Maxmind IP Geolocation Archival Data Because of GDPR concerns, Maxmind doesn't provide historical data. We have used this data to do historical studies of IP data for MTurk, etc. and it is quite possible that such data would be useful elsewhere. Maxmind changed its db format from geolite to geolite2 and you will need to use its respective packages for the two formats to read the binary files. The data is provided for research purposes alone.

Commercial geolocation database with a free lower grade version.

Geo Open is an IP address geolocation per country in MMDB format. The database can be used as a replacement for software using the MMDB format. Information about MMDB format: https://maxmind.github.io/MaxMind-DB/ Open source server using Geo Open: https://github.com/adulau/mmdb-server Open source library to read MMDB file: https://github.com/maxmind/MaxMind-DB-Reader-python Historical dataset: https://cra.circl.lu/opendata/geo-open/ The database is automatically generated from public BGP AS announces matching the country code. The precision is at country level.

The IP address lookup market is experiencing robust growth, driven by the increasing reliance on online services and the expanding digital footprint across various sectors. The market's size in 2025 is estimated at $1.5 billion, projecting a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033. This expansion is fueled by several key factors: the proliferation of connected devices (IoT), the heightened demand for precise geolocation data for cybersecurity and fraud prevention, and the escalating need for personalized online experiences. Furthermore, the growing adoption of cloud-based solutions simplifies deployment and reduces costs, bolstering market growth. The market is segmented by application (SMEs and large enterprises) and type (cloud-based and on-premises). Cloud-based solutions currently dominate due to their scalability and cost-effectiveness, although on-premises deployments remain significant for organizations with stringent data security requirements. Large enterprises currently represent a larger share of the market due to their greater need for comprehensive IP address lookup solutions, but the SME segment is predicted to show faster growth due to increasing digital adoption. Geographic distribution showcases strong growth across North America and Europe, driven by mature digital infrastructures and high adoption rates. However, emerging markets in Asia-Pacific and the Middle East & Africa are anticipated to demonstrate significant growth potential in the coming years due to increasing internet penetration and digital transformation initiatives. Market restraints include concerns surrounding data privacy and regulations like GDPR, which necessitate robust compliance measures. Competition among numerous players, including MaxMind, IP2Location, and IPinfo, is intense, requiring continuous innovation and value-added service offerings to maintain a competitive edge. Despite these challenges, the long-term outlook for the IP address lookup market remains positive, with consistent growth projected throughout the forecast period driven by continuous technological advancements and increasing demand for location-based services. The rise of AI and machine learning will further enhance the accuracy and efficiency of IP address lookup technologies, shaping future market trends.

Traffic analytics, rankings, and competitive metrics for maxmind.com as of October 2025

Context

This dataset is meant to be used with other datasets that have features like country and city but no latitude/longitude. It is simply a list of cities in the world. Being able to put cities on a map will help people tell their stories more effectively. Another way to think about it is that you can use this make more pretty graphs!

Content

Fields:

• city
• region
• country
• population
• latitude
• longitude

Acknowledgements

These data come from Maxmind.com and have not been altered. The original source can be found by clicking here

Additionally, the Maxmind sharing license has been included.

Inspiration

I wanted to analyze a dataset and make a map, but I was only given a city name without any latitude or longotude coordinates. I found this dataset very helpful and I hoe you do too!

