Confidential computing is rapidly evolving with Intel TDX, AMD SEV-SNP, and Arm CCA. However, unlike TDX and SEV-SNP, Arm CCA lacks publicly available hardware, making performance evaluation difficult. While Arm's hardware simulation provides functional correctness, it lacks cycle accuracy, forcing researchers to build best-effort performance prototypes by transplanting their CCA-bound implementations onto non-CCA Arm boards and estimating CCA overheads in software. This leads to duplicated efforts, inconsistent comparisons, and high barriers to entry.

In this talk, I will present OpenCCA, our open research framework that enables CCA-bound code execution on commodity Arm hardware. OpenCCA systematically adapts the software stack—from bootloader to hypervisor—to emulate CCA operations for performance evaluation while preserving functional correctness. Our approach allows researchers to lift-and-shift implementations from Arm’s simulation to real hardware, providing a framework for performance analysis, even without publicly available Arm CPUs with CCA.

I will discuss the key challenges in OpenCCA's design, implementation, and evaluation, demonstrating its effectiveness through life-cycle measurements and case studies inspired by prior CCA research. OpenCCA runs on an affordable Armv8.2 Rockchip RK3588 board ($250), making it a practical and accessible platform for Arm CCA research.

https://github.com/opencca