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Overview of

IP family
ipset hash
ipset entries
unique IPs
local copy
average update
fetch errors
monitoring since
last time
by its maintainers
last time
by us
last time
we checked


Evolution of

Each time the IP list is changed, modified, or updated we keep track of its size (both number of entries and number of unique IPs matched). Using this information we can detect what the list maintainers do, get an idea of the list trend and its maintainers habbits.

Using the chart below we attempt to answer these questions:

  • If you are going to use this IP list as a blocklist / blacklist at a firewall, its size can be important for the performance of the firewall.
    Keep in mind that the performance of Linux netfilter / iptables firewalls that use ipsets (like FireHOL does), is not affected by the size of an ipset. Any number of entries can be added and the firewall will just do one lookup for every packet checked against the ipset. Linux ipsets are affected only by the number of different subnets in an ipset. FireHOL solves this by automatically reducing the number of unique subnets on all hash:net ipsets (check this article for more information on how this is done).
  • The number of unique IPs matched by an IP list, determines the effectiveness of the blacklist / blocklist.
    Generally, smaller IP lists are more focused and safer to use as firewall blacklists / blocklists. Fewer unique IPs means fewer possible false positives.
    On the other hand a very small list will not provide a significant level of protection.
  • We need IP lists that are well maintained, frequently and regularly.
    In the chart below, every point is updated only when the list maintainers add IPs to, or remove IPs from the IP list, so even if the number of unique IPs remains the same, a point in the chart indicates that something changed in it. The exact number of unique IPs added and removed with each update can be seen on the chart next to the one below.
    The frequency of updates is irrelevant to the retention policy of the IP list. We will examine its retention below in the sections below.
  • We don't want surprises. Sudden increases or decreases is generally an indication of poor maintainance.
    Of course, there are cases where an IP list will by definition have sudden changes in its size.

The chart below shows the last 500 updates, of the IP list.

  • Entries is the number of entries the ipset has.
  • UniqueIPs is the number of unique IPs the ipset matches.

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The chart below shows the change history of the IP list, i.e. the number of unique IPs added and removed with each update.

Using the chart below we attempt to answer these questions:

  • There are IP lists that, although they have an almost constant size, they change their contents almost entirely on every update.
    In other cases, similar IP lists have minimal incremental updates.
    The following chart attempts to visualize this.

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Country Map of

Each time an ipset is updated we check it against the MaxMind GeoLite2 country, the IPDeny.com country and the IP2Location.com Lite country databases, to find the list's unique IPs per country.

Using the maps below we attempt to answer these questions:

  • If you are going to install this IP list as a blocklist / blacklist at a firewall, it is important to know which countries will be mainly affected, since you are going to block access from/to these IPs.

    All lists suffer from false positives to some degree, so using this IP list at your firewall might block some of your users or customers.

  • Some lists focus only on specific regions of the world. The following map illustrates this. It is a heat map of the list's focus.

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Age of IPs listed in

The age of each IP in the list is shown below. The time shown is calculated in realtime; it will be refreshed as time passes, even if the list is not updated.

Using the chart below we attempt to answer these questions:

  • Most lists include IPs that match some criteria (e.g. an attack or abuse is detected originated from the IP in question). Once an IP is listed, it remains listed for a pre-defined amount of time, unless it matches the criteria again, in which case its expiration time is refreshed.

    Many lists announce the duration they list IPs. Many don't and almost all lists have exceptions that do not follow the announced rules.

    A false positive is in place when an IP that was properly detected and added to the list, was released and re-used by another person, before being unlisted from the list. Since the world is full of dynamic IP users, false positives is the biggest problem of blocklist / blacklists.

    In the chart below we show the exact age of the IPs currently listed. Small ages are good. Long ages are not necessarily bad. Normally, longer ages should only be a small part of the list's size.

    Pay attention to the 50% mark. This is the average age of the IPs in the list. Pay also attention to the 75% (most probable) and the 90% (expected max) marks.

  • The ideal age chart of a well maintained IP list should a straight line from the bottom left corner, to the upper right corner of the chart.

    Of course, this is affected by the pressure of different attacks and possibly the different listing policies for different types of attacks.

    In general though, this chart should be as granural as possible.

    Long horizontal lines indicate either sustaining attacks, or unreasonably high listing policies.

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Retention Policy of

The retention policy of the list shows the duration IPs were listed, when they were listed. This is calculated every time the list maintainers remove an IP from the list. The chart below shows the retention policy detected, since we started monitoring the list (it is not limited to a certain timeframe).

Using the chart below we attempt to answer these questions:

  • This chart shows data for the past IPs, currently unlisted.
    The vertical parts of the "stair steps" in this chart, indicate periods of intensive IPs cleanup. This is their retention policy.
    If the chart contains more than one "stair steps", the list has many different retention policies.

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Overlaps of with other IP lists

Using the chart below we attempt to answer these questions:

  • Check the column Their %. A high percentage in this column, indicates that the IP list of that row is included in .

  • Check the column This %. A high percentage in this column, indicates that is included in the IP list of that row.

  • Focus on the last two columns: Their % and This %. These two percentages show the percentage of overlap this list has with other IP lists.

    Using the comparison table, we can easily find out that, for example, abuse is often initiated from anonymizing IPs (like open proxies) and malwares.

List Their % This %

Comments on

2015-2016 Costa Tsaousis, for FireHOL a firewall for humans!.
The data on this page are automatically generated using FireHOL's update-ipsets.sh (for downloading the lists from their sources and generating the data for this site), which utilizes iprange (for comparing and manipulating IP lists). Both are part of FireHOL, which is provided under GPL v2, so you are free to get, use, adapt and re-distribute.
This site is provided as-is, without any warranty. IP Lists are a property of their maintainers.
This site is a single static page, with all its data uploaded as static JSON and CSV files every time an IP List is updated. For the final result, it utilizes IP data and web services provided by third parties. It uses IP lists and related data provided and maintained by their respective owners (mentioned together with each IP list), IP-to-country geolocation data provided by maxmind.com (GeoLite2), ipdeny.com and ip2location.com (Lite), javascript chart libraries provided by highcharts.com, comments engine provided by disqus.com, social media sharing buttons provided by shareaholic.com, the HTML, CSS and JS framework bootstrap, the bootstrap-table component, icons provided by iconsdb.com and it uses several services provided by github.