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ANALYSIS	
  BRIEF	
  –	
  September	
  2012	
  
IS	
  YOUR	
  BROWSER	
  PUTTING	
  YOU	
  AT	
  RISK?	
  	
  
PART	
  2	
  –	
  CLICK	
  FRAUD	
  

	
  
Authors	
  -­‐	
  Francisco	
  Artes,	
  Stefan	
  Frei,	
  Ken	
  Baylor,	
  Jayendra	
  Pathak,	
  Bob	
  Walder	
  
	
  

Overview	
  
                                                                                                                                                                                                                                                                           1
The	
  US	
  online	
  advertising	
  market	
  in	
  2011	
  was	
  approximately	
  $155	
  billion	
  USD .	
  Fraudsters	
  utilize	
  click	
  fraud	
  to	
  
deflect	
  some	
  of	
  this	
  money	
  to	
  them	
  or	
  to	
  deplete	
  their	
  competitors	
  marketing	
  budgets.	
  In	
  the	
  process,	
  millions	
  of	
  
consumer	
  and	
  corporate	
  users	
  are	
  infected	
  by	
  malware	
  as	
  a	
  byproduct	
  of	
  this	
  war	
  between	
  ad	
  buyers,	
  ad	
  
publishers	
  and	
  fraudsters.	
  

Click	
  fraud	
  is	
  a	
  type	
  of	
  Internet	
  crime	
  that	
  abuses	
  pay-­‐per-­‐click	
  online	
  advertising	
  for	
  the	
  purpose	
  of	
  generating	
  a	
  
charge	
  per	
  click,	
  of	
  which	
  the	
  criminal	
  is	
  paid	
  a	
  percentage	
  of	
  the	
  ad	
  revenue.	
  	
  The	
  effects	
  of	
  click	
  fraud	
  can	
  be	
  
devastating	
  for	
  small	
  business	
  owners	
  and	
  very	
  costly	
  for	
  big	
  budget	
  ad	
  buyers.	
  	
  

For	
  individuals	
  and	
  enterprise	
  users,	
  the	
  effects	
  of	
  click	
  fraud	
  itself	
  are	
  malignant,	
  as	
  click	
  fraudsters	
  fund	
  many	
  
malware	
  campaigns.	
  These	
  campaigns	
  lead	
  to	
  multiple	
  malware	
  infections	
  such	
  as	
  banking	
  trojans	
  that	
  typically	
  
accompany	
  each	
  click	
  fraud	
  software	
  installation.	
  

	
  


NSS	
  Lab	
  Findings:	
  
                                •                               Click	
  fraud	
  itself,	
  causes	
  minimal	
  direct	
  harm	
  to	
  the	
  typical	
  end	
  user,	
  as	
  the	
  ultimate	
  target	
  is	
  the	
  ad	
  
                                                                buyer.	
  	
  	
  
                                •                               Consumer	
  and	
  corporate	
  users	
  are	
  infected	
  by	
  additional	
  malware	
  as	
  a	
  byproduct	
  of	
  click	
  fraud	
  
                                                                installation.	
  
                                •                               Click	
  fraud	
  catch	
  rates	
  are	
  Chrome	
  1.6%,	
  Firefox	
  0.8%,	
  Internet	
  Explorer	
  96.6%,	
  and	
  Safari	
  0.7%.	
  
                                •                               Services	
  are	
  available	
  that	
  may	
  help	
  ad	
  buyers	
  identify	
  click	
  fraud.	
  	
  However,	
  service	
  contracts	
  with	
  ad	
  
                                                                                                                                                                                                                          2
                                                                networks	
  may	
  contain	
  clauses	
  that	
  restrict	
  ad	
  buyers’	
  ability	
  to	
  recover	
  damages	
  for	
  click	
  fraud.	
   	
  
                                •                               The	
  average	
  lifespan	
  of	
  a	
  click	
  fraud	
  URL	
  was	
  32	
  hours	
  with	
  over	
  50%	
  expiring	
  within	
  54	
  hours.	
  	
  
                                                                	
  

	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  

1
       	
  http://www.marketingcharts.com/direct/internet-­‐advertising-­‐revenues-­‐continue-­‐growth-­‐20257/	
  
2
       	
  https://www.google.com/intl/en_us/adwords/select/TCUSbilling0806.html	
  Section	
  5.	
  
NSS	
  Labs	
                                                                 Analysis	
  Brief	
  –	
  Is	
  Your	
  Browser	
  Putting	
  You	
  At	
  Risk?	
  Pt	
  2	
  –	
  Click	
  Fraud	
  


	
  


NSS	
  Labs	
  Recommendations:	
  
Ad	
  buyers	
  should:	
  

       •       Put	
  pressure	
  on	
  Google	
  to	
  increase	
  the	
  click	
  fraud	
  protection	
  capabilities	
  of	
  Chrome	
  and	
  the	
  SafeBrowsing	
  
               API.	
  
       •       Consider	
  the	
  use	
  of	
  click	
  fraud	
  forensics	
  to	
  reduce	
  the	
  amount	
  of	
  click	
  fraud	
  damages.	
  
       •       Check	
  and	
  challenge	
  contract	
  clauses	
  that	
  may	
  limit	
  damages	
  or	
  restrict	
  ability	
  to	
  recover	
  damages.	
  
