Amazon Technologies, Inc.

University of Southern California

Yingjun Lyu

Omer Tripp

Qiang Zhou

Michael Wilson

Lee Pike

Rajdeep Mukherjee

Nenad Medvidovic

Yixue Zhao

Marcelo Schmitt Laser

Peixuan Li

Thodoris Sotiropoulos

Michael McDougall

Security vulnerability analysis may be performed using policy inference. Application code may have operations that are labeled according to the respective functions that they perform. Some operations may be labeled according to a knowledge database of known operations while others may be inferred through similarity to known operations. The knowledge database may be associated with libraries of programmatic interfaces. Once components of the application code are labeled, a vulnerability database may be that identifies potential vulnerabilities based on data sources, data sinks and threat mitigation operations. Using the labeled operations, one or more potential vulnerabilities may be identified based on labeled data sources and data sinks. The application may then be evaluated for potential security threats based on the identified potential vulnerabilities.

Knowledge-based taint policy inference

Techniques for program verification are described. An exemplary method includes receiving a request to evaluate code based on a customized rule, the customized rule comprising one or more conditions for which the customized rule is applicable and one or more postconditions to indicate at least one check to perform for a given node in a graph for the code, wherein an application of the customized rule performs one or more of: an interleave between a backward analysis and forward analysis based on user-specified conditions, an analysis between sub-graphs by a query from a first sub-graph to a second sub-graph, and an operation on a sub-graph, storage of a result of the operation on the sub-graph, and usage of the stored result in a subsequent operation; generating a graph for the code; and evaluating the code by applying the customized rule to the generated graph.

Data flow tracking in program verification

Systems and methods for reducing latency in use of mobile applications include creating a list of potential internet requests from a mobile application based on an analysis of the mobile application. The systems and methods include creating a trigger map that maps each of a plurality of trigger points of the mobile application with a corresponding target internet request to be prefetched from the list of potential internet requests. The systems and methods include creating a URL map that maps each of a plurality of the potential internet requests with corresponding URL values. The systems and methods include identifying that a current app function matches a trigger point of the plurality of trigger points. The systems and methods include performing the potential internet request in response to identifying that the current app function matches the trigger point prior to the target request being received in order to reduce latency.

Latency minimization in mobile applications

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Los Angeles, CA, United States of America

Yingjun Lyu