Abstract
Static taint analysis can be used to find various security weaknesses and vulnerabilities in programs by discovering dataflow paths from taint sources to taint sinks. In most cases the data is called ”tainted” if it was obtained from an untrusted source without proper sanitization. In this paper we present a static taint analyzer Irbis. It implements analysis based on IFDS (Interprocedural Finite Distributive Subset) dataflow problem, as well as various extensions aimed at improving accuracy and completeness of the analysis. It supports different definitions of tainted data, which enables it to find such weaknesses as out of buffer access, use of freed memory, hardcoded passwords, data leaks and discover dataflow paths between user-defined sources and sinks. All sources, sinks and propagators definitions are stored in JSON format and can be adjusted to meet the users’ needs. We compare analysis results on Juliet Test Suite for C/C++ with several other analyzers, such as Infer, Clang Static Analyzer and Svace. Irbis manages to demonstrate 100% coverage on taint-related subset of tests for implemented CWEs, while suppressing all the false positives using heuristics. We also show performance and false positive rate on real projects, with examples of real vulnerabilities, which can be detected by Irbis.
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