A vast amount of software, from low-level systems code to high-performance applications, is written in memory-unsafe languages such as C and C++. The lack of memory safety in C/C++ can lead to severe consequences; a simple buffer overflow can result in code or data corruption anywhere in the program memory. The problem is even worse in systems that constantly operate on inputs of unknown trustworthiness. For example, in 2021 a memory safety vulnerability was discovered in sudo, a near-ubiquitous utility available on major Unix-like operating systems. The vulnerability, which remained silent for over 10 years, allows any unprivileged user to gain root privileges on a victim machine using a default sudo configuration. As memory-safe languages are unlikely to displace C/C++ in the near future, efficient memory safety mechanisms for both existing and future C/C++ code are needed. Both industry and academia have proposed various techniques to address the C/C++ memory safety problem over the last three decades, either by software-only or hardware-assisted solutions. Software-only techniques such as Google’s AddressSanitizer are used to detect memory errors during the testing phase before products are shipped. While sanitizers have been shown to be effective at detecting memory errors with little effort, they typically suffer from high runtime overheads and increased memory footprint. Hardware-assisted solutions such as Oracle’s Application Data Integrity (ADI) and ARM’s Memory Tagging Extension (MTE) have much lower performance overheads, but they do not offer complete protection. Academic proposals manage to minimize the performance costs of memory safety defenses while maintaining fine-grained security protection. Unfortunately, state-of-the-art solutions require complex metadata that increases the program memory footprint, complicates the hardware design, and breaks compatibility with the rest of the system (e.g., unprotected libraries). To address these problems, the research within this thesis innovates in the realm of compiler transformations and hardware extensions to improve the state of the art in memory safety solutions. Specifically, this thesis shows that leveraging common software trends and rethinking computer microarchitectures can efficiently circumvent the problems of traditional memory safety solutions for C and C++. First, I present a novel cache line formatting technique, dubbed Califorms. Califorms builds on a concept called memory blocklisting, which prohibits a program from access- ing certain memory regions based on program semantics. State-of-the-art hardware-assisted memory blocklisting, while much faster than software blocklisting, creates memory fragmentation for each use of the blocklisted location. To prevent this issue, Califorms encodes the metadata, which is used to identify the blocklisted locations, in the blocklisted (i.e., dead) locations themselves. This inlined metadata can be then integrated into the microarchitecture by changing the cache line format. As a result, both the metadata and data are fetched together, eliminating the need for extra memory accesses. Hence, Califorms reduces the performance overheads of memory safety while providing byte-granular protection and maintaining very low hardware overheads. Secondly, I explore how leveraging common software trends can reduce the performance and memory costs of memory permitlisting (also known as base & bounds). Thus, I present No-FAT, a novel technique for enforcing spatial and temporal memory safety. The key observation that enables No-FAT is the increasing adoption of binning allocators. No-FAT, when used with a binning allocator, is able to implicitly derive an allocation’s bounds information (i.e., the base address and size) from the pointer itself without relying on expensive metadata. Moreover, as No-FAT’s memory instructions are aware of allocation bounds information, No-FAT effectively mitigates certain speculative attacks (e.g., Spectre-V1, which is also known as bounds checking bypass) with no additional cost. While No-FAT successfully detects memory safety violations, it falls short against physical attacks. Hence, I propose C-5, an architecture that complements No-FAT with strong data encryption. C-5 strictly uses access control in the L1 cache and encrypts program data at the L1-L2 cache interface. As a result, C-5 mitigates both in-process and physical attacks without burdening system performance. In addition to memory blocklisting and permitlisting, a cost-effective way to alleviate the memory safety threats is by deploying exploit mitigation techniques (e.g., Intel’s CET and ARM’s PAC). Unfortunately, current exploit mitigations offer incomplete security protection in order to save on performance. This thesis investigates potential opportunities to boost the security guarantees of exploit mitigations while maintaining their low overheads. Thus, I present ZeRØ, a hardware primitive that preserves pointer integrity at no performance cost, effectively mitigating pointer manipulation attacks such as ROP, COP, JOP, COOP, and DOP. ZeRØ proposes unique memory instructions and a novel metadata encoding scheme to protect code and data pointers from memory safety violations. The combination of instructions and metadata allows ZeRØ to avoid explicitly tagging every word in memory. On 64-bit systems, ZeRØ encodes the pointer type and location in the currently unused upper pointer bits. This way ZeRØ reduces the performance overheads of enforcing pointer integrity to zero while requiring simple hardware modifications. Finally, although current mitigation techniques excel at providing efficient protection for high-end devices, they typically suffer from significant performance and energy overheads when ported to the embedded domain. As a result, there is a need for developing new defenses that (1) have low overheads, (2) provide high security coverage, and (3) are especially designed for embedded devices. To achieve these goals I present EPI, an efficient pointer integrity mechanism that is tailored to microcontrollers and embedded devices. Similar to ZeRØ, EPI assigns unique tags to different program assets and uses unique memory instructions for accessing them. However, EPI uses a 32bit friendly encoding scheme to inline the tags within the program data. EPI introduces runtime overheads of less than 1%, making it viable for embedded and low-resource systems.