       •       Prepare	
  for	
  major	
  growth	
  of	
  click	
  fraud	
  in	
  2013.	
  	
  

	
  

Analysis	
  
Who	
  is	
  Affected	
  By	
  Click	
  Fraud?	
  
Primary	
  victims:	
  

Ad	
  buyers.	
  Ad	
  buyers	
  purchase	
  ads	
  from	
  ad	
  publishers	
  and	
  are	
  impacted	
  by	
  click	
  fraud	
  directly,	
  as	
  they	
  pay	
  for	
  the	
  
total	
  number	
  of	
  clicks	
  (valid	
  clicks	
  and	
  undetected	
  click	
  fraud).	
  	
  

Secondary	
  victims:	
  

Ad	
  Publishers:	
  The	
  existence	
  of	
  click	
  fraud	
  has	
  the	
  potential	
  to	
  damage	
  both	
  the	
  reputation	
  of	
  ad	
  publishers	
  and	
  
general	
  confidence	
  in	
  the	
  online	
  advertising	
  economy.	
  Most	
  attempt	
  to	
  identify	
  click	
  fraud	
  and	
  actively	
  reduce	
  it	
  
via	
  the	
  use	
  of	
  fraud	
  detection	
  engines,	
  thus	
  combating	
  negative	
  perceptions.	
  	
  

Consumers	
  and	
  Corporate	
  Users:	
  As	
  ad	
  publishers'	
  fraud	
  detection	
  engines	
  become	
  more	
  sophisticated,	
  fraudsters	
  
evolve	
  creative	
  methods	
  of	
  simulating	
  'undetectable	
  traffic'.	
  One	
  method	
  is	
  to	
  infect	
  millions	
  of	
  unsuspecting	
  
consumers	
  and	
  enterprise	
  users	
  with	
  click	
  fraud	
  malware,	
  which	
  will	
  convert	
  their	
  machines	
  into	
  bots.	
  As	
  these	
  
fraudsters	
  have	
  a	
  strong	
  cash	
  flow,	
  they	
  finance	
  many	
  pay-­‐per-­‐install	
  campaigns.	
  Unfortunately,	
  other	
  malware	
  is	
  
frequently	
  packaged	
  with	
  the	
  click	
  fraud	
  malware,	
  leaving	
  victims	
  open	
  to	
  intellectual	
  property	
  and	
  account	
  theft.	
  

Beneficiaries:	
  	
  	
  

Criminals:	
  	
  Authors	
  of	
  click	
  fraud	
  malware	
  may	
  benefit	
  through	
  direct	
  sales	
  of	
  exploits	
  or	
  via	
  ad	
  revenue	
  from	
  
fraudulent	
  clicks.	
  Organized	
  crime	
  syndicates	
  are	
  known	
  to	
  establish	
  websites	
  with	
  the	
  express	
  intent	
  of	
  
perpetrating	
  click	
  fraud.	
  One	
  common	
  method	
  is	
  to	
  infect	
  unsuspecting	
  consumers	
  and	
  enterprise	
  users	
  with	
  a	
  
combination	
  of	
  click	
  fraud	
  and	
  other	
  malware,	
  turning	
  their	
  machines	
  into	
  bot	
  networks	
  that	
  serve	
  as	
  launching	
  
pads	
  for	
  other	
  criminal	
  activities.	
  

Web	
  Site	
  Owners:	
  	
  Web	
  site	
  owners	
  may	
  perpetrate	
  click	
  fraud	
  as	
  they	
  get	
  paid	
  a	
  proportion	
  of	
  ad	
  revenue	
  when	
  
users	
  click	
  ads	
  that	
  are	
  displayed	
  on	
  their	
  site.	
  This	
  includes	
  organized	
  crime	
  syndicates	
  that	
  establish	
  websites	
  
with	
  the	
  express	
  intent	
  of	
  perpetrating	
  click	
  fraud.	
  Business	
  rivals	
  may	
  purposely	
  use	
  click	
  fraud	
  to	
  deplete	
  their	
  
competitors	
  marketing	
  budget.	
  	
  

Ad	
  Publishers:	
  Ad	
  publishers	
  passively	
  benefit	
  from	
  click	
  fraud,	
  as	
  they	
  earn	
  a	
  portion	
  of	
  revenue	
  every	
  time	
  one	
  of	
  
their	
  ads	
  is	
  clicked,	
  fraudulently	
  or	
  not.	
  They	
  also	
  benefit	
  as	
  click	
  fraud	
  artificially	
  inflates	
  click	
  rates,	
  reducing	
  
confidence	
  in	
  their	
  competitors	
  and	
  causing	
  ad	
  purchasers	
  to	
  defect	
  to	
  their	
  ad	
  network.	
  


©	
  2012	
  NSS	
  Labs,	
  Inc.	
  All	
  rights	
  reserved.	
                         	
