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arXiv · 2502.16756

Towards Reinforcement Learning for Exploration of Speculative Execution Vulnerabilities

Evan Lai·Wenjie Xiong·Edward Suh·Mohit Tiwari·Mulong Luo
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Abstract

Speculative attacks such as Spectre can leak secret information without being discovered by the operating system. Speculative execution vulnerabilities are finicky and deep in the sense that to exploit them, it requires intensive manual labor and intimate knowledge of the hardware. In this paper, we introduce SpecRL, a framework that utilizes reinforcement learning to find speculative execution leaks in post-silicon (black box) microprocessors.

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Evan Lai, Wenjie Xiong, Edward Suh, Mohit Tiwari, Mulong Luo. 2025-02-24. Towards Reinforcement Learning for Exploration of Speculative Execution Vulnerabilities. https://arxiv.org/abs/2502.16756

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