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Uncovering and Exploiting AMD Speculative Memory Access Predictors for Fun and Profit

Chang Liu, Dongsheng Wang, Yongqiang Lyu, Pengfei Qiu, Yu Jin, Zhuoyuan Lu, Yinqian Zhang, Gang Qu

2024Year
9Citations
4Top-tier citations

Abstract

This paper presents a comprehensive investigation into the security vulnerabilities associated with speculative memory access on AMD processors. Firstly, employing novel reverse engineering techniques, our study uncovers two key predictors, namely the Predictive Store Forwarding Predictor (PSFP) and the Speculative Store Bypass Predictor (SSBP), along with elucidating their internal structures and state machine designs. Secondly, our research empirically confirms that these predictors can be deliberately manipulated and altered during transient execution, resulting in secret leakage across security domains. Leveraging these discoveries, we propose innovative attacks targeting these predictors, including an out-of-place variant of Spectre-STL and an entirely new form of Spectre attack named Spectre-CTL. Finally, we establish experimentally that enabling Speculative Store Bypass Disable alleviates the vulnerabilities. However, this comes at the expense of significant performance degradation.

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