                                                                                                           2	
     	
     	
  
NSS	
  Labs	
                                                                                                                                                                                                                                                                              Analysis	
  Brief	
  –	
  Is	
  Your	
  Browser	
  Putting	
  You	
  At	
  Risk?	
  Pt	
  2	
  –	
  Click	
  Fraud	
  


	
  

According	
  to	
  Adometry,	
  an	
  organization	
  specializing	
  in	
  click	
  forensics	
  and	
  click	
  fraud	
  detection,	
  “In	
  an	
  environment	
  
where	
  more	
  clicks	
  equals	
  more	
  money,	
  limiting	
  total	
  clicks	
  implicitly	
  means	
  ad	
  networks	
  reduce	
  revenue.”3	
  	
  

	
  

Test	
  Results	
  
The	
  average	
  lifespan	
  of	
  a	
  click	
  fraud	
  URL	
  was	
  32	
  hours	
  with	
  over	
  50%	
  expiring	
  within	
  54	
  hours.	
  	
  This	
  shows	
  us	
  that	
  
click	
  fraud	
  is	
  distributed	
  via	
  quick	
  strike	
  campaigns.	
  	
  Protection	
  technologies	
  must	
  respond	
  within	
  this	
  timeframe	
  in	
  
order	
  to	
  be	
  effective.	
  


                                                                                                                                                                                                                                                                    Decay	
  of	
  Malicious	
  URLs	
  Over	
  Time.	
  
                                                       100%
       Percent	
  URLs	
  Expired	
  /	
  ReTred	
  




                                                       80%

                                                                                                                                                                                                                                                                                                                                                                                     57%
                                                       60%


                                                       40%


                                                       20%


                                                        0%
                                                                           0                                                                                                          20                                                                                   40                      60                          80                         100                         120
                                                                                                                                                                                                                                                                                       LifeTme	
  in	
  Hours	
                                                                                   	
  
                                                                                                                                                                                                                                                                             Figure	
  1	
  -­‐	
  Cumulative	
  Distribution	
  

	
  

	
  

	
  

	
  

	
  

	
  

	
  

	
  

	
  

	
  



	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  
3
            http://www.adometry.com/blog/?p=682


©	
  2012	
  NSS	
  Labs,	
  Inc.	
  All	
  rights	
  reserved.	
                                                                                                                                                                                                                                       	
                                                                                                          3	
     	
     	
  
NSS	
  Labs	
                                                                               Analysis	
  Brief	
  –	
  Is	
  Your	
  Browser	
  Putting	
  You	
  At	
  Risk?	
  Pt	
  2	
  –	
  Click	
  Fraud	
  


	
  

Figure	
  2	
  -­‐	
  Block	
  Rate	
  Unique	
  Payload	
  (MD5),	
  highlights	
  the	
  browser	
  block	
  rates	
  by	
  class	
  of	
  malware	
  purpose.	
  
Internet	
  Explorer	
  exhibits	
  the	
  highest	
  block	
  rate,	
  followed	
  by	
  Google	
  Chrome,	
  and	
  then	
  either	
  Firefox	
  or	
  Safari.	
  	
  
However,	
  there	
  is	
  significant	
  difference	
  in	
  the	
  ability	
  of	
  each	
  browser	
  to	
  block	
  the	
  different	
  types	
  of	
  malware.	
  	
  This	
  
report	
  applies	
  to	
  click	
  fraud	
  only,	
  and	
  should	
  not	
  be	
  used	
  as	
  the	
  sole	
  basis	
  for	
  browser	
  selection.	
  

	
  

       Block Rate Unique Payload (MD5)                                           Firefox                       Chrome             Internet Explorer                           Safari


       ClickFraud                                                                0.8%                          1.6%               96.6%                                       0.7%


       Not ClickFraud                                                            6.3%                          25.9%              92.4%                                       6.6%

	
  


                                  0.7%
                  Safari
                                           6.6%

                                                                                                                                                                                    96.6%
  Internet Explorer
                                                                                                                                                                                 92.4%

                                   1.6%
              Chrome
                                                                          25.9%

                                  0.8%
                Firefox
                                          6.3%

                           0%            10%             20%              30%           40%            50%             60%             70%             80%             90%           100%
                                                                                                                                                                                                  	
  
                                                                      Figure	
  2	
  -­‐	
  Block	
  Rate	
  Unique	
  Payload	
  (MD5)	
  

	
  

While	
  it	
  is	
  apparent	
  from	
  these	
  results	
  that	
  click	
  fraud	
  is	
  a	
  leading	
  purpose	
  of	
  browser	
  malware,	
  it	
  is	
  surprising	
  and	
  
concerning	
  that	
  there	
  is	
  such	
  a	
  large	
  difference	
  between	
  blocked	
  rates	
  for	
  other	
  malware	
  types	
  vs.	
  click	
  fraud	
  from	
  
browser	
  to	
  browser.	
  	
  As	
  seen	
  in	
  Figure	
  2,	
  NSS	
  Labs	
  found	
  Chrome	
  blocked	
  only	
  1.6%	
  of	
  click	
  fraud	
  as	
  compared	
  to	
  
its	
  block	
  rate	
  of	
  other	
  malware	
  of	
  25.9%.	
  

