Introduction

As security professionals we always are asked how large is the population of an infection. Conficker is no different from any other, and it seems that everyone wants to have some value to use for many different purposes. The press for impact, some vendors for FUD, and others to have a number to compare to other infections. The bottom line is that no one can give an exact number on any infection ever. If anyone ever states exact numbers, they either are controlling it, or are not being completely honest to themselves or others on the means of data collection. We can estimate a number based off of certain traffic types, but we make mistakes as often as anyone else. A lot of the malicious traffic can resemble other legitimate or malicious traffic which of course skews the numbers. On top of simple traffic analysis each threat provides its own unique mechanisms for tracking infection statistics. Each of these methods of course come with their own positives and negatives when discussing accuracy of the data. It is what that in mind that we wanted attempt to draw out some of the pro's and con's of our data collection methodology below.

So, it is with a lot of trepidation that we even show any values for conficker knowing that they will most likely be taken out of context and quoted by many.

Population Numbers

What the following tables show are the daily connections and unique IP's that have been connecting to our tracking systems. Many people equate one IP to one system, but that is not usually the case. If the system is behind a NAT gateway, it would represent dozens or hundreds of systems. If a system is mobile it could be reported several times in a single day under different IP's. And in today's world there are a very large number of mobile users which could inflate the number of connections and unique IP's that are tracked.

What does this really mean? The daily numbers should represent the potential maximum level of the infection, but in previous test cases usually prove to be much less than that maximum. So, take the range of 25% to 75% of the values that we display as the possible infection population and you will be close to the real value. And yes, this is a very large range, and you can see why we do not like to quote any numbers for infection populations, and why you will see very high and low numbers get quoted regularly depending on the purpose of the person making the quote.

One last note: we are publishing these numbers to give a better understanding of what we are tracking. We do not believe in shaming anyone related to these values, and is not our purpose in any way.

Data Details

These tables are updated daily from the tracking systems. They are updated only once a day.

Conficker A+B

These tables are specifically for the A+B infections.

Day        Date        Total HTTP Hits  Unique IP's  Unique ASN's  Unique GEO's
Sunday     2015-01-25      152,395,526      644,784        11,951           222
Saturday   2015-01-24      185,085,875      738,568        12,410           222
Friday     2015-01-23      209,567,326      841,277        13,180           222
Thursday   2015-01-22      232,516,518      860,490        13,278           222
Wednesday  2015-01-21      201,599,289      852,463        13,227           222
Tuesday    2015-01-20      188,003,606      857,190        13,267           222
Monday     2015-01-19      182,623,856      878,391        13,302           222
Sunday     2015-01-18      169,098,046      644,318        12,027           222
Saturday   2015-01-17      127,700,112      665,682        12,090           220
Friday     2015-01-16      346,306,749      833,380        13,230           222
Thursday   2015-01-15      394,788,772      869,112        13,342           222
Wednesday  2015-01-14      410,875,711      866,221        13,327           223
Tuesday    2015-01-13      448,480,935      890,845        13,389           223
Monday     2015-01-12       74,940,523      373,469        11,263           220
Sunday     2015-01-11              580           92            50            19
Saturday   2015-01-10              533          127            54            18
Friday     2015-01-09              566          141            53            24
Thursday   2015-01-08              587          156            53            24
Wednesday  2015-01-07              462          130            48            22
Tuesday    2015-01-06              654          124            62            25
Monday     2015-01-05              565          149            60            28
Sunday     2015-01-04              538          137            50            20
Saturday   2015-01-03              510          132            42            23
Friday     2015-01-02              457           88            35            18
Thursday   2015-01-01              457          105            37            17
Wednesday  2014-12-31              391           95            39            20
Monday     2014-12-29              331           93            46            23
Saturday   2014-12-27              190           48            24            12
Friday     2014-12-26              271           71            32            17
Thursday   2014-12-25              306           92            31            16

This chart shows the rate of IP's being seen over time.

