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Massachusetts Institute of Technology

Taxi : defeating code reuse attacks with tagged memory

Abstract

dc:description.abstract

The rise of code reuse attacks has been devastating for users of languages like C and C++ that lack memory safety. We survey existing defenses to understand why none are generally applicable, focusing our attention on the Code Pointer Integrity (CPI) defense. We show that while CPI is hard to implement securely on modern architectures, it is based on the promising idea of storing metadata on memory. We also introduce Taxi (Tagged C), a set of hardware modifications that aim to prevent code reuse attacks by storing small amounts of memory metadata known as tags in hardware. Our reference implementation prevents several classes of code reuse attacks without losing compatibility with the C memory model and provides valuable insight into how tagged architectures can be used to enforce security properties on existing code.

Degree

thesis:*
Department dc:contributor.department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2015

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • González, Julián Armando
Advisor dc:contributor.advisor
  • Howard E. Shrobe.

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1721.1/105987
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/105987

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

González, Julián Armando. Taxi : defeating code reuse attacks with tagged memory. Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/105987