	
  




©	
  2012	
  NSS	
  Labs,	
  Inc.	
  All	
  rights	
  reserved.	
                                       	
                                                                                                           4	
     	
     	
  
NSS	
  Labs	
                                                                                                                                                                                                                                                                                                                              Analysis	
  Brief	
  –	
  Is	
  Your	
  Browser	
  Putting	
  You	
  At	
  Risk?	
  Pt	
  2	
  –	
  Click	
  Fraud	
  


	
  


Impact	
  
            70%	
  
            60%	
  
                                                                                                                                                                                                                                                                                                                                                                                                                                                             Internet	
  Explorer	
  
            50%	
  
                                                                                                                                                                                                                                                                                                                                                                                                                                                             Firefox	
  
            40%	
  
            30%	
                                                                                                                                                                                                                                                                                                                                                                                                                                            Chrome	
  
            20%	
                                                                                                                                                                                                                                                                                                                                                                                                                                            Safari	
  
            10%	
  
                                                                                                                                                                                                                                                                                                                                                                                                                                                             Opera	
  
                     0%	
  
                                                         2009-­‐09	
  
                                                                                    2009-­‐11	
  
                                                                                                                2010-­‐01	
  


                                                                                                                                                                       2010-­‐05	
  
                                                                                                                                                                                                   2010-­‐07	
  
                                                                                                                                                                                                                              2010-­‐09	
  
                                                                                                                                                                                                                                                          2010-­‐11	
  
                                                                                                                                                                                                                                                                                  2011-­‐01	
  


                                                                                                                                                                                                                                                                                                                  2011-­‐05	
  
                                                                                                                                                                                                                                                                                                                                  2011-­‐07	
  
                                                                                                                                                                                                                                                                                                                                                  2011-­‐09	
  
                                                                                                                                                                                                                                                                                                                                                                  2011-­‐11	
  
                                                                                                                                                                                                                                                                                                                                                                                    2012-­‐01	
  


                                                                                                                                                                                                                                                                                                                                                                                                                    2012-­‐05	
  
                                                                                                                                                                                                                                                                                                                                                                                                                                    2012-­‐07	
  
                                                                                                                                            2010-­‐03	
  




                                                                                                                                                                                                                                                                                                  2011-­‐03	
  




                                                                                                                                                                                                                                                                                                                                                                                                    2012-­‐03	
  
                                                                                                                                                                                                                                                                                                                                                                                                                                                             Other	
  


                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              	
  
                                                                                                                                                                                                                                                                                                  Figure	
  3	
  -­‐	
  Market	
  Share	
  by	
  Browser	
  

                                                                                                                                                                                                                                                                                                                                                                                                                                                                4
Chrome’s	
  adoption	
  rate	
  has	
  established	
  it	
  as	
  the	
  leader	
  in	
  overall	
  browser	
  market	
  share	
   as	
  of	
  the	
  latter	
  half	
  of	
  
2012.	
  	
  Unless	
  Chrome	
  improves	
  its	
  protection	
  against	
  click	
  fraud,	
  NSS	
  predicts	
  an	
  increase	
  in	
  fraudulent	
  click	
  
transaction	
  rates	
  given	
  Chrome’s	
  dominant	
  and	
  increasing	
  market	
  share.	
  

                            35%	
  
                            30%	
  
                            25%	
  
                            20%	
                                                                                                                                                                                                                                                                                                                                                                                                                              Firefox	
  	
  

                            15%	
                                                                                                                                                                                                                                                                                                                                                                                                                              Safari	
  	
  
                            10%	
                                                                                                                                                                                                                                                                                                                                                                                                                              Chrome	
  	
  
                                      5%	
                                                                                                                                                                                                                                                                                                                                                                                                                     Internet	
  Explorer	
  	
  
                                      0%	
  
                                                                         2009-­‐09	
  
                                                                                                     2009-­‐11	
  
                                                                                                                                2010-­‐01	
  


                                                                                                                                                                                       2010-­‐05	
  
                                                                                                                                                                                                                  2010-­‐07	
  
                                                                                                                                                                                                                                              2010-­‐09	
  
                                                                                                                                                                                                                                                                           2010-­‐11	
  
                                                                                                                                                                                                                                                                                           2011-­‐01	
  


                                                                                                                                                                                                                                                                                                                           2011-­‐05	
  
                                                                                                                                                                                                                                                                                                                                           2011-­‐07	
  
                                                                                                                                                                                                                                                                                                                                                           2011-­‐09	
  
                                                                                                                                                                                                                                                                                                                                                                             2011-­‐11	
  
                                                                                                                                                                                                                                                                                                                                                                                             2012-­‐01	
  


                                                                                                                                                                                                                                                                                                                                                                                                                             2012-­‐05	
  
                                                                                                                                                                                                                                                                                                                                                                                                                                             2012-­‐07	
  
                                                                                                                                                           2010-­‐03	
  




                                                                                                                                                                                                                                                                                                           2011-­‐03	
  




                                                                                                                                                                                                                                                                                                                                                                                                             2012-­‐03	
  




	
  	
                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               	
  
                                                                                                                                                                                                                                                                                Figure	
  4	
  -­‐	
  Click	
  fraud	
  downloads	
  by	
  browser	
  

This	
  graph	
  represents	
  the	
  overlay	
  of	
  our	
  test	
  results	
  when	
  applied	
  to	
  the	
  change	
  in	
  market	
  share	
  of	
  each	
  of	
  the	
  
tested	
  browsers	
  since	
  2009.	
  	
