Backend
SecDMP: Provably Secure Data Memory-Dependent Prefetching (Extended Version)
arXiv cs.CR0 views
arXiv:2610.37454v1 Announce Type: new Abstract: Data memory-dependent prefetchers (DMPs) are a microarchitectural optimization recently introduced in mainstream desktop and server CPUs. Although DMPs offer performance improvements, they have been shown to enable side-channel leakage of secrets, even from constant-time code that has been hardened against Spectre attacks. Unfortunately, existing defenses either incur significant performance overhead or, as we show, fail to prevent all DMP leakage. In this work, we address this gap by designing a defense that is both secure and efficient. First, we propose a classification of DMP leakage, categorize existing and novel attacks, and analyze which leakage classes are mitigated by existing defenses. We validate this analysis empirically by implementing the first open-source DMPs on a RISC-V processor, showing that the only existing defense that aims to preserve DMP performance fails to protect against entire leakage classes. Next, we propose SecDMP, a provably secure and efficient hardware-based defense. SecDMP requires secrets to be marked in memory and ensures that DMPs never encode these secrets in the microarchitecture---without compromising performance for public data. We formally prove that SecDMP introduces no leakage beyond a baseline semantics without DMPs. Notably, when combined with speculative-execution defenses, SecDMP restores complete microarchitectural security for constant-time code. Finally, our empirical evaluation shows that SecDMP prevents all DMP leakage while incurring minimal performance overhead and hardware cost.
Source:https://arxiv.org/abs/2610.37454PreviousThe Envelope Layer: An Underestimated Surface of LLM Agent DefenseNextWhen POST Becomes GET: Investigating HTTP Method Interchangeability and Its Security Implications
Related posts
I read all 308 open jobs at xAI: 54% are in its data center team, and most of them are in Memphis
0dev.to AI
Claude Code marketing analytics with an app-scoped key
0dev.to AI
I red-teamed my own support bot with 30 scenarios. It failed 7 — here's the harness.
0dev.to AI
The Log That Told Everyone the Password: Redacting Secrets in n8n Execution Logs
0dev.to WebDev
Your AI Portal Isn't Ready Until a Stranger Can Recover from Failure
0dev.to WebDev
API traffic monitoring: what to track, and how to set it up for a Node API
0dev.to Security