Sergej Proskurin, Marius Momeu, Seyedhamed Ghavamnia, V. Kemerlis, M. Polychronakis
{"title":"xMP: Selective Memory Protection for Kernel and User Space","authors":"Sergej Proskurin, Marius Momeu, Seyedhamed Ghavamnia, V. Kemerlis, M. Polychronakis","doi":"10.1109/SP40000.2020.00041","DOIUrl":null,"url":null,"abstract":"Attackers leverage memory corruption vulnerabilities to establish primitives for reading from or writing to the address space of a vulnerable process. These primitives form the foundation for code-reuse and data-oriented attacks. While various defenses against the former class of attacks have proven effective, mitigation of the latter remains an open problem. In this paper, we identify various shortcomings of the x86 architecture regarding memory isolation, and leverage virtualization to build an effective defense against data-oriented attacks. Our approach, called xMP, provides (in-guest) selective memory protection primitives that allow VMs to isolate sensitive data in user or kernel space in disjoint xMP domains. We interface the Xen altp2m subsystem with the Linux memory management system, lending VMs the flexibility to define custom policies. Contrary to conventional approaches, xMP takes advantage of virtualization extensions, but after initialization, it does not require any hypervisor intervention. To ensure the integrity of in-kernel management information and pointers to sensitive data within isolated domains, xMP protects pointers with HMACs bound to an immutable context, so that integrity validation succeeds only in the right context. We have applied xMP to protect the page tables and process credentials of the Linux kernel, as well as sensitive data in various user-space applications. Overall, our evaluation shows that xMP introduces minimal overhead for real-world workloads and applications, and offers effective protection against data-oriented attacks.","PeriodicalId":6849,"journal":{"name":"2020 IEEE Symposium on Security and Privacy (SP)","volume":"5 1","pages":"563-577"},"PeriodicalIF":0.0000,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"47","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE Symposium on Security and Privacy (SP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SP40000.2020.00041","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 47
Abstract
Attackers leverage memory corruption vulnerabilities to establish primitives for reading from or writing to the address space of a vulnerable process. These primitives form the foundation for code-reuse and data-oriented attacks. While various defenses against the former class of attacks have proven effective, mitigation of the latter remains an open problem. In this paper, we identify various shortcomings of the x86 architecture regarding memory isolation, and leverage virtualization to build an effective defense against data-oriented attacks. Our approach, called xMP, provides (in-guest) selective memory protection primitives that allow VMs to isolate sensitive data in user or kernel space in disjoint xMP domains. We interface the Xen altp2m subsystem with the Linux memory management system, lending VMs the flexibility to define custom policies. Contrary to conventional approaches, xMP takes advantage of virtualization extensions, but after initialization, it does not require any hypervisor intervention. To ensure the integrity of in-kernel management information and pointers to sensitive data within isolated domains, xMP protects pointers with HMACs bound to an immutable context, so that integrity validation succeeds only in the right context. We have applied xMP to protect the page tables and process credentials of the Linux kernel, as well as sensitive data in various user-space applications. Overall, our evaluation shows that xMP introduces minimal overhead for real-world workloads and applications, and offers effective protection against data-oriented attacks.