Biblio

Hardware security architectures and primitives are becoming increasingly important in practice providing trust anchors and trusted execution environment to protect modern software systems. Over the past two decades we have witnessed various hardware security solutions and trends from Trusted Platform Modules (TPM), performance counters for security, ARM's TrustZone, and Physically Unclonable Functions (PUFs), to very recent advances such as Intel's Software Guard Extension (SGX). Unfortunately, these solutions are rarely used by third party developers, make strong trust assumptions (including in manufacturers), are too expensive for small constrained devices, do not easily scale, or suffer from information leakage. Academic research has proposed a variety of solutions, in hardware security architectures, these advancements are rarely deployed in practice.

Just-in-time return-oriented programming (JIT-ROP) is a powerful memory corruption attack that bypasses various forms of code randomization. Execute-only memory (XOM) can potentially prevent these attacks, but requires source code. In contrast, destructive code reads (DCR) provide a trade-off between security and legacy compatibility. The common belief is that DCR provides strong protection if combined with a high-entropy code randomization. The contribution of this paper is twofold: first, we demonstrate that DCR can be bypassed regardless of the underlying code randomization scheme. To this end, we show novel, generic attacks that infer the code layout for highly randomized program code. Second, we present the design and implementation of BGDX (Byte-Granular DCR and XOM), a novel mitigation technique that protects legacy binaries against code inference attacks. BGDX enforces memory permissions on a byte-granular level allowing us to combine DCR and XOM for legacy, off-the-shelf binaries. Our evaluation shows that BGDX is not only effective, but highly efficient, imposing only a geometric mean performance overhead of 3.95 % on SPEC.

Remote attestation is a crucial security service particularly relevant to increasingly popular IoT (and other embedded) devices. It allows a trusted party (verifier) to learn the state of a remote, and potentially malware-infected, device (prover). Most existing approaches are static in nature and only check whether benign software is initially loaded on the prover. However, they are vulnerable to runtime attacks that hijack the application's control or data flow, e.g., via return-oriented programming or data-oriented exploits. As a concrete step towards more comprehensive runtime remote attestation, we present the design and implementation of Control-FLow ATtestation (C-FLAT) that enables remote attestation of an application's control-flow path, without requiring the source code. We describe a full prototype implementation of C-FLAT on Raspberry Pi using its ARM TrustZone hardware security extensions. We evaluate C-FLAT's performance using a real-world embedded (cyber-physical) application, and demonstrate its efficacy against control-flow hijacking attacks.

Recent literature on iOS security has focused on the malicious potential of third-party applications, demonstrating how developers can bypass application vetting and code-level protections. In addition to these protections, iOS uses a generic sandbox profile called "container" to confine malicious or exploited third-party applications. In this paper, we present the first systematic analysis of the iOS container sandbox profile. We propose the SandScout framework to extract, decompile, formally model, and analyze iOS sandbox profiles as logic-based programs. We use our Prolog-based queries to evaluate file-based security properties of the container sandbox profile for iOS 9.0.2 and discover seven classes of exploitable vulnerabilities. These attacks affect non-jailbroken devices running later versions of iOS. We are working with Apple to resolve these attacks, and we expect that SandScout will play a significant role in the development of sandbox profiles for future versions of iOS.