%0 Conference Proceedings
%T Wrangling in the Power of Code Pointers with ProxyCFI
%+ University of Michigan [Ann Arbor]
%A Aga, Misiker, Tadesse
%A Holoday, Colton
%A Austin, Todd
%Z Part 6: Source Code Security
%< avec comité de lecture
%( Lecture Notes in Computer Science
%B 33th IFIP Annual Conference on Data and Applications Security and Privacy (DBSec)
%C Charleston, SC, United States
%Y Simon N. Foley
%I Springer International Publishing
%3 Data and Applications Security and Privacy XXXIII
%V LNCS-11559
%P 317-337
%8 2019-07-15
%D 2019
%R 10.1007/978-3-030-22479-0_17
%K CFG mimicry attacks
%K CFI
%K Pointer proxy
%Z Computer Science [cs]Conference papers
%X Despite being a more than 40-year-old dark art, control flow attacks remain a significant and attractive means of penetrating applications. Control Flow Integrity (CFI) prevents control flow attacks by forcing the execution path of a program to follow the control flow graph (CFG). This is performed by inserting checks before indirect jumps to ensure that the target is within a statically determined valid target set. However, recent advanced control flow attacks have been shown to undermine prior CFI techniques by swapping targets of an indirect jump with another one from the valid set.In this article, we present a novel approach to protect against advanced control flow attacks called ProxyCFI. Instead of building protections to stop code pointer abuse, we replace code pointers wholesale in the program with a less powerful construct – pointer proxies. Pointer proxies are random identifiers associated with legitimate control flow edges. All indirect control transfers in the program are replaced with multi-way branches that validate control transfers with pointer proxies. As pointer proxies are uniquely associated with both the source and the target of control-flow edges, swapping pointer proxies results in a violation even if they have the same target, stopping advanced control flow attacks that undermine prior CFI techniques. In all, ProxyCFI stops a broad range of recently reported advanced control flow attacks on real-world applications with only a 4% average slowdown.
%G English
%Z TC 11
%Z WG 11.3
%2 https://inria.hal.science/hal-02384583/document
%2 https://inria.hal.science/hal-02384583/file/480962_1_En_17_Chapter.pdf
%L hal-02384583
%U https://inria.hal.science/hal-02384583
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-TC
%~ IFIP-WG
%~ IFIP-TC11
%~ IFIP-WG11-3
%~ IFIP-DBSEC
%~ IFIP-LNCS-11559