Poirot: Probabilistically Recommending Protections for the Android Framework
Zeinab El-Rewini, Zhuo Zhang, Yousra Aafer
Abstract
Inconsistent security policy enforcement within the Android framework can allow malicious actors to improperly access sensitive resources. A number of prominent inconsistency detection approaches have been proposed in and across various layers of the Android operating system. However, the existing approaches suffer from high false positive rates as they rely solely on simplistic convergence analysis and reachability based relations to reason about the validity of access control enforcement. We observe that resource-to-access control associations are highly uncertain in the context of Android. Thus, we introduce Poirot, a next-generation inconsistency detection tool that leverages probabilistic inference to generate a comprehensive set of protection recommendations for Android framework APIs. We evaluate Poirot on four Android images and detect 26 total inconsistencies.
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