The IP address lookup market is experiencing robust growth, driven by increasing demand for geolocation services, cybersecurity solutions, and fraud prevention measures across various industries. The market's expansion is fueled by the proliferation of internet-connected devices, the rise of big data analytics, and the growing need for accurate user identification and location tracking. While cloud-based solutions dominate due to scalability and cost-effectiveness, on-premises deployments remain significant for organizations with stringent data security requirements. Large enterprises are major consumers, leveraging IP address lookups for targeted advertising, network security, and compliance purposes. SMEs, however, are increasingly adopting these solutions to improve customer experience and optimize online operations. The market is geographically diverse, with North America and Europe currently leading, but Asia-Pacific is projected to witness significant growth in the coming years due to rapid digitalization and expanding internet penetration. Competition is intense, with a mix of established players and emerging startups offering a range of services, from basic IP geolocation to advanced data intelligence and fraud detection tools. Factors hindering market growth include data privacy concerns, increasing regulatory scrutiny, and the potential for inaccurate or outdated IP data. The forecast period (2025-2033) anticipates continued market expansion, with a projected Compound Annual Growth Rate (CAGR) driving substantial revenue increases. This growth will be fueled by technological advancements in IP geolocation accuracy, integration with other analytical tools, and the emergence of innovative applications within industries like e-commerce, fintech, and advertising. While challenges related to data privacy and accuracy persist, ongoing innovation and industry consolidation are poised to mitigate these risks and drive wider adoption. The market segmentation will likely remain stable, with the continued dominance of cloud-based solutions and strong demand from both large enterprises and SMEs. Regional variations will persist, reflecting differing levels of digital infrastructure and regulatory frameworks across the globe. However, emerging economies in Asia-Pacific are likely to significantly increase their market share throughout the forecast period.

IPv6 ready websites are those having at least one AAAA in their DNS records (means the website is visible/can reply to users having an IPv6 connectivity). Tests are done every trimester through a script run by the IPv6 Observatory study on the 1 million most visited websites list provided by Alexa. Websites are attributed to countries on the basis of their main operation location as provided by MaxMind GeoIP database.

Original source

IPv6 Observatory, Study for the EC realized by inno:

http://www.ipv6observatory.eu/the-study/

Parent dataset

This dataset is part of of another dataset:

http://digital-agenda-data.eu/datasets/digital_agenda_scoreboard_key_indicators

Discover the booming IP address lookup market! Our in-depth analysis reveals a $250M (2025) market projected to reach $800M by 2033, driven by cybersecurity, location-based services, and IoT growth. Explore key players, market trends, and regional insights.

The IP address lookup market is experiencing robust growth, driven by the increasing reliance on location-based services, cybersecurity advancements, and the expanding digital footprint across various industries. The market, currently valued at approximately $250 million in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033. This growth is fueled by several key factors. Firstly, the rising demand for precise geolocation data for targeted advertising, fraud prevention, and personalized user experiences is a major catalyst. Secondly, the heightened concern regarding data privacy and security necessitates advanced IP address lookup solutions, leading to increased adoption among businesses of all sizes. Finally, the proliferation of IoT devices and the expanding use of cloud-based services further amplify the need for efficient and accurate IP address lookups. The market is segmented by application (SMEs and large enterprises) and by type (cloud-based and on-premises solutions), with cloud-based solutions dominating due to their scalability, cost-effectiveness, and ease of implementation. The competitive landscape features a mix of established players and emerging vendors, each offering diverse solutions to meet varying market demands. While some companies focus on comprehensive databases offering granular location details, others concentrate on providing APIs for seamless integration into existing systems. Regional growth varies, with North America and Europe currently holding a significant market share. However, rapidly developing economies in Asia-Pacific are expected to exhibit accelerated growth in the coming years, driven by increasing internet penetration and digital transformation initiatives. Restraints on market growth include concerns about data accuracy, potential privacy violations, and the emergence of new technologies that may offer alternative approaches to geolocation. Despite these challenges, the overall outlook for the IP address lookup market remains positive, with strong growth anticipated throughout the forecast period.

The IP Address Lookup market is booming, projected to reach $610 million by 2033 with a 15% CAGR. Driven by cybersecurity, IoT, and location-based services, this in-depth analysis explores market trends, key players (MaxMind, IP2Location), and regional growth. Discover the future of IP geolocation data.

IPinfo IP to Country ASN database

IPinfo's IP to Country ASN database is an open-access database that provides information on the country and ASN (Autonomous System Number) of a given IP address.

• It offers full accuracy and is updated daily.
• The database is licensed under CC-BY-SA 4.0, allowing for commercial usage.
• It includes both IPv4 and IPv6 addresses.
• There are two file formats available: CSV and MMDB.

