We propose, BanditRepair, a system that systematically explores and assesses a set of possible runtime patches. The system is grounded on so-called bandit algorithms, that are online machine learning algorithms, designed for constantly balancing exploitation and exploration. BanditRepair's runtime patches are based on modifying the execution state for repairing null dereferences. BanditRepair constantly trades the ratio of automatically handled failures for searching for new runtime patches and vice versa. We evaluate the system with 16 null dereference field bugs, where BanditRepair identifies a total of 8460 different runtime patches, which are composed of 1 up to 8 decisions (execution modifications) taken in a row. We are the first to finely characterize the search space and the outcomes of runtime repair based on execution modification.
@cite_17 presents a technique to avoid illegal memory accesses by adding additional code around each memory operation during the compilation process. For example, the additional code verifies at runtime that the program only uses the allocated memory. If the memory access is outside the allocated memory, the access is ignored instead crashing with a segmentation fault. The two differences between this work and are: first can apply different decisions to handle a given failure (and not a single code, hard-coded in the injected code), and second, uses an oracle to reason about the viability of the decision.
@cite_17
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We present a new technique, failure-oblivious computing, that enables servers to execute through memory errors without memory corruption. Our safe compiler for C inserts checks that dynamically detect invalid memory accesses. Instead of terminating or throwing an exception, the generated code simply discards invalid writes and manufactures values to return for invalid reads, enabling the server to continue its normal execution path. We have applied failure-oblivious computing to a set of widely-used servers from the Linux-based open-source computing environment. Our results show that our techniques 1) make these servers invulnerable to known security attacks that exploit memory errors, and 2) enable the servers to continue to operate successfully to service legitimate requests and satisfy the needs of their users even after attacks trigger their memory errors. We observed several reasons for this successful continued execution. When the memory errors occur in irrelevant computations, failure-oblivious computing enables the server to execute through the memory errors to continue on to execute the relevant computation. Even when the memory errors occur in relevant computations, failure-oblivious computing converts requests that trigger unanticipated and dangerous execution paths into anticipated invalid inputs, which the error-handling logic in the server rejects. Because servers tend to have small error propagation distances (localized errors in the computation for one request tend to have little or no effect on the computations for subsequent requests), redirecting reads that would otherwise cause addressing errors and discarding writes that would otherwise corrupt critical data structures (such as the call stack) localizes the effect of the memory errors, prevents addressing exceptions from terminating the computation, and enables the server to continue on to successfully process subsequent requests. The overall result is a substantial extension of the range of requests that the server can successfully process.