Control-flow hijacking and data-oriented attacks are becoming more sophisticated. These attacks, especially data-oriented attacks, can result in critical security threats, such as leaking an SSL key. Data-oriented attacks are hard to defend against with acceptable performance due to the sheer amount of data pointers present. The root cause of such attacks is using pointers in unintended ways; fundamentally, these attacks rely on abusing pointers to violate the original scope they were used in or the original types that they were declared as.

System calls are a critical building block in many serious security attacks, such as control-flow hijacking and privilege escalation attacks. Security-sensitive system calls (e.g., execve, mprotect), especially play a major role in completing attacks. Yet, few defense efforts focus to ensure their legitimate usage, allowing attackers to maliciously leverage system calls in attacks.

Most modern software attacks are rooted in memory corruption vulnerabilities, which are capable of altering security-sensitive data (e.g., function pointers) to unintended values. This paper introduces a new security property, the Value Invariant Property (VIP), and HyperSpace, our prototype that enforces VIP on security-sensitive data. HyperSpace safeguards the integrity of "data values" instead of enforcing control/data flow, allowing for low runtime overhead, yet defeating critical attacks effectively. We implement four representative security policies including Control Flow Integrity (VIP-CFI), Code Pointer Integrity (VIP-CPI), Virtual function Table protection (VIP-VTPtr), and heap metadata protection based on HyperSpace. We evaluate HyperSpace with SPEC CPU2006 benchmarks and real-world applications (NGINX and PostgreSQL) and test how HyperSpace defeats memory corruption-based attacks, including three real-world exploits and six attacks that bypass existing defenses (COOP, heap exploits, etc.). Our experimental evaluation shows that HyperSpace successfully stops all these attacks with low runtime overhead: 0.88% and 6.18% average performance overhead for VIP-CFI and VIP-CPI, respectively, and overall approximately 13.18% memory overhead with VIP-CPI in SPEC CPU2006.

One approach to assess the security of embedded IoT devices is applying dynamic analysis such as fuzz testing to their firmware in scale. To this end, existing approaches aim to provide an emulation environment that mimics the behavior of real hardware/peripherals. Nonetheless, in practice, such approaches can emulate only a small fraction of firmware images. For example, Firmadyne, a state-of-the-art tool, can only run 183 (16.28%) of 1,124 wireless router/IP-camera images that we collected from the top eight manufacturers. Such a low emulation success rate is caused by discrepancy in the real and emulated firmware execution environment.

Multi-user oblivious storage allows users to access their shared data on the cloud while retaining access pattern obliviousness and data confidentiality simultaneously. Most secure and efficient oblivious storage systems focus on the utilization of the maximum network bandwidth in serving concurrent accesses via a trusted proxy. How- ever, since the proxy executes a standard ORAM protocol over the network, the performance is capped by the network bandwidth and latency. Moreover, some important features such as access control and security against active adversaries have not been thoroughly explored in such proxy settings. In this paper, we propose MOSE, a multi-user oblivious storage system that is efficient and enjoys from some desirable security properties. Our main idea is to harness a secure enclave, namely Intel SGX, residing on the untrusted storage server to execute proxy logic, thereby, minimizing the network bottleneck of proxy-based designs. In this regard, we address various technical design chal- lenges such as memory constraints, side-channel attacks and scala- bility issues when enabling proxy logic in the secure enclave. We present a formal security model and analysis for secure enclave multi-user ORAM with access control. We optimize MOSE to boost its throughput in serving concurrent requests. We implemented MOSE and evaluated its performance on commodity hardware. Our evaluation confirmed the efficiency of MOSE, where it achieves approximately two orders of magnitudes higher throughput than the state-of-the-art proxy-based design, and also, its performance is scalable proportional to the available system resources.

Fuzz testing has been proved its effectiveness in discovering software vulnerabilities. Empowered its randomness nature along with a coverage-guiding feature, fuzzing has been identified a vast number of vulnerabilities in real-world programs. This paper begins with an observation that the design of the current state-of-the-art fuzzers is not well suited for a particular (but yet important) set of software programs. Specifically, current fuzzers have limitations in fuzzing programs serving multiple purposes, where each purpose is controlled by extra options.

Defense techniques such as Data Execution Prevention (DEP) and Address Space Layout Randomization (ASLR) were role models in preventing early return-oriented programming (ROP) attacks by keeping performance and scalability in the forefront, making them widely-adopted. As code reuse attacks evolved in complexity, defenses have lost touch with pragmatic defense design to ensure security, either being narrow in scope or providing unrealistic overheads.