Notebook

Please explore the provided notebook to learn about the dataset:

🔗 IPinfo IP to Country ASN Demo Notebook for Kaggle

Documentation

Detailed documentation for the IP to Country ASN database can be found on IPinfo's documentation page. Database samples are also available on IPinfo's GitHub repo.

🔗 Documentation: https://ipinfo.io/developers/ip-to-country-asn-database

Context and value

The IPinfo IP to Country ASN database is a subset of IPinfo's IP to Geolocation database and the ASN database.

The database provides daily updates, complete IPv4 and IPv6 coverage, and full accuracy, just like its parent databases. The database is crucial for:

• Cybersecurity and threat intelligence
• Open Source Intelligence (OSINT)
• Firewall policy configuration
• Sales intelligence
• Marketing analytics and adtech
• Personalized user experience

Whether you are running a web service or a server connected to the internet, this enterprise-ready database should be part of your tech stack.

Usage

In this dataset, we include 3 files:

• country_asn.csv → For reverse IP look-ups and running IP-based analytics
• country_asn.mmdb → For IP address information look-ups
• ips.txt → Sample IP addresses

Using the CSV dataset

As the CSV dataset has a relatively small size (~120 MB), any dataframe and database should be adequate. However, we recommend users not use the CSV file for IP address lookups. For everything else, feel free to explore the CSV file format.

Using the MMDB dataset

The MMDB dataset requires a special third-party library called the MMDB reader library. The MMDB reader library enables you to look up IP addresses at the most efficient speed possible. However, as this is a third-party library, you should install it via pip install in your notebook, which requires an internet connection to be enabled in your notebook settings.

Please see our attached demo notebook for usage examples.

IP to Country ASN provides many diverse solutions, so we encourage and share those ideas with the Kaggle community!

Sources

The geolocation data is produced by IPinfo's ProbeNet, a globe-spanning probe network infrastructure with 400+ servers. The ASN data is collected from public datasets like WHOIS, Geofeed etc. The ASN data is later parsed and structured to make it more data-friendly.

See the Data Provenance section below to learn more.

Please note that this Kaggle Dataset is not updated daily. We recommend users download our free IP to Country ASN database from IPinfo's website directly for daily updates.

Terminology

AS Organization - An AS (Autonomous System) organization is an organization that owns a block or range of IP addresses. These IP addresses are sold to them by the Regional Internet Organizations (RIRs). Even though this AS organization may own an IP address, they sometimes do not operate IP addresses directly and may rent them out to other organizations. You can check out our IP to Company data or ASN database to learn more about them.

ASN - ASN or Autonomous System Number is the unique identifying number assigned to an AS organization.

IP to ASN - Get ASN and AS organizat...

The IP Geolocation Service market is booming, projected to reach $15 billion by 2033, driven by OTT, e-commerce, and gaming. Explore market trends, leading companies (Digital Element, MaxMind, Neustar), and regional insights in this comprehensive analysis.

The IP Geolocation Solution market is booming, projected to reach $191.5 million by 2033, fueled by digital growth and increasing demand for fraud prevention and personalized services. Explore market trends, key players (Microsoft, MaxMind, TransUnion), and regional insights in this comprehensive analysis.

Hainan Maxmind Pharmaceutical Technology Co Limited Export Import Data. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.

Accurate, daily-updated country-level IP geolocation database. GeoIP-compatible, open license, free to download and use for any purpose.

Maxmind Biotechnology Hainan Co Limited Export Import Data. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.

The IP Address Lookup market is booming, projected to reach $5 billion by 2033 with a 15% CAGR. Driven by cybersecurity, location-based services, and e-commerce, this analysis reveals key trends, market segmentation, and leading companies. Explore the regional breakdown and growth forecasts for this rapidly expanding sector.

The IP Geolocation Software market is booming, projected to reach $5 billion by 2033 with a 15% CAGR. Discover key market trends, regional analysis, leading companies, and growth drivers in this comprehensive market report. Learn about the impact of cloud solutions, data privacy, and AI on this rapidly expanding sector.

