Hybrid Information Flow Analysis for Python Bytecode
Zhifei Chen, Lin Chen, Baowen Xu · 2014
Python is widely used to create and manage complex, database-driven websites. However, due to dynamic features such as dynamic typing of variables, Python programs pose a serious security risk to web applications. Most security vulnerabilities result from the fact that unsafe data input reaches security-sensitive operations. To address this problem, information flow analysis for Python programs is proposed to enforce this property. Information flow can capture the fact that a particular value affects another value in the program. In this paper, we present a novel approach for analyzing information flow in Python byte code which is a low-level language and is more widely broadcast. Our approach performs a hybrid of static and dynamic control/data flow analysis. Static analysis is used to study implicit flow, while dynamic analysis efficiently tracks execution information and determines definition-use pair. To the best of our knowledge, it is the first one for Python byte code.