IP-Find: A Free IP Intelligence and Network Diagnostic Tool What I Built

An La — Mon, 02 Nov 2026 12:29:39 +0000

What I Built

Hey everyone! 👋

I'm excited to share my latest project: IP-Find.

I'm a no-code enthusiast interested in AI, web scraping, IP intelligence, and network technologies. With the help of AI-powered development tools, I built IP-Find to make IP detection and network analysis more useful and accessible.

Unlike traditional IP lookup tools that mainly provide basic location information, IP-Find combines multiple public IP intelligence sources to provide a more comprehensive view of an IP address.

Key features include:

🌍 IP Lookup: Detect public IPv4/IPv6 addresses, geolocation, ISP, and ASN information.
🔍 Multi-Source Detection: Integrate 16 public IP intelligence sources across different categories for cross-reference.
🤖 AI IP Risk Scoring: Evaluate IP network characteristics for services such as ChatGPT, Claude, Gemini, and more.
📊 Scenario-Based Assessment: Provide reference risk assessments for AI applications, TikTok, social media, and cross-border e-commerce.
🛡️ Network Diagnostics: Detect potential WebRTC leaks and provide DNS diagnostics.
⚡ Connectivity Testing: Test network connectivity to selected websites and AI platforms.
🔗 Free JSON API: Allow developers to integrate IP lookup functionality into their own projects without API key registration.

One of the features I'm most excited about is the AI-oriented IP scoring system. Instead of using one universal standard, IP-Find applies different reference rules based on the target platform and usage scenario.

My goal is to make IP information more actionable for developers and technical users.

Demo

🌐 Live Website: https://ip-find.com/

Try it yourself! You can check your current IP, explore multiple intelligence sources, test network connectivity, and view AI-oriented IP risk assessments.

API Documentation: https://ip-find.com/docs

Scoring Methodology: https://ip-find.com/ai-ip-method

No registration required. Just open the website and give it a try!

Partner Technologies

I built this project with the help of AI-powered development tools and a no-code development workflow.

AI played an important role in helping me explore technical solutions, develop features, refine detection logic, and turn ideas into a working product.

I also integrated multiple public IP intelligence providers and network data sources to build a more comprehensive IP analysis experience.

I haven't integrated a specific MLH partner technology into this project yet, but I'm looking forward to exploring more technologies and learning from the community.

Hackathon Experience

This project represents my enthusiasm for AI-assisted development and building useful tools as an independent creator.

I'm still learning, experimenting, and improving my development skills. Participating in the DEV community challenge is a great opportunity for me to share what I've built, discover new technologies, and connect with developers who have similar interests.

Since IP-Find is still a newly launched project, I'm especially looking forward to receiving feedback from the community.

I'd love to hear your thoughts!

What other IP intelligence sources should I integrate?
What features would make this tool more useful?
How could I improve the current IP risk scoring methodology?

Feel free to try it, share your feedback, or suggest new ideas!

Thanks for checking out my project. Let's keep building and learning together! 🚀

Project: https://ip-find.com/

I Built a Free IP Intelligence Tool with Multi-Source Detection and AI-Oriented Risk Scoring — Meet IP-Find

An La — Mon, 02 Nov 2026 12:05:38 +0000

Hey DEV Community! 👋

I'm excited to introduce a small project I've recently built: IP-Find.

I'm a no-code enthusiast with a strong interest in AI, web scraping, IP intelligence, and network-related technologies. I've been experimenting with AI-powered development tools and using them to turn ideas into practical little utilities.

IP-Find is one of my recent projects.

The idea started with a simple question:

Why do most IP lookup tools only tell you where an IP address is located, but don't really help you understand whether that IP is suitable for a particular use case?

For example:

Is this IP coming from a residential network or a data center?
Is it associated with a proxy, VPN, or Tor exit node?
Are there any DNS or WebRTC leaks?
Is this IP suitable for accessing AI services such as ChatGPT, Claude, or Gemini?
Does this IP look appropriate for a particular target market or application?

I wanted to build something that could provide more useful information than a basic IP lookup.

That's how IP-Find came to life.

🌐 Website: https://ip-find.com/

1. What Is IP-Find?

IP-Find is a free IP intelligence and network diagnostic tool designed to help developers, researchers, and everyday users better understand their network environments.

It supports both IPv4 and IPv6 and provides several types of network information and diagnostic capabilities in one place.

The main features include:

Public IP address detection
IP geolocation and ISP information
ASN and network organization lookup
Proxy, VPN, hosting, and Tor detection
Multi-source IP intelligence
AI service IP risk assessment
Scenario-based IP risk scoring
WebRTC leak detection
DNS resolver and egress detection
IP connectivity testing
Batch IP lookup
Local query history
Free JSON API

The goal is to make IP information easier to understand and more useful for real-world applications.

