Notes:

  • Population and Internet population numbers are generally as of 2014, and are sourced directly from the World Bank public access repositories. See, for example: Population Figures for more information.
  • The Regional Internet Registries (RIR) uses two letter codes for countries. These codes almost always agree with ISO3166-1-Alpha-2 (ISO 2 letter codes). However, RIR databases also contain some country codes that are not in ISO3166-1-Alpha-2 because they are obsolete (eg: SU), are sporadically used regional designations (eg: EU), alternates (eg: 'UK' versus 'GB') or are simply errors.
  • The country codes used (ISO3011-1-Alpha-2 for allocation-to-country mapping, ISO3166-1-Alpha-3 for population-to-country mapping) and for official country names are from ISO, obtained from here. Some minor stylistic changes have been made to a few country names to better align with more commonly recognized forms.
  • The per-capita numbers are calculated with the total internet population per-country. (The World Bank supplies the "internet population" as a percentage of the population)
  • The network sizes are calculated totalling up the sizes of network allocations assigned to each country as per RIR information .
  • The first grouping "By Infections" is the total number of infections in the corresponding country, and its percentage of the total number of infections the CBL knows about.
  • "By Spam Volume" is the total amount of spam we've observed coming from the corresponding country, and its percentage of the total. Please note that the very high volume associated with the United States is because of a very small number of a particular infection that "thinks" our spam sensors are their outbound SMTP relays. As such, instead of receiving a fraction of the spambot's spam, we receive all of it.
  • "By Network Infected", this is the percentage of the IP address netblocks assigned to the country that are infected. For example, 8% means that 8% of all IP addresses allocated to the country are infected with something we can detect.
  • "Per-Capita Infections" is the percentage of the population who have Internet access that are infected. As an example, a "12%" means that 12% of the Internet-connected population of that country has an infection that we can detect.
  • "Spam Per Capita" is the amount of spam we see from the country expressed in terms of the Internet-connected poopulation. for example, a "3" means that we've seen 3 spams for every Internet-connected user in the corresponding country. Note that the US figures are inflated for the same reason the "Spam Volume" figure is.
  • We now publish CSV format files that contain the basic infection/traffic numbers for all countries (including population), ASNs and domains.

    The top 20 worst countries (Prepared: 2019-02-17)
    Rank By Infections By Spam Volume By Network Infected Per-Capita Infections Spam Per-Capita
      Country Infections %of CBL Country %of traffic Country Rate Country Rate Country /capita
    1India300513920.1%Russian Federation19.5%Togo38%State of Palestine3.61%Estonia3.04
    2China190636012.7%United Kingdom of Great Britain and Northern Ireland12%Yemen27%Mongolia2.62%Ireland1.28
    3Iran (Islamic Republic of)10645237.12%China8.32%Anguilla26%Syrian Arab Republic2.38%Antigua and Barbuda0.672
    4Vietnam7849905.25%United States of America7.28%Guernsey19%Tunisia2.35%Cayman Islands0.567
    5Brazil7244764.84%Brazil6.05%Mayotte18%The former Yugoslav Republic of Macedonia2.31%Belize0.535
    6Thailand7214064.82%Vietnam3.29%Laos16%Iran (Islamic Republic of)2.17%Seychelles0.467
    7Indonesia4631203.1%South Africa2.96%Syrian Arab Republic12%Algeria2.04%Russian Federation0.463
    8Pakistan4019952.69%Canada2.91%Tajikistan10%Thailand1.98%Maldives0.349
    9Russian Federation3815042.55%Ireland1.99%Bhutan8.2%Libya1.89%Grenada0.302
    10Algeria3613132.42%France1.85%Myanmar8.2%Mauritius1.78%Saint Lucia0.297
    11Egypt3398712.27%India1.6%Iraq8%Vietnam1.77%Saint Vincent and the Grenadines0.294
    12Turkey3088882.06%Poland1.56%Mauritania7.9%Venezuela (Bolivarian Republic of)1.49%Montenegro0.294
    13Venezuela (Bolivarian Republic of)2859821.91%Indonesia1.4%State of Palestine6.6%Maldives1.47%Lithuania0.276
    14Mexico2657141.78%Argentina1.37%India5.7%Pakistan1.32%Barbados0.272
    15Philippines1811091.21%Estonia1.35%Albania5.5%Albania1.29%The former Yugoslav Republic of Macedonia0.259
    16Morocco1620411.08%South Korea1.32%Mongolia5.1%Antigua and Barbuda1.26%South Africa0.252
    17Tunisia1502441%Ukraine1.24%Venezuela (Bolivarian Republic of)5%Bosnia and Herzegovina1.22%Serbia0.251
    18Syrian Arab Republic1384190.925%Spain1.09%Comoros4.9%Seychelles1.15%Albania0.251
    19United States of America1367710.914%Iran (Islamic Republic of)1.04%Cambodia4.8%Uruguay1.14%Bulgaria0.249
    20Italy1159790.775%Italy1.01%Niger4.5%Aruba0.942%Canada0.227