Biblio

Modern commercial software development organizations frequently prescribe to a development and deployment pattern for releases known as continuous integration / continuous deployment (CI/CD). Kubernetes, a cluster-based distributed application platform, is often used to implement this pattern. While the abstract concept is fairly well understood, CI/CD implementations vary widely. Resources are scattered across on-premise and cloud-based services, and systems may not be fully automated. Additionally, while a development pipeline may aim to ensure the security of the finished artifact, said artifact may not be protected from outside observers or cloud providers during execution. This paper describes a complete CI/CD pipeline running on Kubernetes that addresses four gaps in existing implementations. First, the pipeline supports strong separation-of-duties, partitioning development, security, and operations (i.e., DevSecOps) roles. Second, automation reduces the need for a human interface. Third, resources are scoped to a Kubernetes cluster for portability across environments (e.g., public cloud providers). Fourth, deployment artifacts are secured with Asylo, a development framework for trusted execution environments (TEEs).

Software diversity promises to invert the current balance of power in cybersecurity by preventing exploit reuse. Nevertheless, the comparative evaluation of diversity techniques has received scant attention. In ongoing work, we use the DARPA Cyber Grand Challenge (CGC) environment to assess the effectiveness of diversifying compilers in mitigating exploits. Our approach provides a quantitative comparison of diversity strategies and demonstrates wide variation in their effectiveness.

Diversity has been suggested as an effective alternative to the current trend in rules-based approaches to cybersecurity. However, little work to date has focused on how various techniques generalize to new attacks. That is, there is no accepted methodology that researchers use to evaluate diversity techniques. Starting with the hypothesis that an attacker's effort increases as the common set of executable code snippets (return-oriented programming (ROP) gadgets) decreases across application variants, we explore how different diversification techniques affect the set of ROP gadgets that is available to an attacker. We show that a small population of diversified variants is sufficient to eliminate 90-99% of ROP gadgets across a collection of real-world applications. Finally, we observe that the number of remaining gadgets may still be sufficient for an attacker to mount an effective attack regardless of the presence of software diversity.