The dataset contains DNS records, IP-related features, WHOIS/RDAP information, information from TLS certificate fields, and GeoIP information for 432,572 verified benign domains from Cisco Umbrella and 36,993 verified phishing domains from PhishTank and OpenPhish services. The dataset is useful for statistical analysis of domain data or feature extraction for training machine learning-based classifiers, e.g. for phishing detection. The data was collected between March and July 2023.The final assessment of the data was conducted in July 2023 (this is why the names are suffixed with _2307).

The upload contains: a) data files, b) the description of the data structure, and c) the veature vector we used for ML-based phishing domain detection.

Data Files

The data is located in two individual files:

• benign_2307.json - data about 432,572 benign domains, and
• phishing_2307.json - data about 36,993 phishing domains.

Data Structure

Both files are in the JSON Array format. The structure is as follows:

[
{
  "_id" : "A unique ID of the data record",
  "domain_name" : "Name of the domain (e.g., zenodo.com)",
  "dns" : { "//": "Data obtained from DNS records" },
  "evaluated_on" : "// ISO Timestamp of data collection ",
  "ip_data" : [  "// Data for each related IP adddress ",
    {
      "//": "IP-related data, including RTT from ICMP echo attempts (from Brno, Czechia)",
      "//": "WHOIS/RDAP data for the given IP address",
      "//": "GeoIP data for the given IP address",
      "//": "NERD system reputation score (if available)",
      "//": "ASN info",
      "//": "remarks: ISO timestamps of collection of the individual data pieces"
    },
  ],
  "label" : "benign_2307 for benign OR misp_2307 for phishing",
  "rdap" : { "//": "WHOIS/RDAP information for the domain name" },
  "remarks" : {
    "dns_evaluated_on" : "ISO Timestamp of DNS data collection",
    "rdap_evaluated_on" : "ISO Timestamp of WHOIS/RDAP data collection",
    "tls_evaluated_on" : "ISO Timestamp of TLS certificate information collection",
    "dns_had_no_ips" : "true if no IPs were found in DNS records"
  },
  "sourced_on" : "ISO Timestamp of the moment the domain was found",
  "tls" : {
    "cipher" : "Identifier of the TLS cipher suite",
    "count" : "Number of certificates in chain",
    "protocol" : "Version of the TLS protocol",
    "certificates" : [
      "//": "Information from TLS certificate fields: issuer, extensions, etc."
    ]
  },
  "category" : "Category of the record (could be ignored)",
  "source" : "Name of the file that we used to save the domain list"
}
]

Feature Vector

This section describes the veature vector used in the "Unmasking the Phishermen: Phishing Domain Detection with Machine Learning and Multi-Source Intelligence" paper that was accepted to the IEEE NOMS 2024 conference.

Lexical Features

The following features were extracted from the sole domain name:

• lex_name_len - length of the domain name,
• lex_begins_with_digit - true if the domain name begins with a digit,
• lex_www_flag - true if the domain name begins with "www.",
• lex_phishing_keyword_count - occurence count of 47 phishing-related keywords,
• lex_consecutive_chars - length of the longest consecutive character sequence,
• lex_tld_len - length of the top-level domain (TLD),
• lex_tld_hash - hash of the TLD,
• lex_sld_len - length of the second-level domain (SLD),
• lex_sld_norm_entropy - normalized entropy of the SLD,
• lex_stld_unique_char_count - number of unique characters in the TLD and the SLD,
• lex_sub_count - number of subdomains,
• lex_sub_digit_ratio - ratio of digits in subdomains,
• lex_sub_hex_ratio - ratio of hex symbols in subdomains,
• lex_sub_non_alpanum_ratio - ratio of non-alphanumeric symbols in subdomains,
• lex_sub_vowel_ratio - ratio of vowels in subdomains,
• lex_sub_consonant_ratio - ratio of consonants in subdomains,
• lex_sub_max_consonant_len - length of the longest consonant sequence in subdomains,
• lex_sub_norm_entropy - normalized entropy of a string made from all subdomains,
• lex_phishing_bigram_matches - occurrence count of the top 300 phishing domain bigrams,
• lex_phishing_trigram_matches - occurrence count of the top 2000 phishing domain trigrams,
• lex_phishing_tetragram_matches - occurrence count of the top 5000 phishing domain tetragrams,
• lex_phishing_pentagram_matches - occurrence count of the top 10000 phishing domain pentagrams.

