NDSS

PyPANDA: Taming the PANDAmonium of Whole System Dynamic Analysis

Luke Craig, Tim Leek (MIT Lincoln Laboratory), Andrew Fasano, Tiemoko Ballo (MIT Lincoln Laboratory, Northeastern University), Brendan Dolan-Gavitt (New York University), William Robertson (Northeastern University)

When working with real world programs, dynamic analyses often must be run on a whole-system instead of just a single binary. Existing whole-system dynamic analysis platforms generally require analyses to be written in compiled languages, a suboptimal choice for many iterative analysis tasks. Furthermore, these platforms leave analysts with a split view between the behavior of the system under analysis and the analysis itself—in particular the system being analyzed must commonly be controlled manually while analysis scripts are run. To improve this process, we designed and implemented PyPANDA, a Python interface to the PANDA dynamic analysis platform. PyPANDA unifies the gap between guest virtual machines behavior and analysis tasks; enables painless integrations with other program analysis tools; and greatly lowers the barrier of entry to whole-system dynamic analysis. The capabilities of PyPANDA are demonstrated by using it to dynamically evaluate the accuracy of three binary analysis frameworks, track heap allocations across multiple processes, and synchronize state between PANDA and a binary analysis platform. Significant challenges were overcome to integrate a scripting language into PANDA with minimal performance impact.