Low-level languages, which require manual memory management from the programmer, remain in wide use for performance-critical applications. Memory-safety bugs are common, and now a major source of exploits. In particular, a use-after-free bug occurs when an object is erroneously deallocated, whilst pointers to it remain active in memory, and those (dangling) pointers are later used to access the object. An attacker can reallocate the memory area backing an erroneously freed object, then overwrite its contents, injecting carefully chosen data into the host program, thus altering its execution and achieving privilege escalation.We present MineSweeper, a system to mitigate use-after-free vulnerabilities by retaining freed allocations in a quarantine, until no pointers to them remain in program memory, thus preventing their reallocation until it is safe. MineSweeper performs efficient linear sweeps of memory to identify quarantined items that have no dangling pointers to them, and thus can be safely reallocated. This allows MineSweeper to be significantly more efficient than previous transitive marking procedure techniques.MineSweeper, attached to JeMalloc, improves security at an acceptable overhead in memory footprint (11.1% on average) and an execution-time cost of only 5.4% (geometric mean for SPEC CPU2006), with 9.6% additional threaded CPU usage. These figures considerably improve on the state-of-the-art for non-probabilistic drop-in temporal-safety systems, and make MineSweeper the only such scheme suitable for deployment in real-world production environments. CCS CONCEPTS• Security and privacy → Software and application security; Systems security.

We present a uni ed approach for exploiting thread-level, data-level, and memory-level parallelism through a same-ISA dynamic binary modi er guided by static binary analysis. A static binary analyser rst examines an executable and determines the operations required to extract parallelism at runtime, encoding them as a series of rewrite rules that a dynamic binary modi er uses to perform binary transformation. We demonstrate this framework by exploiting three di erent kinds of parallelism to perform automatic vectorisation, software prefetching, and automatic parallelisation together on legacy application binaries. Software prefetch insertion alone achieves an average speedup of 1.2×, comparing favourably with an automatic compiler pass. Automatic vectorisation brings speedups of 2.7× on the TSVC benchmarks, signi cantly beating a compiler approach for some workloads. Finally, combining prefetching, vectorisation, and parallelisation realises a speedup of 3.8× on a representative application loop.