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Exploiting Open Functionality in SMS-Capable Cellular Networks

Exploiting Open Functionality in SMS-Capable Cellular Networks. Authors: William Enck, Patrick Traynor, Patrick McDaniel, and Thomas La Porta Publication: 12th ACM conference on Computer and communications security, November 2005 Presenter: Brad Mundt for CAP6133 Spring ‘08. Motivation.

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Exploiting Open Functionality in SMS-Capable Cellular Networks

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  1. Exploiting Open Functionality in SMS-Capable Cellular Networks Authors: William Enck, Patrick Traynor, Patrick McDaniel, and Thomas La Porta Publication:12th ACM conference on Computer and communications security, November 2005 Presenter: Brad Mundt for CAP6133 Spring ‘08

  2. Motivation • SMS • Ingrained into modern culture • 69 million messages per day in UK • 10 cents per message • Popular with telecom • Voice traffic is fixed revenue, unlike SMS • Opened up the system- web, email, IM…

  3. Motivation… • Internet-originated text messages • Deny voice service to a city • Zombies • Hit lists • Similar to traffic from Slammer worm • BoA ATMs, 911 services

  4. Presentation Flow • Cellular Network Overview • Vulnerability Analysis • Research • Discovery • Attack vectors and implements • Scenario • Other stuff

  5. SMS/Cellular Network • Sending • Mobile device or ESME • External Short Messaging Entities (ESME) • Delivering • Short Messaging Service Center (SMSC) • SMS formatting • Queued for forwarding • Query Home Location Register (HLR) for directions

  6. SMS/Cellular Network • Delivering (Continued) • HLR • Subscriber Info, call waiting, text messaging • If user is busy, store SMS for later • Otherwise give address for MSC • Mobile Switching Center

  7. SMS/Cellular Network • Delivering (Continued) • MSC • Service, Authentication • Location management for BS, no not that BS! • Base Stations • Hand offs / gateway to PSTN • Public Switched Telephone Network • Query Visitor Location Register (VLR) • Returns Info when device is away from HLR • Forwards to correct BS for delivery

  8. SMS/Cellular Network

  9. Vulnerability Analysis • Bottlenecks • System is a composite of multiple Queuing Points • Injection rate versus delivery rate • Targeting Queues • SMSC • Finite number in queue, SMS age, policy • Messages remain in SMSC buffer when device is full • Device • 500 messages drained a battery

  10. Plan • Messages exceeding saturation levels are lost • Successful DoS needs • Multiple subscribers • Multiple interfaces • Hit-lists and Zombies

  11. Hit-list Creation • Internet search for NPA/NXX DB • Target wireless numbers by domain owner name • Web Scraping • Worm • Device recently call lists • Computers that sync with device

  12. Attack profile attributes • GSM gray-box testing • 900 SMS per hour on each dedicated channel • 1 dedicated channel per 4 voice • 2 dedicated channels per carrier • Protocol sharing • Number of dedicated channels per area • Number of carriers per area

  13. Cellular device channels • Two Channels • Control Channel (CCH) • Common CCH • BS uses for voice and SMS connections establishment • All connected mobiles are listening on this for signaling • Dedicated CCH • Data • Traffic Channel (TCH) • Voice

  14. Attack Scenario • 2500 numbers in hit list • Average 50 message device buffer • 8 dedicated channels, (D.C.) • 1 message per phone every 10.4 sec • 8.68 min to fill buffers

  15. Targeted Attacks • Fill the buffers, users loose messages • Data loss on some devices from overflowing • Read messages overwritten when new ones arrive (Nokia 3560) • Message delays due to overflowing • Campus alert messages- blocking? • Deleting junk SMS, accidentally delete good ones • Battery depletion

  16. Tomorrows email • SPAM • Phishing • Viruses • Cabir and Skulls • Both were bluetooth

  17. SMS Spam

  18. Summary • Cellular networks are critical part of • Social and economic infrastructures • Potential misuse from external services • DoS • InfoWar • Economic

  19. Contributions • Security impact of SMS on Cellular network • Demonstrate ability to deny serivce to city sized area • Techniques for targeting these systems • How to avoid

  20. Weaknesses • Gray-box testing • Documentation • Experimentation without EULA violations • Time of Day / Day of Week • Payload size variations • Estimations

  21. How to Improve • Traffic analysis for • Time of Day / Day of Week • Vary payload size • If White hats, work with the telecoms • Validate for more facts

  22. The End Thank you…

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