Ahmed M. Azab

Hypervision Across Worlds: Real-time Kernel Protection from the ARM TrustZone Secure World

TrustZone-based Real-time Kernel Protection (TZ-RKP) is a novel system that provides real-time protection of the OS kernel using the ARM TrustZone secure world. TZ-RKP is more secure than current approaches that use hypervisors to host kernel protection tools. Although hypervisors provide privilege and isolation, they face fundamental security challenges due to their growing complexity and code size. TZ-RKP puts its security monitor, which represents its entire Trusted Computing Base (TCB), in the TrustZone secure world; a safe isolated environment that is dedicated to security services. Hence, the security monitor is safe from attacks that can potentially compromise the kernel, which runs in the normal world. Using the secure world for kernel protection has been crippled by the lack of control over targets that run in the normal world. TZ-RKP solves this prominent challenge using novel techniques that deprive the normal world from the ability to control certain privileged system functions. These functions are forced to route through the secure world for inspection and approval before being executed. TZ-RKPs control of the normal world is non-bypassable. It can effectively stop attacks that aim at modifying or injecting kernel binaries. It can also stop attacks that involve modifying the system memory layout, e.g, through memory double mapping. This paper presents the implementation and evaluation of TZ-RKP, which has gone through rigorous and thorough evaluation of effectiveness and performance. It is currently deployed on the latest models of the Samsung Galaxy series smart phones and tablets, which clearly demonstrates that it is a practical real-world system.

SEER: practical memory virus scanning as a service

Virus Scanning-as-a-Service (VSaaS) has emerged as a popular security solution for virtual cloud environments. However, existing approaches fail to scan guest memory, which can contain an emerging class of Memory-only Malware. While several host-based memory scanners are available, they are computationally less practical for cloud environments. This paper proposes SEER as an architecture for enabling Memory VSaaS for virtualized environments. SEER leverages cloud resources and technologies to consolidate and aggregate virus scanning activities to efficiently detect malware residing in memory. Specifically, SEER combines fast memory snapshotting and computation deduplication to provide practical and efficient off-host memory virus scanning. We evaluate SEER and demonstrate up to an 87% reduction in data size that must be scanned and up to 72% savings in overall scan time, compared to naively applying file-based scanning approaches. Furthermore, SEER provides a 50% reduction in scan time when using a warm cache. In doing so, SEER provides a practical solution for cloud vendors to transparently and periodically scan virtual machine memory for malware.

NORAX: Enabling Execute-Only Memory for COTS Binaries on AArch64

Code reuse attacks exploiting memory disclosure vulnerabilities can bypass all deployed mitigations. One promising defense against this class of attacks is to enable execute-only memory (XOM) protection on top of fine-grained address space layout randomization (ASLR). However, recent works implementing XOM, despite their efficacy, only protect programs that have been (re)built with new compiler support, leaving commercial-off-the-shelf (COTS) binaries and source-unavailable programs unprotected. We present the design and implementation of NORAX, a practical system that retrofits XOM into stripped COTS binaries on AArch64 platforms. Unlike previous techniques, NORAX requires neither source code nor debugging symbols. NORAX statically transforms existing binaries so that during runtime their code sections can be loaded into XOM memory pages with embedded data relocated and data references properly updated. NORAX allows transformed binaries to leverage the new hardware-based XOM support—a feature widely available on AArch64 platforms (e.g., recent mobile devices) yet virtually unused due to the incompatibility of existing binaries. Furthermore, NORAX is designed to co-exist with other COTS binary hardening techniques, such as in-place randomization (IPR). We apply NORAX to the commonly used Android system binaries running on SAMSUNG Galaxy S6 and LG Nexus 5X devices. The results show that NORAX on average slows down the execution of transformed binaries by 1.18% and increases their memory footprint by 2.21%, suggesting NORAX is practical for real-world adoption.

SPOKE: Scalable Knowledge Collection and Attack Surface Analysis of Access Control Policy for Security Enhanced Android

SEAndroid is a mandatory access control (MAC) framework that can confine faulty applications on Android. Nevertheless, the effectiveness of SEAndroid enforcement depends on the employed policy. The growing complexity of Android makes it difficult for policy engineers to have complete domain knowledge on every system functionality. As a result, policy engineers sometimes craft over-permissive and ineffective policy rules, which unfortunately increased the attack surface of the Android system and have allowed multiple real-world privilege escalation attacks. We propose SPOKE, an SEAndroid Policy Knowledge Engine, that systematically extracts domain knowledge from rich-semantic functional tests and further uses the knowledge for characterizing the attack surface of SEAndroid policy rules. Our attack surface analysis is achieved by two steps: 1) It reveals policy rules that cannot be justified by the collected domain knowledge. 2) It identifies potentially over-permissive access patterns allowed by those unjustified rules as the attack surface. We evaluate SPOKE using 665 functional tests targeting 28 different categories of functionalities developed by Samsung Android Team. SPOKE successfully collected 12,491 access patterns for the 28 categories as domain knowledge, and used the knowledge to reveal 320 unjustified policy rules and 210 over-permissive access patterns defined by those rules, including one related to the notorious libstagefright vulnerability. These findings have been confirmed by policy engineers.

PrivWatcher: Non-bypassable Monitoring and Protection of Process Credentials from Memory Corruption Attacks

Commodity operating systems kernels are typically implemented using low-level unsafe languages, which leads to the inevitability of memory corruption vulnerabilities. Multiple defense techniques are widely adopted to mitigate the impact of memory corruption on executable code and control data. Nevertheless, there has not been much attention to defend against corruption of non-control data despite the fact that previous incidents of kernel exploitation showed that corrupting non-control data is a real threat. We present PrivWatcher, a framework for monitoring and protecting the integrity of process credentials and their usage contexts from memory corruption attacks. PrivWatcher solves multiple challenges to achieve this objective. It introduces techniques to isolate and protect the data that define process credentials and guarantee the locality of this data within the protected memory. Then, by adopting a dual reference monitor model, it guarantees the Time of Check To Time of Use (TOCTTOU) consistency between verification and usage contexts for process credentials. Moreover, it provides a secure mechanism that allows the presumably protected kernel code to verify the protected data without relying on unprotected data fields. PrivWatcher provides non-bypassable integrity assurances for process credentials and can be adapted to enforce a variety of integrity policies. In this paper, we demonstrate an application of PrivWatcher that enforces the original semantics of the OS kernels access control policy: a change in process privileges is legitimate only if an uncompromised kernel would have allowed it. We implemented a PrivWatcher prototype to protect Ubuntu Linux running on x86-64. Evaluation of our prototype showed that PrivWatcher is effective and efficient.