The growing dependence on software and the increasing complexity of such systems builds and feeds the attack surface for exploitable vulnerabilities. Security researchers put up a lot of effort to develop exploits and analyze existing exploits with the goal of staying ahead of the state-of-the-art in attacks and defenses. The urge for automated systems that operate at scale, speed and efficiency is therefore undeniable. Given their complexity and large user base, web browsers pose an attractive target. Due to various mitigation strategies, the exploitation of a browser vulnerability became a time consuming, multi-step task: creating a working exploit even from a crashing input is a resource-intensive task that can take a substantial amount of time to complete. In many cases, the input, which triggers a vulnerability follows a crashing path but does not enter an exploitable state.

With the general availability of closed-source software for various CPU architectures, there is a need to identify security-critical vulnerabilities at the binary level to perform a vulnerability assessment. Unfortunately, existing bug finding methods fall short in that they i) require source code, ii) only work on a single architecture (typically x86), or iii) rely on dynamic analysis, which is inherently difficult for embedded devices. In this paper, we propose a system to derive bug signatures for known bugs. We then use these signatures to find bugs in binaries that have been deployed on different CPU architectures (e.g., x86 vs. MIPS). The variety of CPU architectures imposes many challenges, such as the incomparability of instruction set architectures between the CPU models. We solve this by first translating the binary code to an intermediate representation, resulting in assignment formulas with input and output variables. We then sample concrete inputs to observe the I/O behavior of basic blocks, which grasps their semantics. Finally, we use the I/O behavior to find code parts that behave similarly to the bug signature, effectively revealing code parts that contain the bug. We have designed and implemented a tool for cross architecture bug search in executables. Our prototype currently supports three instruction set architectures (x86, ARM, and MIPS) and can find vulnerabilities in buggy binary code for any of these architectures. We show that we can find Heart bleed vulnerabilities, regardless of the underlying software instruction set. Similarly, we apply our method to find backdoors in closed source firmware images of MIPS- and ARM-based routers.

Cold boot attacks exploit the fact that data in RAM gradually fades away over time, rather than being lost immediately when power is cycled off. An attacker can gain access to all memory contents by a restart or short power-down of the system, a so called cold boot. Consequently, sensitive data in RAM like cryptographic keys are exposed to attackers with physical access. Research in recent years found software-based solutions to the cold boot problem in terms of CPU-bound or memory-less encryption. To date, however, the focus has been set on symmetric ciphers, particularly concerning disk encryption systems. Contrary to that, the work in hand aims to close the gap to asymmetric ciphers. With PRIME, we present a cold boot resistant infrastructure for private RSA operations. All private RSA parameters reside symmetrically encrypted in RAM and are decrypted only within CPU registers. The modular exponentiation algorithm for RSA is implemented entirely on the CPU, such that no sensitive state of RSA ever goes to RAM.