Biblio

Increased peripheral performance is causing strain on the memory subsystem of modern processors. For example, available DRAM throughput can no longer sustain the traffic of a modern network card. Scrambling to deliver the promised performance, instead of transferring peripheral data to and from DRAM, modern Intel processors perform I/O operations directly on the Last Level Cache (LLC). While Direct Cache Access (DCA) instead of Direct Memory Access (DMA) is a sensible performance optimization, it is unfortunately implemented without care for security, as the LLC is now shared between the CPU and all the attached devices, including the network card.In this paper, we reverse engineer the behavior of DCA, widely referred to as Data-Direct I/O (DDIO), on recent Intel processors and present its first security analysis. Based on our analysis, we present NetCAT, the first Network-based PRIME+PROBE Cache Attack on the processor's LLC of a remote machine. We show that NetCAT not only enables attacks in cooperative settings where an attacker can build a covert channel between a network client and a sandboxed server process (without network), but more worryingly, in general adversarial settings. In such settings, NetCAT can enable disclosure of network timing-based sensitive information. As an example, we show a keystroke timing attack on a victim SSH connection belonging to another client on the target server. Our results should caution processor vendors against unsupervised sharing of (additional) microarchitectural components with peripherals exposed to malicious input.

In 2007, Shacham published a seminal paper on Return-Oriented Programming (ROP), the first systematic formulation of code reuse. The paper has been highly influential, profoundly shaping the way we still think about code reuse today: an attacker analyzes the "geometry" of victim binary code to locate gadgets and chains these to craft an exploit. This model has spurred much research, with a rapid progression of increasingly sophisticated code reuse attacks and defenses over time. After ten years, the common perception is that state-of-the-art code reuse defenses are effective in significantly raising the bar and making attacks exceedingly hard. In this paper, we challenge this perception and show that an attacker going beyond "geometry" (static analysis) and considering the "dynamics" (dynamic analysis) of a victim program can easily find function call gadgets even in the presence of state-of-the-art code-reuse defenses. To support our claims, we present Newton, a run-time gadget-discovery framework based on constraint-driven dynamic taint analysis. Newton can model a broad range of defenses by mapping their properties into simple, stackable, reusable constraints, and automatically generate gadgets that comply with these constraints. Using Newton, we systematically map and compare state-of-the-art defenses, demonstrating that even simple interactions with popular server programs are adequate for finding gadgets for all state-of-the-art code-reuse defenses. We conclude with an nginx case study, which shows that a Newton-enabled attacker can craft attacks which comply with the restrictions of advanced defenses, such as CPI and context-sensitive CFI.