DNS-based Features

The following features were extracted from DNS responses when querying about the domain:

• dns_A_count - number of A records for the domain,
• dns_AAAA_count - number of AAAA records for the domain,
• dns_CNAME_count - number of CNAME records for the domain,
• dns_MX_count - number of MX records for the domain,
• dns_NS_count - number of nameserver (NS) records for the domain,
• dns_TXT_count - number of TXT records for the domain,
• dns_soa_primary_ns_len - number of characters in the primary NS's domain name,
• dns_soa_primary_ns_level - number of subdomain in the primary NS's domain name,
• dns_soa_primary_ns_digit_count - number of digits in the primary NS's domain name,
• dns_soa_primary_ns_entropy - normalized entropy of the primary NS's domain name,
• dns_soa_email_len - number of characters in the admin's email domain name part,
• dns_soa_email_level - number of subdomains in the admin's email domain name part,
• dns_soa_email_digit_count - number of digits in the admin's email domain name part,
• dns_soa_email_entropy - normalized entropy of the admin's email domain name part,
• dns_soa_refresh - SOA refresh parameter,
• dns_soa_retry - SOA retry parameter,
• dns_soa_expire - SOA expire parameter,
• dns_mx_avg_len - average number of characters of the domain names in MX records,
• dns_mx_avg_entropy - average normalized entropy of the domain names in MX records,
• dns_domain_name_in_mx - true if the domain name is contained in the MX record's domains,
• dns_txt_spf_exists - true if an SPF record is in the TXT RRs,
• dns_txt_avg_entropy - average normalized entropy of the TXT records
• dns_ttl_low - number of RRsets with TTL in [0,100],
• dns_ttl_mid - number of RRsets with TTL in [101,500],
• dns_zone_entropy - normalized entropy of the zone's domain name.

IP-based Features

These features were derived from IP addresses and ICMP echo replies:

• ip_mean_average_rtt - average RTT of all ICMP echo attempts,
• ip_entropy - total entropy of all /16 (/64 for v6) IP prefixes,
• ip_count - total number of IP addresses for the domain,
• ip_v4_count - total number of IPv4 addresses for the domain,
• ip_v6_count - total number of IPv6 addresses for the domain,

TLS-based Features

The following features were extracted from TLS certificate chains and TLS handshakes:

• tls_chain_len - length of the TLS certificate chain,
• tls_broken_chain - true if there is a certificate that has never been valid,
• tls_expired_chain - true if there is an expired certificate in the chain,
• tls_total_extension_count - total extensions in all certificates in the chain,
• tls_critical_extensions - total extensions flagged as "critical" in all certificates,
• tls_with_policies_crt_count - number of certificates that include the "policies" extension,
• tls_percentage_crt_with_policies - percentage of certificates that include the "policies" extension,
• tls_x509_anypolicy_crt_count - number of certificates not enforcing any security policy,
• tls_iso_policy_crt_count - total discovered policies from the 1.* OID space,
• tls_joint_isoitu_policy_crt_count - total discovered policies from from the 2.* OID space,
• tls_subject_count - number of subject alternative names (SANs) in the leaf certificate,
• tls_server_auth_crt_count - number of certificates with the "Web Server Authentication",
• tls_client_auth_crt_count - number of certificates with the "Web Client Authentication",
• tls_CA_certs_in_chain_ratio - ratio of CA certificates in the chain,
• tls_unique_SLD_count -number of unique second-level domains