IP to Abuser Database

IP to Abuser Database Abuser Detection IP Abuse Prevention

The IP to Abuser Database is a database that contains IP addresses known for abusive behavior. The database is updated on a regular basis and is available for purchase in CSV or MMDB format.

Abusive IP addresses can be used for various malicious activities, including spam, hacking attempts, and DDoS attacks. The IP to Abuser Database is a valuable tool for businesses that want to detect and prevent abuse on their website or app and to take appropriate measures to protect their services.

IP to Abuser Database

Price 49$ per month
Filesize 103MB
Format CSV and MMDB
Total Abuser IPs 2,585,928
Total Blocklist Sources 159
Last Updated January 22, 2026
Download CSV Sample Sample (CSV)
Download MMDB Sample Sample (MMDB)

# Purchase Database

To purchase the database, you need to create a free account. Database subscriptions are billed monthly and can be canceled at any time. Learn more about the pricing and the terms. If you purchase the database, you will receive a download link to the database file for all formats.

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# Abuser Database Format

The file format of the IP to Abuser Database is either in CSV or MMDB format and contains the following fields:

  • ipVersion - Either 4 (IPv4) or 6 (IPv6), determining the IP type of the network.
  • startIp - The start IP address of the range in string format. Example: 45.86.210.31
  • endIp - The end IP address of the range in string format. Example: 45.86.210.31
  • isAbuser - A boolean value indicating whether the IP is known for abusive behavior. Example: true
  • sourceCount - The number of independent blocklist sources where this IP address was found. A higher number indicates the IP is more widely recognized as abusive. Example: 7 (meaning the IP was found on 7 different blocklists)
  • totalSources - The total number of active blocklist sources used by the database. This allows you to calculate the percentage of sources where an IP appears. Example: 159
Understanding sourceCount: The database is sorted by sourceCount in descending order. IPs with higher sourceCount values are found on more independent blocklists and are generally considered more reliably abusive. For example, an IP with sourceCount: 15 out of totalSources: 159 has been flagged by approximately 15 independent sources, making it a high-confidence abuser.

The following example contains a small excerpt of the entire database: 

startIp,endIp,ipVersion,isAbuser,sourceCount,totalSources
45.148.10.0,45.148.10.255,4,true,23,159
185.220.101.0,185.220.101.255,4,true,21,159
193.32.162.0,193.32.162.255,4,true,19,159
45.155.205.0,45.155.205.255,4,true,18,159
80.82.77.0,80.82.77.255,4,true,17,159
171.25.193.0,171.25.193.255,4,true,16,159
89.248.167.0,89.248.167.255,4,true,15,159
185.129.61.0,185.129.61.255,4,true,14,159
162.247.74.0,162.247.74.255,4,true,13,159
198.98.51.0,198.98.51.255,4,true,12,159
45.134.26.0,45.134.26.255,4,true,11,159
185.56.80.0,185.56.80.255,4,true,10,159
92.63.194.0,92.63.194.255,4,true,9,159
141.98.10.0,141.98.10.255,4,true,8,159
179.43.175.0,179.43.175.255,4,true,7,159
5.188.210.0,5.188.210.255,4,true,6,159
1.10.16.0,1.10.31.255,4,true,5,159
1.19.0.0,1.19.255.255,4,true,4,159

# How to use the IP to Abuser Database?

This example shows how to work with the IP to Abuser Database in MMDB format. First, you have to download the database sample:

curl -O https://ipapi.is/data/samples/Abuser-Database-Sample.mmdb

And then you can read the database with mmdbctl:

mmdbctl read -f json-pretty 2.57.121.25 Abuser-Database-Sample.mmdb

which outputs:

{
  "ipVersion": "4",
  "isAbuser": "true",
  "network": "2.57.121.25-2.57.121.25",
  "sourceCount": "25",
  "totalSources": "159"
}

# Why is Abuser Detection Important?

Abuser detection is the process of identifying IP addresses that are known for malicious or abusive behavior. It is crucial for maintaining the security and integrity of online services.

The IP to Abuser Database includes information about IP addresses known for abusive behavior. This helps in identifying and mitigating potential threats to your online services.

There are many good reasons why websites or apps want to detect abusive IP addresses:

  • Prevent spam and unwanted automated activities
  • Protect against DDoS attacks
  • Reduce the risk of fraud and malicious activities
  • Improve overall security of online services
  • Maintain the quality of user experience for legitimate users

# How does Abuser Detection Work?

Abuser detection involves various methods to identify IP addresses associated with malicious activities. These methods may include:

  • Historical Data Analysis: Examining past behavior and patterns associated with IP addresses.
  • Real-time Monitoring: Continuously tracking IP activities for suspicious behavior.
  • Machine Learning Algorithms: Using AI to predict and identify potentially abusive IP addresses based on various factors.
  • Collaborative Databases: Sharing information about known abusive IP addresses across multiple platforms and services.

By utilizing these methods, the IP to Abuser Database provides a comprehensive list of IP addresses that have been identified as potentially abusive, helping you protect your online services more effectively.