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UAFSan: an object-identifier-based dynamic approach for detecting use-after-free vulnerabilities

Binfa Gui, Wei Song, Jeff Huang

2021Year
9Citations
4Top-tier citations

Abstract

Use-After-Free (UAF) vulnerabilities constitute severe threats to software security. In contrast to other memory errors, UAFs are more difficult to detect through manual or static analysis due to pointer aliases and complicated relationships between pointers and objects. Existing evidence-based dynamic detection approaches only track either pointers or objects to record the availability of objects, which become invalid when the memory that stored the freed object is reallocated. To this end, we propose an approach UAFSan dedicated to comprehensively detecting UAFs at runtime. Specifically, we assign a unique identifier to each newly-allocated object and its pointers; when a pointer dereferences a memory object, we determine whether a UAF occurs by checking the consistency of their identifiers. We implement UAFSan in an open-source tool and evaluate it on a large collection of popular benchmarks and real-world programs. The experiment results demonstrate that UAFSan successfully detect all UAFs with reasonable overhead, whereas existing publicly-available dynamic detectors all miss certain UAFs.

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