenix-usw2.id.forgerock.io' is registered with subdomain 'openam-univofphoenix-usw2.id'. The second-level label 'forgerock' is 9 characters long containing three vowels alongside six consonants. Tokenizing the label suggests 2 words: forge, rock. Median word length comes out to 4.5 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://openam-univofphoenix-usw2.id.forgerock.io

Page Load Overview

2.17s
Total Load Time
15
HTTP Requests
3
Domains
1.9 MB
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:107 chars
Detector Agreement:100%

Website Classification

Primary Category

technology software42% confidence
Type: static
Method: ml+structural

All Detected Categories

technology software
42%
adult content
40%
news media journalism
37%
healthcare medical
32%
documentation technical
32%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
534.149.207.11Kansas City, Missouri, United States
AS396982Google LLC
534.102.193.34Kansas City, Missouri, United States
AS396982Google LLC
5178.63.2.112Falkenstein, Saxony, Germany
AS24940Hetzner Online GmbH
153--

Detected Technologies6

X-UA-Compatible
100%
Google Cloud
50%
Vue.js
40%
HTTP/3
40%
HSTS
40%
Google Cloud CDN
40%

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T10A52B91BA910253F20B3CADC64F26F5B223FC325C9291979ED894BA41FE5C94BD3E191

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

192:PTDyNfjo+77sGV+RCWwGErGE+dmA+dm0+GmA+dm0x/m0Hm0Hm0DIuyfYipsudTrx:YjL7sxR/DyfY6vd3TCVpcrzF

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:13471:EhIpMoIIIABqKVDGqCHYKRJetixCFAEjEIaoodHR27Ik4qkkCBCIhUQwSUFCLMCAISABAY4CEiUkUnQGMEAARUigjEFl8kMk

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:ffffe7ffffe7e7ff
Perceptual Hash:b3cccc3399662699
Difference Hash:10282828304d4c30
Wavelet Hash:f7dbc3db1800180c
Color Hash:#87bdc5

Other Hashes

Crop Resistant:10282828304d4c30

Scan History

Scan history not available

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