We present sandbox mining, a technique to confine an application to resources accessed during automatic testing. Sandbox mining first explores software behavior by means of automatic test generation, and extracts the set of resources accessed during these tests. This set is then used as a sandbox, blocking access to resources not used during testing. The mined sandbox thus protects against behavior changes such as the activation of latent malware, infections, targeted attacks, or malicious updates.

Dynamic symbolic execution (DSE) can efficiently explore all simple paths through a program, reliably determining whether there are any program crashes or violations of assertions or code contracts. However, if such automated oracles do not exist, the traditional approach is to present the developer a small and representative set of tests in order to let him/her determine their correctness. Customer feedback on Microsoft's Pex tool revealed that users expect different values and also more values than those produced by Pex, which threatens the applicability of DSE in a scenario without automated oracles. Indeed, even though all paths might be covered by DSE, the resulting tests are usually not sensitive enough to make a good regression test suite. In this paper, we present augmented dynamic symbolic execution, which aims to produce representative test sets by augmenting path conditions with additional conditions that enforce target criteria such as boundary or mutation adequacy, or logical coverage criteria.