  NSS	
  predicts	
  an	
  increase	
  in	
  fraudulent	
  click	
  transaction	
  rates	
  given	
  Chrome’s	
  
increasing	
  market	
  share.	
  

With	
  the	
  growth	
  of	
  online	
  advertising	
  revenues,	
  the	
  profitability	
  of	
  click	
  fraud,	
  and	
  the	
  weakness	
  of	
  leading	
  
browsers	
  to	
  protect	
  end-­‐users,	
  NSS	
  Labs	
  predicts	
  major	
  growth	
  in	
  click	
  fraud	
  in	
  2013.	
  


	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  
4
       	
  http://gs.statcounter.com	
  	
  


©	
  2012	
  NSS	
  Labs,	
  Inc.	
  All	
  rights	
  reserved.	
                                                                                                                                                                                                                                                                                                     	
                                                                                                                                    5	
     	
     	
  
NSS	
  Labs	
                                                                                Analysis	
  Brief	
  –	
  Is	
  Your	
  Browser	
  Putting	
  You	
  At	
  Risk?	
  Pt	
  2	
  –	
  Click	
  Fraud	
  


	
  


	
  
	
  


Contact	
  Information	
  
NSS	
  Labs,	
  Inc.	
  
6207	
  Bee	
  Caves	
  Road,	
  Suite	
  350	
  
Austin,	
  TX	
  78746	
  USA	
  
+1	
  (512)	
  961-­‐5300	
  
info@nsslabs.com	
  
www.nsslabs.com	
  	
  

	
  
This	
  analysis	
  brief	
  was	
  produced	
  as	
  part	
  of	
  NSS	
  Labs’	
  independent	
  testing	
  information	
  services.	
  Leading	
  products	
  
were	
  tested	
  at	
  no	
  cost	
  to	
  the	
  vendor,	
  and	
  NSS	
  Labs	
  received	
  no	
  vendor	
  funding	
  to	
  produce	
  this	
  analysis	
  brief.	
  

©	
  2012	
  NSS	
  Labs,	
  Inc.	
  All	
  rights	
  reserved.	
  No	
  part	
  of	
  this	
  publication	
  may	
  be	
  reproduced,	
  photocopied,	
  stored	
  on	
  a	
  retrieval	
  
                                                                                                      	
  
system,	
  or	
  transmitted	
  without	
  the	
  express	
  written	
  consent	
  of	
  the	
  authors.	
  	
  
	
  
Please	
  note	
  that	
  access	
  to	
  or	
  use	
  of	
  this	
  report	
  is	
  conditioned	
  on	
  the	
  following:	
  
	
  
1.	
  	
  The	
  information	
  in	
  this	
  report	
  is	
  subject	
  to	
  change	
  by	
  NSS	
  Labs	
  without	
  notice.	
  
	
  
2.	
  	
  The	
  information	
  in	
  this	
  report	
  is	
  believed	
  by	
  NSS	
  Labs	
  to	
  be	
  accurate	
  and	
  reliable	
  at	
  the	
  time	
  of	
  publication,	
  but	
  is	
  not	
  
guaranteed.	
  All	
  use	
  of	
  and	
  reliance	
  on	
  this	
  report	
  are	
  at	
  the	
  reader’s	
  sole	
  risk.	
  NSS	
  Labs	
  is	
  not	
  liable	
  or	
  responsible	
  for	
  any	
  
	
  
damages,	
  losses,	
  or	
  expenses	
  arising	
  from	
  any	
  error	
  or	
  omission	
  in	
  this	
  report.	
  

3.	
  	
  NO	
  WARRANTIES,	
  EXPRESS	
  OR	
  IMPLIED	
  ARE	
  GIVEN	
  BY	
  NSS	
  LABS.	
  ALL	
  IMPLIED	
  WARRANTIES,	
  INCLUDING	
  IMPLIED	
  
WARRANTIES	
  OF	
  MERCHANTABILITY,	
  FITNESS	
  FOR	
  A	
  PARTICULAR	
  PURPOSE,	
  AND	
  NON-­‐INFRINGEMENT	
  ARE	
  DISCLAIMED	
  AND	
  
EXCLUDED	
  BY	
  NSS	
  LABS.	
  IN	
  NO	
  EVENT	
  SHALL	
  NSS	
  LABS	
  BE	
  LIABLE	
  FOR	
  ANY	
  CONSEQUENTIAL,	
  INCIDENTAL	
  OR	
  INDIRECT	
  
DAMAGES,	
  OR	
  FOR	
  ANY	
  LOSS	
  OF	
  PROFIT,	
  REVENUE,	
  D ATA,	
  COMPUTER	
  PROGRAMS,	
  OR	
  OTHER	
  ASSETS,	
  EVEN	
  IF	
  ADVISED	
  OF	
  THE	
  
POSSIBILITY	
  THEREOF.	
  

4.	
  	
