An Architecture for Exploiting Native User-Land Checkpoint-Restart to Improve Fuzzing
This addresses a bottleneck in software security testing for developers and researchers by reducing startup overhead and enabling more efficient vulnerability discovery.
The paper tackles the inefficiency of fuzzing due to time spent restarting crashed applications and the difficulty of fuzzing from deeper execution points, proposing a novel architecture that uses native checkpoint-restart to attach fuzzers after program start, improving throughput and enabling new testing strategies.
Fuzzing is one of the most popular and widely used techniques to find vulnerabilities in any application. Fuzzers are fast enough, but they still spend a good portion of time to restart a crashed application and then fuzz it from the beginning. Fuzzing an application from a point deeper in the execution is also important. To do this, a user needs to take a snapshot of the program while fuzzing it on top of an emulator, virtual machine, or by utilizing a special kernel module to enable checkpointing. Even with this ability, it can be difficult to attach a fuzzer after restoring a checkpoint. As a result, most fuzzers leverage a form of fork-server design. We propose a novel testing architecture that allows users to attach a fuzzer after the program has started running. We do this by natively checkpointing the target application at a point of interest, and attaching the fuzzer after restoring the checkpoint. A fork-server may even be engaged at the point of restoration. This not only improves the throughput of the fuzzing campaign by minimizing startup time, but opens up a new way to fuzz applications. With this architecture, a user can take a series of checkpoints at points of interest, and run parallel tests to reduce the overall state-complexity of an individual test. Checkpoints allow us to begin fuzzing from a deeper point in the execution path, omitting prior execution from the required coverage path. This and other checkpointing techniques are described in the paper to help improve fuzzing.