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Drive-By Key-Extraction Cache Attacks from Portable Code

  • Daniel Genkin
  • Lev Pachmanov
  • Eran Tromer
  • Yuval Yarom
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10892)

Abstract

We show how malicious web content can extract cryptographic secret keys from the user’s computer. The attack uses portable scripting languages supported by modern browsers to induce contention for CPU cache resources, and thereby gleans information about the memory accesses of other programs running on the user’s computer. We show how this side-channel attack can be realized in WebAssembly and PNaCl; how to attain fine-grained measurements; and how to extract ElGamal, ECDH and RSA decryption keys from various cryptographic libraries.

The attack does not rely on bugs in the browser’s nominal sandboxing mechanisms, or on fooling users. It applies even to locked-down platforms with strong confinement mechanisms and browser-only functionality, such as Chromebook devices.

Moreover, on browser-based platforms the attacked software too may be written in portable JavaScript; and we show that in this case even implementations of supposedly-secure constant-time algorithms, such as Curve25519’s, are vulnerable to our attack.

Notes

Acknowledgments

This work was partially inspired by unpublished work on portable cache attacks done jointly with Ethan Heilman, Perry Hung, Taesoo Kim and Andrew Meyer.

Daniel Genkin, Lev Pachmanov and Eran Tromer are members of the Check Point Institute for Information Security. Yuval Yarom performed part of this work as a visiting scholar at the University of Pennsylvania.

This work was supported by the Australian Department of Education and Training through an Endeavour Research Fellowship; by the Blavatnik Interdisciplinary Cyber Research Center (ICRC); by the Check Point Institute for Information Security; by the Defense Advanced Research Project Agency (DARPA) and Army Research Office (ARO) under Contract #W911NF-15-C-0236; by the Israeli Ministry of Science and Technology; by the Israeli Centers of Research Excellence I-CORE program (center 4/11); by the Leona M. & Harry B. Helmsley Charitable Trust; by NSF awards #CNS-1445424 and #CCF-1423306; by the 2017–2018 Rothschild Postdoctoral Fellowship; by the Warren Center for Network and Data Sciences; by the financial assistance award 70NANB15H328 from the U.S. Department of Commerce, National Institute of Standards and Technology; and by the Defense Advanced Research Project Agency (DARPA) under Contract #FA8650-16-C-7622. Any opinions, findings, and conclusions or recommendations expressed are those of the authors and do not necessarily reflect the views of ARO, DARPA, NSF, the U.S. Government or other sponsors.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Daniel Genkin
    • 1
    • 2
  • Lev Pachmanov
    • 3
  • Eran Tromer
    • 3
    • 4
  • Yuval Yarom
    • 5
    • 6
  1. 1.University of PennsylvaniaPhiladelphiaUSA
  2. 2.University of MarylandCollege ParkUSA
  3. 3.Tel Aviv UniversityTel AvivIsrael
  4. 4.Columbia UniversityNew YorkUSA
  5. 5.University of AdelaideAdelaideAustralia
  6. 6.Data61SydneyAustralia

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