PartiSan: Fast and Flexible Sanitization via Run-time Partitioning
This addresses the problem of limited public release of sanitized builds due to performance constraints, offering a more practical solution for developers and users, though it is incremental in improving existing sanitization methods.
The paper tackles the high overhead of sanitizers in C/C++ code by introducing PartiSan, a run-time partitioning technique that allows flexible and faster sanitization, reducing performance impact by dynamically adjusting sanitized slices.
Sanitizers can detect security vulnerabilities in C/C++ code that elude static analysis. Current practice is to continuously fuzz and sanitize internal pre-release builds. Sanitization-enabled builds are rarely released publicly. This is in large part due to the high memory and processing requirements of sanitizers. We present PartiSan, a run-time partitioning technique that speeds up sanitizers and allows them to be used in a more flexible manner. Our core idea is to partition the execution into sanitized slices that incur a run-time overhead, and unsanitized slices running at full speed. With PartiSan, sanitization is no longer an all-or-nothing proposition. A single build can be distributed to every user regardless of their willingness to enable sanitization and the capabilities of their host system. PartiSan can automatically adjust the amount of sanitization to fit within a performance budget or disable sanitization if the host lacks sufficient resources. The flexibility afforded by run-time partitioning also means that we can alternate between different types of sanitizers dynamically; today, developers have to pick a single type of sanitizer ahead of time. Finally, we show that run-time partitioning can speed up fuzzing by running the sanitized partition only when the fuzzer discovers an input that causes a crash or uncovers new execution paths.