2. Multi-Source IP Intelligence: More Than a Single Database

This is one of the features I particularly wanted to focus on.

Many basic IP lookup tools rely on one or a small number of geolocation databases. However, different databases can return different information for the same IP address.

An IP might be classified as residential by one provider but identified as hosting infrastructure by another.

Instead of relying on a single source, IP-Find combines multiple public data sources and cross-checks information from different perspectives.

Currently, the main IP information providers include:

ip-api.com
ipwho.is
ip.sb
IPinfo
Tor Project

In addition, IP-Find integrates a reference panel covering 16 public data sources across six categories:

Category	What it helps identify
Registration	IP allocation and registration information
Identity	Network ownership and organization details
Routing	ASN and routing-related information
Proxy Detection	Proxy, VPN, and hosting-related signals
Threat Intelligence	Public threat and abuse indicators
Exposure	Internet-facing assets and exposure signals

Some of the additional sources include:

RIR RDAP
RIPEstat
IP2Location
Shodan InternetDB
Spamhaus DROP
proxycheck.io
IPsum
Feodo Tracker
DShield
Blocklist.de

The purpose of combining these sources is not simply to collect more data.

It's to provide a broader picture of an IP address and make it easier to identify inconsistencies between different intelligence providers.

One important detail: different databases have different definitions and update schedules. A missing record does not automatically mean an IP is clean or safe.

The multi-source reference panel is designed to provide additional evidence, rather than blindly turning every data point into a risk conclusion.

3. AI-Oriented IP Risk Scoring

This is probably the feature I'm most excited about.

With the growing adoption of AI services, developers increasingly need to understand whether their network environment is suitable for accessing different AI platforms.

However, a conventional IP lookup usually provides only basic information such as country, city, ISP, and ASN.

I wanted to take this a step further.

IP-Find introduces a lightweight IP risk scoring model for several popular AI services, including:

ChatGPT
OpenAI API
Claude
Gemini App
Gemini API
Grok
Perplexity
Microsoft Copilot

Rather than assigning one universal score to every platform, the tool uses different reference rules for different services.

The scoring model considers several factors:

1. Geographic Availability

Whether the IP's country or region is included in the relevant service's officially published availability information.

2. Network Type

Whether the IP appears to belong to:

Residential networks
Data center infrastructure
Proxy or VPN networks
Tor exit nodes
Mobile networks
Organization networks

3. IP Reputation

Where an actual reputation data source is available, its signals can be considered. If a reputation feed is not connected, the tool reports that information as unavailable rather than assuming the IP has no negative records.

4. Original IP and Time Zone Consistency

The scoring model also considers whether the IP appears to be a native network address and whether the browser's time zone is reasonably consistent with the IP's estimated time zone.

Based on these signals, IP-Find calculates a reference score from 0 to 100.

The general interpretation is:

Score	Interpretation
75–100	Relatively stable
45–74	Use with caution
1–44	Higher network risk
0	Not suitable under the applicable rules

One important design decision: Gemini App and Gemini API are evaluated separately because their officially supported regions are not necessarily identical.

I also avoid treating a high score as a guarantee of successful access.

The score only evaluates network-layer characteristics. It cannot determine account history, phone number region, payment information, browser fingerprints, cookies, or a platform's internal risk decisions.

You can read the scoring methodology here:

https://ip-find.com/ai-ip-method

4. Scenario-Based IP Risk Assessment

Different applications have different network requirements.

An IP that works well for ordinary browsing may not necessarily be suitable for social media management, cross-border e-commerce, or accessing AI services.

That's why I added scenario-based scoring.

Currently, the tool provides reference assessments for:

TikTok and short-video platforms
Cross-border e-commerce
Social media operations
AI applications

For example, when evaluating an IP for cross-border e-commerce, the system considers network type, target market consistency, and other available risk signals.

Users can select a target market or account registration region to obtain a more relevant assessment.

I deliberately designed this feature so that the system does not automatically assume your current IP country is your target market.

If no target market is selected, the tool will not generate a misleading scenario score.

The idea is simple:

An IP address should be evaluated in the context of how you intend to use it, rather than judged by a single universal standard.

5. WebRTC and DNS Leak Detection

IP location and network classification are only part of network diagnostics.

Sometimes, users may also want to know whether their browser or DNS configuration is exposing additional network information.

IP-Find includes two additional diagnostic tools.

WebRTC Leak Detection

WebRTC can expose local or public network addresses through browser networking mechanisms.