90-Day

180-Day

Year

Conficker C

These tables are specifically for the C infections

Day        Date        Total HTTP Hits  Unique IP's  Unique ASN's  Unique GEO's
Sunday     2015-01-25                                                          
Saturday   2015-01-24                                                          
Friday     2015-01-23                                                          
Thursday   2015-01-22                                                          
Wednesday  2015-01-21                                                          
Tuesday    2015-01-20                                                          
Monday     2015-01-19                                                          
Sunday     2015-01-18                                                          
Saturday   2015-01-17                                                          
Friday     2015-01-16                                                          
Thursday   2015-01-15                                                          
Wednesday  2015-01-14                                                          
Tuesday    2015-01-13                                                          
Monday     2015-01-12                                                          
Sunday     2015-01-11                                                          
Saturday   2015-01-10                                                          
Friday     2015-01-09                                                          
Thursday   2015-01-08                                                          
Wednesday  2015-01-07                                                          
Tuesday    2015-01-06                                                          
Monday     2015-01-05                                                          
Sunday     2015-01-04                                                          
Saturday   2015-01-03                                                          
Friday     2015-01-02                                                          
Thursday   2015-01-01                                                          
Wednesday  2014-12-31                                                          
Monday     2014-12-29                                                          
Saturday   2014-12-27                                                          
Friday     2014-12-26                                                          
Thursday   2014-12-25                                                          

This chart shows the rate of IP's being seen over time. Because of the great difference between the daily totals and the hourly, we are using two Y-Axis values. The Y-Axis on the left is for the daily totals, while the one on the right s for both the hourly lines.

90-Day

180-Day

Year

Conficker A+B+C

This data set is the aggregate of all the conficker infections for today.

Day        Date        Total HTTP Hits  Unique IP's  Unique ASN's  Unique GEO's
Sunday     2015-01-25      152,395,526      644,784        11,951           222
Saturday   2015-01-24      185,085,875      738,568        12,410           222
Friday     2015-01-23      209,567,326      841,277        13,180           222
Thursday   2015-01-22      232,516,518      860,490        13,278           222
Wednesday  2015-01-21      201,599,289      852,463        13,227           222
Tuesday    2015-01-20      188,003,606      857,190        13,267           222
Monday     2015-01-19      182,623,856      878,391        13,302           222
Sunday     2015-01-18      169,098,046      644,318        12,027           222
Saturday   2015-01-17      127,700,112      665,682        12,090           220
Friday     2015-01-16      346,306,749      833,380        13,230           222
Thursday   2015-01-15      394,788,772      869,112        13,342           222
Wednesday  2015-01-14      410,875,711      866,221        13,327           223
Tuesday    2015-01-13      448,480,935      890,845        13,389           223
Monday     2015-01-12       74,940,523      373,469        11,263           220
Sunday     2015-01-11              580           92            50            19
Saturday   2015-01-10              533          127            54            18
Friday     2015-01-09              566          141            53            24
Thursday   2015-01-08              587          156            53            24
Wednesday  2015-01-07              462          130            48            22
Tuesday    2015-01-06              654          124            62            25
Monday     2015-01-05              565          149            60            28
Sunday     2015-01-04              538          137            50            20
Saturday   2015-01-03              510          132            42            23
Friday     2015-01-02              457           88            35            18
Thursday   2015-01-01              457          105            37            17
Wednesday  2014-12-31              391           95            39            20
Monday     2014-12-29              331           93            46            23
Saturday   2014-12-27              190           48            24            12
Friday     2014-12-26              271           71            32            17
Thursday   2014-12-25              306           92            31            16

90-Day

180-Day

Year

ASN Statistics

These charts represent how many ASN's are effected during the period of the graph.

90-Day

180-Day

Year

Country Statistics

These charts represent how many countries are effected during the period of the graph.

90-Day

180-Day

Year

HTTP Hit Statistics

These charts show how many daily hits from Conficker systems that we are seeing during the period of the graphs. While this is not really representative of an infection population, it does show the level of work that the Conficker Working Group must do daily in dealing with the level of events from Conficker.

90-Day

180-Day

Year