Abstract The ability to query and update over encrypted data is an essential feature to enable breach-resilient cyber-infrastructures. Statistical attacks on searchable encryption (SE) have demonstrated the importance of sealing information leaks in access patterns. In response to such attacks, the community has proposed the Oblivious Random Access Machine (ORAM). However, due to the logarithmic communication overhead of ORAM, the composition of ORAM and SE is known to be costly in the conventional client-server model, which poses a critical barrier toward its practical adaptations. In this paper, we propose a novel hardware-supported privacy-enhancing platform called Practical Oblivious Search and Update Platform (POSUP), which enables oblivious keyword search and update operations on large datasets with high efficiency. We harness Intel SGX to realize efficient oblivious data structures for oblivious search/update purposes. We implemented POSUP and evaluated its performance on a Wikipedia dataset containing ≥229 keyword-file pairs. Our implementation is highly efficient, taking only 1 ms to access a 3 KB block with Circuit-ORAM. Our experiments have shown that POSUP offers up to 70× less end-to-end delay with 100× reduced network bandwidth consumption compared with the traditional ORAM-SE composition without secure hardware. POSUP is also at least 4.5× faster for up to 99.5% of keywords that can be searched compared with state-of-the-art Intel SGX-assisted search platforms.

Kernel hardening has been an important topic since many applications and security mechanisms often consider the kernel as part of their Trusted Computing Base (TCB). Among various hardening techniques, Kernel Address Space Layout Randomization (KASLR) is the most effective and widely adopted defense mechanism that can practically mitigate various memory corruption vulnerabilities, such as buffer overflow and use-after-free. In principle, KASLR is secure as long as no memory leak vulnerability exists and high entropy is ensured.

Long Term Evolution (LTE) is becoming the dominant cellular networking technology, shifting the cellular network away from its circuit-switched legacy towards a packet-switched network that resembles the Internet. To support voice calls over the LTE network, operators have introduced Voice-over-LTE (VoLTE), which dramatically changes how voice calls are handled, both from user equipment and infrastructure perspectives. We find that this dramatic shift opens up a number of new attack surfaces that have not been previously explored. To call attention to this matter, this paper presents a systematic security analysis.

While private browsing is a standard feature, its implementation has been inconsistent among the major browsers. More seriously, it often fails to provide the adequate or even the intended privacy protection. For example, as shown in prior research, browser extensions and add-ons often undermine the goals of private browsing. In this paper, we first present our systematic study of private browsing. We developed a technical approach to identify browser traces left behind by a private browsing session, and showed that Chrome and Firefox do not correctly clear some of these traces. We analyzed the source code of these browsers and discovered that the current implementation approach is to decide the behaviors of a browser based on the current browsing mode (i.e., private or public); but such decision points are scattered throughout the code base. This implementation approach is very problematic because developers are prone to make mistakes given the complexities of browser components (including extensions and add-ons). Based on this observation, we propose a new and general approach to implement private browsing. The main idea is to overlay the actual filesystem with a sandbox filesystem when the browser is in private browsing mode, so that no unintended leakage is allowed and no persistent modification is stored. This approach requires no change to browsers and the OS kernel because the layered sandbox filesystem is implemented by interposing system calls. We have implemented a prototype system called Ucognito on Linux. Our evaluations show that Ucognito, when applied to Chrome and Firefox, stops all known privacy leaks identified by prior work and our current study. More importantly, Ucognito incurs only negligible performance overhead: e.g., 0%-2.5% in benchmarks for standard JavaScript and webpage loading.

Driven in part by federal law, accessibility (a11y) support for disabled users is becoming ubiquitous in commodity OSs. Some assistive technologies such as natural language user interfaces in mobile devices are welcomed by the general user population. Unfortunately, adding new features in modern, complex OSs usually introduces new security vulnerabilities. Accessibility support is no exception. Assistive technologies can be defined as computing subsystems that either transform user input into interaction requests for other applications and the underlying OS, or transform application and OS output for display on alternative devices. Inadequate security checks on these new I/O paths make it possible to launch attacks from accessibility interfaces. In this paper, we present the first security evaluation of accessibility support for four of the most popular computing platforms: Microsoft Windows, Ubuntu Linux, iOS, and Android. We identify twelve attacks that can bypass state-of-the-art defense mechanisms deployed on these OSs, including UAC, the Yama security module, the iOS sandbox, and the Android sandbox. Further analysis of the identified vulnerabilities shows that their root cause is that the design and implementation of accessibility support involves inevitable trade-offs among compatibility, usability, security, and (economic) cost. These trade-offs make it difficult to secure a system against misuse of accessibility support. Based on our findings, we propose a number of recommendations to either make the implementation of all necessary security checks easier and more intuitive, or to alleviate the impact of missing/incorrect checks. We also point out open problems and challenges in automatically analyzing accessibility support and identifying security vulnerabilities.