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AUTOMATED
MOBILE MALWARE
CLASSIFICATION
zynamics GmbH
Status Quo: Mobile Malware
   The deluge of mobile malware that was
    predicted has not happened yet
Status Quo: Mobile Malware
   This does not mean that mobile malware is not
    a threat

   More money moving through GSM means
    more incentive to build malware

   Result: There WERE and WILL be outbreaks
News Item
Problem: Variants
   A lot of filtering can be done using MD5
     But:   Fraudsters learned to obfuscate
   Variants are easy to create
   In the Windows world:
     20k
        MD5-different variants of the same malware
     each month
Problem: Variants
   Ways to determine whether a file is a variant of
    a known malware are needed. Preferrably:
     Fast

     Cheap

     Reliable

     Easily   adapted to future threats
Current approach
   Analysis is
     Notdone at all
     Done manually by a security expert

     Done in some ad-hoc automated fashion
Problem: Variants
   Manual approaches do not satisfy our
    requirements:
     Fast:                No
     Cheap:               No
     Reliable:            Depends on the guy
     Easily   adaptable   Depends on the guy
Program Comparison
   How would we check if a file is a variant ?
   Program comparison tools are needed
   Surprise: We have built some
     In use in the ITSec and AV world since 2004
     „Best Paper“ at SSTIC 2005

     Germany‘s biggest privately funded research
      prize 2006
       We   beat Siemens and T-Systems
Program Comparison
   Core principle: Comparison is structural
   Instructions may change a lot, the program
    structure only slightly
   Graphs are generated from the programs
   Comparison happens on these graphs
Status Quo: The Windows World
Competition
Program Comparison
   Our comparison is strong because ...
     The entire program is taken into consideration
     Recompiling does not fool us

     Stable parts are identified

     Large changes do not matter much
VxClass for Mobile Malware
   VxClass compares executables
   A library of known malware is kept
   New executables can be checked if they are
    similar to existing malware
   Easy to use, Reliable, Cheap
Case Study
   Unknown executable is received
   MD5 does not match anything
   Is it a variant of an existing piece of malware ?
Multi-User capability

   Web-based
   Log in via username/password or SSL
    certificates
   Automation: Interaction via XMLRPC
Multi-User capability

   Different users can upload samples
   Three levels of permissions:
     Public:      All users can download the sample
     Protected:   All users can see, but not download
                   the sample
     Private:     No other users can see the sample
Business Case
Basic scenario:

   Recognize new malware variants
   Limit risk of outbreak
   Low-cost
   Fast response time
Business Case
Advanced scenario (with shared samples):

   Neighborhood watch
     Who else has seen this before ?
     Where ?

     When ?

     Who should I talk to ?

   Improve communication
Pricing
Telco-Style: Base Fee + Volume
 Basic:

     200 € / month
     50 € per uploaded executable

   Medium:
     500 € / month
     10 uploads included, 30 € each afterwards

   Flat rate:
     999 € / month
     No volume fee*
Pricing
   Only available to GSMA members
   The basic and medium packages may be
    shared between business entities
Pricing
This includes

   Providing the server / service
   Backups
   Email support
Roadmap
We will watch and adapt to new threats

   Windows Mobile Executables
   Of current relevance: .pyc
   Widgets
   iPhone executables
   Android
Summary
   We provide strong methods that identify
    malware variants
   Cheap, Fast, Accurate
   Any questions ?

                    Contact us !
                info@zynamics.com

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Automated Mobile Malware Classification

  • 2. Status Quo: Mobile Malware  The deluge of mobile malware that was predicted has not happened yet
  • 3. Status Quo: Mobile Malware  This does not mean that mobile malware is not a threat  More money moving through GSM means more incentive to build malware  Result: There WERE and WILL be outbreaks
  • 5. Problem: Variants  A lot of filtering can be done using MD5  But: Fraudsters learned to obfuscate  Variants are easy to create  In the Windows world:  20k MD5-different variants of the same malware each month
  • 6. Problem: Variants  Ways to determine whether a file is a variant of a known malware are needed. Preferrably:  Fast  Cheap  Reliable  Easily adapted to future threats
  • 7. Current approach  Analysis is  Notdone at all  Done manually by a security expert  Done in some ad-hoc automated fashion
  • 8. Problem: Variants  Manual approaches do not satisfy our requirements:  Fast: No  Cheap: No  Reliable: Depends on the guy  Easily adaptable Depends on the guy
  • 9. Program Comparison  How would we check if a file is a variant ?  Program comparison tools are needed  Surprise: We have built some  In use in the ITSec and AV world since 2004  „Best Paper“ at SSTIC 2005  Germany‘s biggest privately funded research prize 2006  We beat Siemens and T-Systems
  • 10. Program Comparison  Core principle: Comparison is structural  Instructions may change a lot, the program structure only slightly  Graphs are generated from the programs  Comparison happens on these graphs
  • 11. Status Quo: The Windows World
  • 13. Program Comparison  Our comparison is strong because ...  The entire program is taken into consideration  Recompiling does not fool us  Stable parts are identified  Large changes do not matter much
  • 14. VxClass for Mobile Malware  VxClass compares executables  A library of known malware is kept  New executables can be checked if they are similar to existing malware  Easy to use, Reliable, Cheap
  • 15. Case Study  Unknown executable is received  MD5 does not match anything  Is it a variant of an existing piece of malware ?
  • 16.
  • 17.
  • 18.
  • 19.
  • 20.
  • 21.
  • 22. Multi-User capability  Web-based  Log in via username/password or SSL certificates  Automation: Interaction via XMLRPC
  • 23. Multi-User capability  Different users can upload samples  Three levels of permissions:  Public: All users can download the sample  Protected: All users can see, but not download the sample  Private: No other users can see the sample
  • 24. Business Case Basic scenario:  Recognize new malware variants  Limit risk of outbreak  Low-cost  Fast response time
  • 25. Business Case Advanced scenario (with shared samples):  Neighborhood watch  Who else has seen this before ?  Where ?  When ?  Who should I talk to ?  Improve communication
  • 26. Pricing Telco-Style: Base Fee + Volume  Basic:  200 € / month  50 € per uploaded executable  Medium:  500 € / month  10 uploads included, 30 € each afterwards  Flat rate:  999 € / month  No volume fee*
  • 27. Pricing  Only available to GSMA members  The basic and medium packages may be shared between business entities
  • 28. Pricing This includes  Providing the server / service  Backups  Email support
  • 29. Roadmap We will watch and adapt to new threats  Windows Mobile Executables  Of current relevance: .pyc  Widgets  iPhone executables  Android
  • 30. Summary  We provide strong methods that identify malware variants  Cheap, Fast, Accurate  Any questions ? Contact us ! info@zynamics.com