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     2015-05-24      293,716,320      589,634        11,604           217
Saturday   2015-05-23      329,257,245      680,372        11,992           215
Friday     2015-05-22      338,564,923      778,253        12,848           219
Thursday   2015-05-21      367,893,549      805,965        13,004           218
Wednesday  2015-05-20      362,595,517      814,285        12,990           220
Tuesday    2015-05-19      374,272,085      813,198        13,005           219
Monday     2015-05-18      394,980,527      812,677        12,943           220
Sunday     2015-05-17      307,399,373      599,802        11,666           218
Saturday   2015-05-16      313,017,431      675,077        12,005           216
Friday     2015-05-15      365,859,431      784,428        12,865           219
Thursday   2015-05-14      310,625,420      791,182        12,950           220
Wednesday  2015-05-13      364,249,412      810,484        12,999           220
Tuesday    2015-05-12      371,960,640      815,355        13,056           219
Monday     2015-05-11      372,438,354      804,325        12,709           219
Sunday     2015-05-10      278,096,009      592,517        11,647           216
Friday     2015-05-08      410,518,618      788,397        12,860           218
Thursday   2015-05-07      374,702,947      820,214        13,042           219
Wednesday  2015-05-06      373,253,380      819,488        13,079           220
Tuesday    2015-05-05      335,548,298      810,042        13,010           222
Monday     2015-05-04      350,558,345      794,872        12,698           220
Sunday     2015-05-03      332,431,468      592,359        11,619           219
Saturday   2015-05-02      325,772,308      653,932        11,843           217
Friday     2015-05-01      301,996,673      611,213        11,897           219
Thursday   2015-04-30      357,726,911      798,286        13,046           221
Wednesday  2015-04-29      397,812,161      822,326        13,121           221
Tuesday    2015-04-28      374,168,423      819,912        13,141           221
Monday     2015-04-27      397,985,922      827,829        13,136           220
Sunday     2015-04-26      286,115,783      614,082        11,796           219
Saturday   2015-04-25      319,883,076      701,448        12,160           219
Friday     2015-04-24      388,313,200      808,114        13,074           220

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     2015-05-24                                                          
Saturday   2015-05-23                                                          
Friday     2015-05-22                                                          
Thursday   2015-05-21                                                          
Wednesday  2015-05-20                                                          
Tuesday    2015-05-19                                                          
Monday     2015-05-18                                                          
Sunday     2015-05-17                                                          
Saturday   2015-05-16                                                          
Friday     2015-05-15                                                          
Thursday   2015-05-14                                                          
Wednesday  2015-05-13                                                          
Tuesday    2015-05-12                                                          
Monday     2015-05-11                                                          
Sunday     2015-05-10                                                          
Friday     2015-05-08                                                          
Thursday   2015-05-07                                                          
Wednesday  2015-05-06                                                          
Tuesday    2015-05-05                                                          
Monday     2015-05-04                                                          
Sunday     2015-05-03                                                          
Saturday   2015-05-02                                                          
Friday     2015-05-01                                                          
Thursday   2015-04-30                                                          
Wednesday  2015-04-29                                                          
Tuesday    2015-04-28                                                          
Monday     2015-04-27                                                          
Sunday     2015-04-26                                                          
Saturday   2015-04-25                                                          
Friday     2015-04-24                                                          

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     2015-05-24      293,716,320      589,634        11,604           217
Saturday   2015-05-23      329,257,245      680,372        11,992           215
Friday     2015-05-22      338,564,923      778,253        12,848           219
Thursday   2015-05-21      367,893,549      805,965        13,004           218
Wednesday  2015-05-20      362,595,517      814,285        12,990           220
Tuesday    2015-05-19      374,272,085      813,198        13,005           219
Monday     2015-05-18      394,980,527      812,677        12,943           220
Sunday     2015-05-17      307,399,373      599,802        11,666           218
Saturday   2015-05-16      313,017,431      675,077        12,005           216
Friday     2015-05-15      365,859,431      784,428        12,865           219
Thursday   2015-05-14      310,625,420      791,182        12,950           220
Wednesday  2015-05-13      364,249,412      810,484        12,999           220
Tuesday    2015-05-12      371,960,640      815,355        13,056           219
Monday     2015-05-11      372,438,354      804,325        12,709           219
Sunday     2015-05-10      278,096,009      592,517        11,647           216
Friday     2015-05-08      410,518,618      788,397        12,860           218
Thursday   2015-05-07      374,702,947      820,214        13,042           219
Wednesday  2015-05-06      373,253,380      819,488        13,079           220
Tuesday    2015-05-05      335,548,298      810,042        13,010           222
Monday     2015-05-04      350,558,345      794,872        12,698           220
Sunday     2015-05-03      332,431,468      592,359        11,619           219
Saturday   2015-05-02      325,772,308      653,932        11,843           217
Friday     2015-05-01      301,996,673      611,213        11,897           219
Thursday   2015-04-30      357,726,911      798,286        13,046           221
Wednesday  2015-04-29      397,812,161      822,326        13,121           221
Tuesday    2015-04-28      374,168,423      819,912        13,141           221
Monday     2015-04-27      397,985,922      827,829        13,136           220
Sunday     2015-04-26      286,115,783      614,082        11,796           219
Saturday   2015-04-25      319,883,076      701,448        12,160           219
Friday     2015-04-24      388,313,200      808,114        13,074           220

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