ROLoad-PMP: Securing Sensitive Operations for Kernels and Bare-Metal Firmware

A common way for attackers to compromise victim systems is hijacking sensitive operations (e.g., control-flow transfers) with attacker-controlled inputs. Existing solutions in general only protect parts of these targets and have high performance overheads, which are impractical and hard to deploy on systems with limited resources (e.g., IoT devices) or for low-level software like kernels and bare-metal firmware. In this paper, we present a lightweight hardware-software co-design solution ROLoad-PMP to protect sensitive operations from being hijacked for low-level software. First, we propose new instructions, which only load data from read-only memory regions with specific keys, to guarantee the integrity of pointees pointed by (potentially corrupted) data pointers. Then, we provide a program hardening mechanism to protect sensitive operations, by classifying and placing their operands into read-only memory with different keys at compile-time and loading them with ROLoad-PMP-family instructions at runtime. We have implemented an FPGA-based prototype of ROLoad-PMP based on RISC-V, and demonstrated an important defense application, i.e., forward-edge control-flow integrity. Results showed that ROLoad-PMP only costs few extra hardware resources (<inline-formula><tex-math notation="LaTeX">$\lt 1.40\%$</tex-math></inline-formula>). Moreover, it enables many lightweight (e.g., with negligible overheads <inline-formula><tex-math notation="LaTeX">$\lt 0.853\%$</tex-math></inline-formula>) defenses, and provides broader and stronger security guarantees than existing hardware solutions, e.g., ARM BTI and Intel CET.

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Publication Details

Journal
IEEE Transactions on Computers
Published
2024-08-23
DOI
https://doi.org/10.1109/tc.2024.3449105
Citations
3
Primary Topic
Security and Verification in Computing
Type
article
Field-Weighted Citation Impact
1.04
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article

ROLoad-PMP: Securing Sensitive Operations for Kernels and Bare-Metal Firmware

Jianping Wu, C Li, Wende Tan, Yangyu Chen et al.
3 citations
IEEE Transactions on Computers
Security and Verification in Computing
1.04
article

ROLoad-PMP: Securing Sensitive Operations for Kernels and Bare-Metal Firmware

Jianping Wu, C Li, Wende Tan, Yangyu Chen, Yuan Li, Chao Zhang
article en
3 citations

Abstract

A common way for attackers to compromise victim systems is hijacking sensitive operations (e.g., control-flow transfers) with attacker-controlled inputs. Existing solutions in general only protect parts of these targets and have high performance overheads, which are impractical and hard to deploy on systems with limited resources (e.g., IoT devices) or for low-level software like kernels and bare-metal firmware. In this paper, we present a lightweight hardware-software co-design solution ROLoad-PMP to protect sensitive operations from being hijacked for low-level software. First, we propose new instructions, which only load data from read-only memory regions with specific keys, to guarantee the integrity of pointees pointed by (potentially corrupted) data pointers. Then, we provide a program hardening mechanism to protect sensitive operations, by classifying and placing their operands into read-only memory with different keys at compile-time and loading them with ROLoad-PMP-family instructions at runtime. We have implemented an FPGA-based prototype of ROLoad-PMP based on RISC-V, and demonstrated an important defense application, i.e., forward-edge control-flow integrity. Results showed that ROLoad-PMP only costs few extra hardware resources (<inline-formula><tex-math notation="LaTeX">$\lt 1.40\%$</tex-math></inline-formula>). Moreover, it enables many lightweight (e.g., with negligible overheads <inline-formula><tex-math notation="LaTeX">$\lt 0.853\%$</tex-math></inline-formula>) defenses, and provides broader and stronger security guarantees than existing hardware solutions, e.g., ARM BTI and Intel CET.

IEEE Transactions on ComputersVol. 73(12)
Chongqing University (CN), Peking University (CN), Tsinghua University (CN)
Openalex Percentile: Top 19%
Security and Verification in Computing
1.04
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