IP-Find uses the browser's native RTCPeerConnection functionality to collect ICE candidates and check whether additional addresses are exposed.

The detection runs directly in the browser.

DNS Egress Detection

The DNS diagnostic feature uses EDNS Client Subnet-related information to help identify the DNS resolver's apparent network location.

There is one important technical limitation worth mentioning:

When the service runs on a remote server, the DNS result represents the server's DNS egress, not necessarily the visitor's local DNS environment.

IP-Find explicitly labels the result perspective to avoid confusing server-side information with the user's own network.

6. IP Connectivity Testing

Another useful feature is browser-based connectivity testing.

You can test whether your current network can directly reach selected domestic and international websites and AI platforms.

The test provides information about:

Network reachability
Connection response time
Whether a request times out or fails

All tests are initiated directly from your browser rather than being routed through the IP-Find server.

This makes it useful for quickly checking your current network environment.

Please note that connectivity results only reflect the current network conditions. A failed request does not necessarily mean the target website is unavailable, and successful connectivity does not guarantee that an account can use the service.

7. Batch IP Lookup and Query History

For users who need to investigate multiple IP addresses, IP-Find also supports batch lookup.

You can enter multiple IP addresses and view information such as:

IP address
Geographical location
ISP and organization
ASN
Network type
Risk information

There's also a local query history feature.

You can review previous lookup results, clear your history, or export the records as JSON.

One thing I wanted to keep simple: query history is stored in your browser's local storage rather than being maintained as a server-side user account history.

8. Free JSON API for Developers

I also wanted IP-Find to be useful beyond its web interface.

That's why I made its JSON API publicly accessible.

Currently, the API offers:

No API key required
No account registration required
JSON responses
IPv4 and IPv6 support
Interactive API documentation
OpenAPI specification
IP-based rate limiting to prevent abuse

Developers can integrate IP lookup and network information into their own scripts, applications, or workflows.

API documentation:

https://ip-find.com/docs

OpenAPI specification:

https://ip-find.com/openapi.json

I hope this makes IP-Find useful not only for individual users but also for developers who want to build their own tools.

9. Privacy and Data Handling

Privacy was another consideration during development.

IP-Find currently does not require user registration and does not maintain a user account system.

Some of the privacy-related design choices include:

No account registration required.
Query history is stored locally in your browser.
Query caching is kept in memory and expires automatically after 15 minutes.
WebRTC ICE candidate analysis is performed locally in the browser.
Google Analytics is loaded only if the visitor gives consent.
No advertising or data-selling business model.

IP addresses submitted for lookup may be sent to the relevant public data providers to retrieve their information.

The server also maintains limited security and abuse-prevention logs with automatic rotation.

You can find more details in the privacy section of the website.

10. Why I Built This Project

To be honest, IP-Find is still a young project.

I'm not a professional software engineer working with a large development team. I'm someone who enjoys exploring technology, experimenting with AI tools, and building small utilities that solve practical problems.

I believe AI-assisted development has made it much easier for individuals to turn ideas into working products.

Instead of just learning about technologies theoretically, I wanted to build something that other people could actually use.

IP-Find is my attempt to combine several things I'm interested in:

AI-assisted development
IP intelligence and network diagnostics
Public data source integration
Practical risk assessment
Developer-friendly tools and APIs

There are still many things I would like to improve.

For example:

More reliable and comprehensive IP intelligence sources.
Better detection accuracy and more transparent scoring rules.
More useful APIs for developers.
Additional diagnostic capabilities.
Better documentation and practical use cases.

I'm also very interested in hearing how other developers approach IP intelligence and network risk assessment.

11. Give It a Try and Share Your Feedback!

IP-Find has just been launched, and I'd really appreciate it if some of you could give it a try.

🌐 Website: https://ip-find.com/

Whether you're an AI developer, web developer, data engineer, cybersecurity enthusiast, or someone who simply wants to understand their network environment, I'd love to hear your thoughts.

Some questions I'm particularly interested in:

What additional IP intelligence sources would you recommend integrating?
What other factors should be considered in an IP risk scoring model?
Are there any useful IP diagnostic features you think are missing?
Would you find the public JSON API useful in your own projects?
How would you improve the current AI-oriented IP scoring methodology?

Please feel free to leave comments, report bugs, or share suggestions.

This project is still at an early stage, and I'm hoping to make it better with feedback and ideas from the developer community.

If you find it useful, feel free to bookmark it or share it with someone who might need it.

Thanks for reading, and I'm looking forward to connecting with more like-minded developers here on DEV! 🚀

Built with curiosity, AI tools, and a passion for making useful things.

IP-Find — A free IP intelligence and network diagnostic toolkit.

https://ip-find.com/

DEV Community: An La