  This	
  report	
  does	
  not	
  constitute	
  an	
  endorsement,	
  recommendation,	
  or	
  guarantee	
  of	
  any	
  of	
  the	
  products	
  (hardware	
  or	
  
software)	
  tested	
  or	
  the	
  hardware	
  and	
  software	
  used	
  in	
  testing	
  the	
  products.	
  The	
  testing	
  does	
  not	
  guarantee	
  that	
  there	
  are	
  no	
  
errors	
  or	
  defects	
  in	
  the	
  products	
  or	
  that	
  the	
  products	
  will	
  meet	
  the	
  reader’s	
  expectations,	
  requirements,	
  needs,	
  or	
  
specifications,	
  or	
  that	
  they	
  will	
  operate	
  without	
  interruption.	
  	
  

5.	
  	
  This	
  report	
  does	
  not	
  imply	
  any	
  endorsement,	
  sponsorship,	
  affiliation,	
  or	
  verification	
  by	
  or	
  with	
  any	
  organizations	
  mentioned	
  
in	
  this	
  report.	
  	
  

6.	
  	
  All	
  trademarks,	
  service	
  marks,	
  and	
  trade	
  names	
  used	
  in	
  this	
  report	
  are	
  the	
  trademarks,	
  service	
  marks,	
  and	
  trade	
  names	
  of	
  
their	
  respective	
  owners.	
  	
  




©	
  2012	
  NSS	
  Labs,	
  Inc.	
  All	
  rights	
  reserved.	
                                         	
                                                                                                          6	
     	
     	
  

