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

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.

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?

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

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

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:

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

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.

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.

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

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

The scoring model considers several factors:

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

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.

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.

You can read the scoring methodology here:

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:

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.

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

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 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.

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.

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.

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.

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:

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.

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

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

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

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

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:

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.

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:

There are still many things I would like to improve.

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

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

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:

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.