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Heaps'n Leaks: How Heap Snapshots Improve Android Taint Analysis

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2021

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Gesellschaft für Informatik e.V.

Zusammenfassung

The assessment of information flows is an essential part of analyzing Android apps, and is frequently supported by static taint analysis. Its precision, however, can suffer from the analysis not being able to precisely determine what elements a pointer can (and cannot) point to. Recent advances in static analysis suggest that incorporating dynamic heap snapshots, taken at one point at runtime, can significantly improve general static analysis. In this paper, we investigate to what extent this also holds for taint analysis, and how various design decisions, such as when and how many snapshots are collected during execution, and how exactly they are used, impact soundness and precision. We have extended FlowDroid to incorporate heap snapshots, yielding our prototype Heapster, and evaluated it on DroidMacroBench, a novel benchmark comprising real-world Android apps that we also make available as an artifact. The results show (1) the use of heap snapshots lowers analysis time and memory consumption while increasing precision; (2) a very good trade-off between precision and recall is achieved by a mixed mode in which the analysis falls back to static points-to relations for objects for which no dynamic data was recorded; and (3) while a single heap snapshot (ideally taken at the end of the execution) suffices to improve performance and precision, a better trade-off can be obtained by using multiple snapshots.

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Benz, Manuel; Kristensen, Erik Krogh; Luo, Linghui; Borges Jr., Nataniel P.; Bodden, Eric; Zeller, Andreas (2021): Heaps'n Leaks: How Heap Snapshots Improve Android Taint Analysis. Software Engineering 2021. DOI: 10.18420/SE2021_02. Bonn: Gesellschaft für Informatik e.V.. PISSN: 1617-5468. ISBN: 978-3-88579-704-3. pp. 23-26. Braunschweig/Virtuell. 22.-26. Februar 2021

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