Security Scan Report: pro.doctolib.de

Redirected to:
https://auth.doctolib.de/pro/realms/doctolib-pro/protocol/openid-conne...
Site favicon
Submitted: Sep 28, 2026, 10:39:35 AMCompleted: Sep 28, 2026, 10:40:09 AMpubliccompleted

This website contacted 12 IPs in 3 countries across 10 domains to perform 78 HTTP transactions. The main domain is auth.doctolib.de and was registered 13 years ago.

Submitted URL: https://pro.doctolib.de

Effective URL:

https://auth.doctolib.de/pro/realms/doctolib-pro/protocol/openid-conne...
Redirected

The Cisco Umbrella rank of the primary domain is #220,128 of the top 1 million websites

AI Security Verdict

Safe Website

Confidence: 92%

0
Risk Score

Official Doctolib practitioner login page on doctolib.de, using its own OIDC/SSO flow to auth.doctolib.de. No phishing, malware, or credential-harvesting indicators found.

Safety Factors (4)
Official Doctolib domain with well-established registration age (3+ years)
Same-organisation SSO redirect (pro.doctolib.de → auth.doctolib.de), both owned by Doctolib
No credential-harvesting form, no brand impersonation, no IoC/YARA/IDS/Safe-Browsing evidence
Standard German privacy/compliance content (cookie consent, Impressum, Datenschutz)
Domain age information unavailable

Details

Page Title

Doctolib

Scan Type

public

Domain Name Analysis

Within the German country-code top-level domain (.de), 'pro.doctolib.de' is registered with subdomain 'pro'. Its registrable label 'doctolib' stretches across 8 characters with 3 vowels and five consonants. It segments into 3 words: doc, to, lib. Average segment length settles at three characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://pro.doctolib.de

Page Load Overview

0.91s
Total Load Time
2.9 MB
Total Size

Language Analysis

Primary Language

🇩🇪German
Code: de
Confidence:80%
Script:Latin
Direction:ltr

Detection Details

HTML Lang Attribute:de
Text Length:1,438 chars
Detector Agreement:67%

Website Classification

Primary Category

technology software56% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

technology software
56%
healthcare medical
48%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
1293.115.102.106Cloudflare · CDNFrance
AS209242Cloudflare London, LLC
693.115.102.100Cloudflare · CDNFrance
AS209242Cloudflare London, LLC
63.174.46.118Cloudfront · CDNUnited States
AS16509Amazon.com, Inc.
693.115.102.102Cloudflare · CDNFrance
AS209242Cloudflare London, LLC
693.115.102.103Cloudflare · CDNFrance
AS209242Cloudflare London, LLC
63.174.46.44Cloudfront · CDNUnited States
AS16509Amazon.com, Inc.
693.115.102.162Cloudflare · CDNFrance
AS209242Cloudflare London, LLC
63.174.46.38Cloudfront · CDNUnited States
AS16509Amazon.com, Inc.
693.115.102.161Cloudflare · CDNFrance
AS209242Cloudflare London, LLC
6104.17.25.14Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
7812--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T134C36E6BE2D0B95CF77F4621F6A0325872116202F926DCBFA20251DB7A83DD1893F52D

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

768:oA/cuJnzgPE4rPSbBn2WTST5/07EOCIvwRbUCv7ydq6UWsv6c+galFXaq7GCM:71JnzgPhrPSPSO0tRv70q6UWsKqqzM

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:123426:sVqDgIDF2hARYVQyFRE0mQMgEMYAJSAIA2gEoDUDmCCoAEgwAYIQMBOokJKbKhszIiLMEYsAE2BoA4EJi6UCI8agBisgaBIG

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:00783c7c7c7c7c00
Perceptual Hash:c89d266335363d1e
Difference Hash:8ce1f1f9f9f9e982
Wavelet Hash:607c7c7c7c7c7c00
Color Hash:#1f937e

Other Hashes

Scan History

Scan history not available

Unable to load historical scan data