Virtualization technologies employed by the cloud providers allow scalable and fast deployment of computation resources at a small cost. Being a core component in the cloud configuration, the hypervisor becomes the target of outside attacks that try to disrupt the normal operation of other users’ systems or to gain control over the cloud infrastructure. Therefore, an effective and reliable method of discovering security vulnerabilities inside the hypervisors is needed.We created a testing environment that employs fuzzing to detect possible vulnerabilities inside the Firecracker hypervisor. We present a complete fuzzing toolchain that can be integrated into the Firecracker development cycle to discover and report bugs that can be missed by other testing methods. Our solution was internally tested by the Amazon Web Services team with promising results.

Apple uses several access control mechanisms to prevent third party applications from directly accessing security sensitive resources, including sandboxing and file access control. However, third party applications may also indirectly access these resources using inter-process communication (IPC) with system daemons. If these daemons fail to properly enforce access control on IPC, confused deputy vulnerabilities may result. Identifying such vulnerabilities begins with an enumeration of all IPC services accessible to third party applications. However, the IPC interfaces and their corresponding access control policies are unknown and must be reverse engineered at a large scale. In this paper, we present the Kobold framework to study NSXPC-based system services using a combination of static and dynamic analysis. Using Kobold, we discovered multiple NSXPC services with confused deputy vulnerabilities and daemon crashes. Our findings include the ability to activate the microphone, disable access to all websites, and leak private data stored in iOS File Providers.

Modern operating systems, such as iOS, use multiple access control policies to define an overall protection system. However, the complexity of these policies and their interactions can hide policy flaws that compromise the security of the protection system. We propose iOracle, a framework that logically models the iOS protection system such that queries can be made to automatically detect policy flaws. iOracle models policies and runtime context extracted from iOS firmware images, developer resources, and jailbroken devices, and iOracle significantly reduces the complexity of queries by modeling policy semantics. We evaluate iOracle by using it to successfully triage executables likely to have policy flaws and comparing our results to the executables exploited in four recent jailbreaks. When applied to iOS 10, iOracle identifies previously unknown policy flaws that allow attackers to modify or bypass access control policies. For compromised system processes, consequences of these policy flaws include sandbox escapes (with respect to read/write file access) and changing the ownership of arbitrary files. By automating the evaluation of iOS access control policies, iOracle provides a practical approach to hardening iOS security by identifying policy flaws before they are exploited.

The popularity and usage of mobile devices have increased and therefore performance demands changed. An important aspect is represented by the whole system stability which has a big impact on general user experience. This paper proposes a solution for improving the implementation process and stability of operating systems for mobile devices. It consists of a system service which collects error messages and sends them to a server. Received data is saved, processed and then useful information is exposed to developers.