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  • 1.   ANALYSIS  BRIEF  –  September  2012   IS  YOUR  BROWSER  PUTTING  YOU  AT  RISK?     PART  2  –  CLICK  FRAUD     Authors  -­‐  Francisco  Artes,  Stefan  Frei,  Ken  Baylor,  Jayendra  Pathak,  Bob  Walder     Overview   1 The  US  online  advertising  market  in  2011  was  approximately  $155  billion  USD .  Fraudsters  utilize  click  fraud  to   deflect  some  of  this  money  to  them  or  to  deplete  their  competitors  marketing  budgets.  In  the  process,  millions  of   consumer  and  corporate  users  are  infected  by  malware  as  a  byproduct  of  this  war  between  ad  buyers,  ad   publishers  and  fraudsters.   Click  fraud  is  a  type  of  Internet  crime  that  abuses  pay-­‐per-­‐click  online  advertising  for  the  purpose  of  generating  a   charge  per  click,  of  which  the  criminal  is  paid  a  percentage  of  the  ad  revenue.    The  effects  of  click  fraud  can  be   devastating  for  small  business  owners  and  very  costly  for  big  budget  ad  buyers.     For  individuals  and  enterprise  users,  the  effects  of  click  fraud  itself  are  malignant,  as  click  fraudsters  fund  many   malware  campaigns.  These  campaigns  lead  to  multiple  malware  infections  such  as  banking  trojans  that  typically   accompany  each  click  fraud  software  installation.     NSS  Lab  Findings:   • Click  fraud  itself,  causes  minimal  direct  harm  to  the  typical  end  user,  as  the  ultimate  target  is  the  ad   buyer.       • Consumer  and  corporate  users  are  infected  by  additional  malware  as  a  byproduct  of  click  fraud   installation.   • Click  fraud  catch  rates  are  Chrome  1.6%,  Firefox  0.8%,  Internet  Explorer  96.6%,  and  Safari  0.7%.   • Services  are  available  that  may  help  ad  buyers  identify  click  fraud.    However,  service  contracts  with  ad   2 networks  may  contain  clauses  that  restrict  ad  buyers’  ability  to  recover  damages  for  click  fraud.     • The  average  lifespan  of  a  click  fraud  URL  was  32  hours  with  over  50%  expiring  within  54  hours.                                                                                                                                           1  http://www.marketingcharts.com/direct/internet-­‐advertising-­‐revenues-­‐continue-­‐growth-­‐20257/   2  https://www.google.com/intl/en_us/adwords/select/TCUSbilling0806.html  Section  5.  
  • 2. NSS  Labs   Analysis  Brief  –  Is  Your  Browser  Putting  You  At  Risk?  Pt  2  –  Click  Fraud     NSS  Labs  Recommendations:   Ad  buyers  should:   • Put  pressure  on  Google  to  increase  the  click  fraud  protection  capabilities  of  Chrome  and  the  SafeBrowsing   API.   • Consider  the  use  of  click  fraud  forensics  to  reduce  the  amount  of  click  fraud  damages.   • Check  and  challenge  contract  clauses  that  may  limit  damages  or  restrict  ability  to  recover  damages.   • Prepare  for  major  growth  of  click  fraud  in  2013.       Analysis   Who  is  Affected  By  Click  Fraud?   Primary  victims:   Ad  buyers.  Ad  buyers  purchase  ads  from  ad  publishers  and  are  impacted  by  click  fraud  directly,  as  they  pay  for  the   total  number  of  clicks  (valid  clicks  and  undetected  click  fraud).     Secondary  victims:   Ad  Publishers:  The  existence  of  click  fraud  has  the  potential  to  damage  both  the  reputation  of  ad  publishers  and   general  confidence  in  the  online  advertising  economy.  Most  attempt  to  identify  click  fraud  and  actively  reduce  it   via  the  use  of  fraud  detection  engines,  thus  combating  negative  perceptions.     Consumers  and  Corporate  Users:  As  ad  publishers'  fraud  detection  engines  become  more  sophisticated,  fraudsters   evolve  creative  methods  of  simulating  'undetectable  traffic'.  One  method  is  to  infect  millions  of  unsuspecting   consumers  and  enterprise  users  with  click  fraud  malware,  which  will  convert  their  machines  into  bots.  As  these   fraudsters  have  a  strong  cash  flow,  they  finance  many  pay-­‐per-­‐install  campaigns.  Unfortunately,  other  malware  is   frequently  packaged  with  the  click  fraud  malware,  leaving  victims  open  to  intellectual  property  and  account  theft.   Beneficiaries:       Criminals:    Authors  of  click  fraud  malware  may  benefit  through  direct  sales  of  exploits  or  via  ad  revenue  from   fraudulent  clicks.  Organized  crime  syndicates  are  known  to  establish  websites  with  the  express  intent  of   perpetrating  click  fraud.  One  common  method  is  to  infect  unsuspecting  consumers  and  enterprise  users  with  a   combination  of  click  fraud  and  other  malware,  turning  their  machines  into  bot  networks  that  serve  as  launching   pads  for  other  criminal  activities.   Web  Site  Owners:    Web  site  owners  may  perpetrate  click  fraud  as  they  get  paid  a  proportion  of  ad  revenue  when   users  click  ads  that  are  displayed  on  their  site.  This  includes  organized  crime  syndicates  that  establish  websites   with  the  express  intent  of  perpetrating  click  fraud.  Business  rivals  may  purposely  use  click  fraud  to  deplete  their   competitors  marketing  budget.     Ad  Publishers:  Ad  publishers  passively  benefit  from  click  fraud,  as  they  earn  a  portion  of  revenue  every  time  one  of   their  ads  is  clicked,  fraudulently  or  not.  They  also  benefit  as  click  fraud  artificially  inflates  click  rates,  reducing   confidence  in  their  competitors  and  causing  ad  purchasers  to  defect  to  their  ad  network.   ©  2012  NSS  Labs,  Inc.  All  rights  reserved.     2      
  • 3. NSS  Labs   Analysis  Brief  –  Is  Your  Browser  Putting  You  At  Risk?  Pt  2  –  Click  Fraud     According  to  Adometry,  an  organization  specializing  in  click  forensics  and  click  fraud  detection,  “In  an  environment   where  more  clicks  equals  more  money,  limiting  total  clicks  implicitly  means  ad  networks  reduce  revenue.”3       Test  Results   The  average  lifespan  of  a  click  fraud  URL  was  32  hours  with  over  50%  expiring  within  54  hours.    This  shows  us  that   click  fraud  is  distributed  via  quick  strike  campaigns.    Protection  technologies  must  respond  within  this  timeframe  in   order  to  be  effective.   Decay  of  Malicious  URLs  Over  Time.   100% Percent  URLs  Expired  /  ReTred   80% 57% 60% 40% 20% 0% 0 20 40 60 80 100 120 LifeTme  in  Hours     Figure  1  -­‐  Cumulative  Distribution                                                                                                                                                           3 http://www.adometry.com/blog/?p=682 ©  2012  NSS  Labs,  Inc.  All  rights  reserved.     3      
