Presentation
Automated Discovery, Classification, and Systematic Security Verification Methodology for Undocumented Instructions
DescriptionUndocumented instructions pose a growing security threat, yet current research is limited.
Existing work focuses on discovery with constrained techniques, while semantic analysis is manual and ad-hoc. Moreover, a significant gap exists in methodologies for systematic security verification. This paper presents a comprehensive framework for the automated discovery, systematic classification, and security verification of undocumented instructions. Our evaluation discovered 23 new instructions and classified 29 using a classifier with 99.8357% accuracy. Most importantly, we verified that 5 instructions have tangible security implications, demonstrating our approach's efficacy in addressing threats at the processor instruction level.
Existing work focuses on discovery with constrained techniques, while semantic analysis is manual and ad-hoc. Moreover, a significant gap exists in methodologies for systematic security verification. This paper presents a comprehensive framework for the automated discovery, systematic classification, and security verification of undocumented instructions. Our evaluation discovered 23 new instructions and classified 29 using a classifier with 99.8357% accuracy. Most importantly, we verified that 5 instructions have tangible security implications, demonstrating our approach's efficacy in addressing threats at the processor instruction level.
Event Type
Research Manuscript
TimeTuesday, July 2811:23am - 11:36am PDT
LocationMtg Room 203C