Constraint-based Diversification of JOP Gadgets

TL;DR

This paper presents DivCon, a constraint-based method using Large Neighborhood Search to generate diverse, high-quality software variants that are resilient against Jump-Oriented Programming attacks, balancing diversity and code quality.

Contribution

DivCon introduces a novel constraint-based diversification approach with adjustable goals, employing LNS and structural decomposition to efficiently produce resilient code variants.

Findings

DivCon generates highly diverse code variants with low shared gadgets.

The approach effectively balances code quality and diversity.

Experimental results show improved resilience against JOP attacks.

Abstract

Modern software deployment process produces software that is uniform and hence vulnerable to large-scale code-reuse attacks, such as Jump-Oriented Programming (JOP) attacks. Compiler-based diversification improves the resilience of software systems by automatically generating different assembly code versions of a given program. Existing techniques are efficient but do not have a precise control over the quality of the generated variants. This paper introduces Diversity by Construction (DivCon), a constraint-based approach to software diversification. Unlike previous approaches, DivCon allows users to control and adjust the conflicting goals of diversity and code quality. A key enabler is the use of Large Neighborhood Search (LNS) to generate highly diverse code efficiently. For larger problems, we propose a combination of LNS with a structural decomposition of the problem. To further improve the diversification efficiency of DivCon against JOP attacks, we propose an application-specific distance measure tailored to the characteristics of JOP attacks. We evaluate DivCon with 20 functions from a popular benchmark suite for embedded systems. These experiments show that the combination of LNS and our application-specific distance measure generates binary programs that are highly resilient against JOP attacks. Our results confirm that there is a trade-off between the quality of each assembly code version and the diversity of the entire pool of versions. In particular, the experiments show that DivCon generates near-optimal binary programs that share a small number of gadgets. For constraint programming researchers and practitioners, this paper demonstrates that LNS is a valuable technique for finding diverse solutions. For security researchers and software engineers, DivCon extends the scope of compiler-based diversification to performance-critical and resource-constrained applications.