  • 4. NSS  Labs   Analysis  Brief  –  Is  Your  Browser  Putting  You  At  Risk?  Pt  2  –  Click  Fraud     Figure  2  -­‐  Block  Rate  Unique  Payload  (MD5),  highlights  the  browser  block  rates  by  class  of  malware  purpose.   Internet  Explorer  exhibits  the  highest  block  rate,  followed  by  Google  Chrome,  and  then  either  Firefox  or  Safari.     However,  there  is  significant  difference  in  the  ability  of  each  browser  to  block  the  different  types  of  malware.    This   report  applies  to  click  fraud  only,  and  should  not  be  used  as  the  sole  basis  for  browser  selection.     Block Rate Unique Payload (MD5) Firefox Chrome Internet Explorer Safari ClickFraud 0.8% 1.6% 96.6% 0.7% Not ClickFraud 6.3% 25.9% 92.4% 6.6%   0.7% Safari 6.6% 96.6% Internet Explorer 92.4% 1.6% Chrome 25.9% 0.8% Firefox 6.3% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%   Figure  2  -­‐  Block  Rate  Unique  Payload  (MD5)     While  it  is  apparent  from  these  results  that  click  fraud  is  a  leading  purpose  of  browser  malware,  it  is  surprising  and   concerning  that  there  is  such  a  large  difference  between  blocked  rates  for  other  malware  types  vs.  click  fraud  from   browser  to  browser.    As  seen  in  Figure  2,  NSS  Labs  found  Chrome  blocked  only  1.6%  of  click  fraud  as  compared  to   its  block  rate  of  other  malware  of  25.9%.     ©  2012  NSS  Labs,  Inc.  All  rights  reserved.     4      
  • 5. NSS  Labs   Analysis  Brief  –  Is  Your  Browser  Putting  You  At  Risk?  Pt  2  –  Click  Fraud     Impact   70%   60%   Internet  Explorer   50%   Firefox   40%   30%   Chrome   20%   Safari   10%   Opera   0%   2009-­‐09   2009-­‐11   2010-­‐01   2010-­‐05   2010-­‐07   2010-­‐09   2010-­‐11   2011-­‐01   2011-­‐05   2011-­‐07   2011-­‐09   2011-­‐11   2012-­‐01   2012-­‐05   2012-­‐07   2010-­‐03   2011-­‐03   2012-­‐03   Other     Figure  3  -­‐  Market  Share  by  Browser   4 Chrome’s  adoption  rate  has  established  it  as  the  leader  in  overall  browser  market  share   as  of  the  latter  half  of   2012.    Unless  Chrome  improves  its  protection  against  click  fraud,  NSS  predicts  an  increase  in  fraudulent  click   transaction  rates  given  Chrome’s  dominant  and  increasing  market  share.   35%   30%   25%   20%   Firefox     15%   Safari     10%   Chrome     5%   Internet  Explorer     0%   2009-­‐09   2009-­‐11   2010-­‐01   2010-­‐05   2010-­‐07   2010-­‐09   2010-­‐11   2011-­‐01   2011-­‐05   2011-­‐07   2011-­‐09   2011-­‐11   2012-­‐01   2012-­‐05   2012-­‐07   2010-­‐03   2011-­‐03   2012-­‐03         Figure  4  -­‐  Click  fraud  downloads  by  browser   This  graph  represents  the  overlay  of  our  test  results  when  applied  to  the  change  in  market  share  of  each  of  the   tested  browsers  since  2009.    NSS  predicts  an  increase  in  fraudulent  click  transaction  rates  given  Chrome’s   increasing  market  share.   With  the  growth  of  online  advertising  revenues,  the  profitability  of  click  fraud,  and  the  weakness  of  leading   browsers  to  protect  end-­‐users,  NSS  Labs  predicts  major  growth  in  click  fraud  in  2013.                                                                                                                                       4  http://gs.statcounter.com     ©  2012  NSS  Labs,  Inc.  All  rights  reserved.     5      
  • 6. NSS  Labs   Analysis  Brief  –  Is  Your  Browser  Putting  You  At  Risk?  Pt  2  –  Click  Fraud         Contact  Information   NSS  Labs,  Inc.   6207  Bee  Caves  Road,  Suite  350   Austin,  TX  78746  USA   +1  (512)  961-­‐5300   info@nsslabs.com   www.nsslabs.com       This  analysis  brief  was  produced  as  part  of  NSS  Labs’  independent  testing  information  services.  Leading  products   were  tested  at  no  cost  to  the  vendor,  and  NSS  Labs  received  no  vendor  funding  to  produce  this  analysis  brief.   ©  2012  NSS  Labs,  Inc.  All  rights  reserved.  No  part  of  this  publication  may  be  reproduced,  photocopied,  stored  on  a  retrieval     system,  or  transmitted  without  the  express  written  consent  of  the  authors.       Please  note  that  access  to  or  use  of  this  report  is  conditioned  on  the  following:     1.    The  information  in  this  report  is  subject  to  change  by  NSS  Labs  without  notice.     2.    The  information  in  this  report  is  believed  by  NSS  Labs  to  be  accurate  and  reliable  at  the  time  of  publication,  but  is  not   guaranteed.  All  use  of  and  reliance  on  this  report  are  at  the  reader’s  sole  risk.  NSS  Labs  is  not  liable  or  responsible  for  any     damages,  losses,  or  expenses  arising  from  any  error  or  omission  in  this  report.   3.    NO  WARRANTIES,  EXPRESS  OR  IMPLIED  ARE  GIVEN  BY  NSS  LABS.  ALL  IMPLIED  WARRANTIES,  INCLUDING  IMPLIED   WARRANTIES  OF  MERCHANTABILITY,  FITNESS  FOR  A  PARTICULAR  PURPOSE,  AND  NON-­‐INFRINGEMENT  ARE  DISCLAIMED  AND   EXCLUDED  BY  NSS  LABS.  IN  NO  EVENT  SHALL  NSS  LABS  BE  LIABLE  FOR  ANY  CONSEQUENTIAL,  INCIDENTAL  OR  INDIRECT   DAMAGES,  OR  FOR  ANY  LOSS  OF  PROFIT,  REVENUE,  D ATA,  COMPUTER  PROGRAMS,  OR  OTHER  ASSETS,  EVEN  IF  ADVISED  OF  THE   POSSIBILITY  THEREOF.   4.    This  report  does  not  constitute  an  endorsement,  recommendation,  or  guarantee  of  any  of  the  products  (hardware  or   software)  tested  or  the  hardware  and  software  used  in  testing  the  products.  The  testing  does  not  guarantee  that  there  are  no   errors  or  defects  in  the  products  or  that  the  products  will  meet  the  reader’s  expectations,  requirements,  needs,  or   specifications,  or  that  they  will  operate  without  interruption.     5.    This  report  does  not  imply  any  endorsement,  sponsorship,  affiliation,  or  verification  by  or  with  any  organizations  mentioned   in  this  report.     6.    All  trademarks,  service  marks,  and  trade  names  used  in  this  report  are  the  trademarks,  service  marks,  and  trade  names  of   their  respective  owners.     ©  2012  NSS  Labs,  Inc.  All  rights  reserved.     6