Visible to the public AddrArmor: An Address-based Runtime Code-reuse Attack Mitigation for Shared Objects at the Binary-level

TitleAddrArmor: An Address-based Runtime Code-reuse Attack Mitigation for Shared Objects at the Binary-level
Publication TypeConference Paper
Year of Publication2021
AuthorsLin, Kunli, Xia, Haojun, Zhang, Kun, Tu, Bibo
Conference Name2021 IEEE Intl Conf on Parallel Distributed Processing with Applications, Big Data Cloud Computing, Sustainable Computing Communications, Social Computing Networking (ISPA/BDCloud/SocialCom/SustainCom)
Keywordscode-reuse attack, codes, compositionality, Hardware, Information Reuse, instrumentation, Instruments, Loading, Performance analysis, pubcrawl, Resiliency, Runtime, security
AbstractThe widespread adoption of DEP has made most modern attacks follow the same general steps: Attackers try to construct code-reuse attacks by using vulnerable indirect branch instructions in shared objects after successful exploits on memory vulnerabilities. In response to code-reuse attacks, researchers have proposed a large number of defenses. However, most of them require access to source code and/or specific hardware features. These limitations hinder the deployment of these defenses much.In this paper, we propose an address-based code-reuse attack mitigation for shared objects at the binary-level. We emphasize that the execution of indirect branch instruction must follow several principles we propose. More specifically, we first reconstruct function boundaries at the program's dynamic-linking stage by combining shared object's dynamic symbols with binary-level instruction analysis. We then leverage static instrumentation to hook vulnerable indirect branch instructions to a novel target address computation and validation routine. At runtime, AddrArmor will protect against code-reuse attacks based on the computed target address.Our experimental results show that AddrArmor provides a strong line of defense against code reuse attacks, and has an acceptable performance overhead of about 6.74% on average using SPEC CPU 2006.
DOI10.1109/ISPA-BDCloud-SocialCom-SustainCom52081.2021.00029
Citation Keylin_addrarmor_2021