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Recent work shows that the Rowhammer hardware bug can be used to craft powerful attacks and completely subvert a system. However, existing e orts either describe probabilistic (and thus unreliable) attacks or rely on special (and often unavailable) memory management features to place victim objects in vulnerable physical memory locations. Moreover, prior work only targets x86 and researchers have openly wondered whether Rowhammer attacks on other architectures, such as ARM, are even possible. We show that deterministic Rowhammer attacks are feasible on commodity mobile platforms and that they cannot be mitigated by current defenses. Rather than assuming special memory management features, our attack, Drammer, solely relies on the predictable memory reuse patterns of standard physical memory allocators. We implement Drammer on Android/ARM, demonstrating the practicability of our attack, but also discuss a generalization of our approach to other Linux-based platforms. Furthermore, we show that traditional x86-based Rowhammer exploitation techniques no longer work on mobile platforms and address the resulting challenges towards practical mobile Rowhammer attacks. To support our claims, we present the rst Rowhammer-based Android root exploit relying on no software vulnerability, and requiring no user permissions. In addition, we present an analysis of several popular smartphones and nd that many of them are susceptible to our Drammer attack. We conclude by discussing potential mitigation strategies and urging our community to address the concrete threat of faulty DRAM chips in widespread commodity platforms.
SDG 16 - Peace, classrowhammer, classmobile, Justice and Strong Institutions
SDG 16 - Peace, classrowhammer, classmobile, Justice and Strong Institutions
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 210 | |
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| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 1% | |
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