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SDLI: Static Detection of Leaks Across Intents

机译:SDLI:静态检测跨意图泄漏

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Intents are Android's intra and inter-application communication mechanism. They specify an action to perform, with extra data, and are sent to a receiver component or broadcast to many components. Components, in the same or in a distinct app, receive the intent if they are available to perform the desired action. Hence, a sound static analyzer must be aware of information flows through intents. That can be achieved by considering intents as both source (when reading) and sink (when writing) of confidential data. But this is overly conservative if the intent stays inside the same app or if the set of apps installed on the device is known in advance. In such cases, a sound approximation of the flow of intents leads to a more precise analysis. This work describes SDLI, a novel static analyzer that, for each app, creates an XML summary file reporting a description of the tainted information in outwards intents and of the intents the app is available to serve. SDLI discovers confidential information leaks when two apps communicate, by matching their XML summaries, looking for tainted outwards intents of the first app that can be inwards intents of the second app. The tool is implemented inside Julia, an industrial static analyzer. On the DroidBench testcases, its shows a precision higher than 75%. On some popular apps from the Google Play marketplace, it spots inter-apps leaks of confidential data, hence showing its practical effectiveness.
机译:意图是Android的应用程序内部和应用程序之间的通信机制。它们使用额外的数据指定要执行的动作,并发送到接收器组件或广播到许多组件。如果组件可用于执行所需的操作,则组件在相同或不同的应用程序中会收到意图。因此,声音静态分析器必须知道通过意图传递的信息。可以通过将意图同时作为机密数据的来源(读取时)和接收者(写入时)来实现。但是,如果意图停留在同一应用程序内,或者如果事先知道设备上安装的应用程序集,则这过于保守。在这种情况下,意图流的合理逼近可导致更精确的分析。这项工作描述了SDLI,这是一种新颖的静态分析器,它为每个应用程序创建一个XML摘要文件,该文件以向外的意图报告该污染信息的描述,并描述该应用程序可服务的意图。当两个应用程序通信时,SDLI通过匹配它们的XML摘要,查找第一个应用程序的受污染的外向意图(可能是第二个应用程序的向内的意图)来发现机密信息泄漏。该工具在工业静态分析器Julia内部实现。在DroidBench测试用例中,其显示的精度高于75%。在Google Play市场上一些流行的应用程序上,它可以发现应用程序间的机密数据泄漏,从而显示出其实用性。

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