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USENIX Security2022顶会

FreeWill: Automatically Diagnosing Use-after-free Bugs via Reference Miscounting Detection on Binaries

Liang He, Hong Hu, Purui Su, Yan Cai, Zhenkai Liang

出版方
2022年份
7顶会引用

摘要

Memory-safety issues in operating systems and popular applications are still top security threats. As one widely exploited vulnerability, Use After Free (UAF) resulted in hundreds of new incidents every year. Existing bug diagnosis techniques report the locations that allocate or deallocate the vulnerable object, but cannot provide sufficient information for developers to reason about a bug or synthesize a correct patch. In this work, we identified incorrect reference counting as one common root cause of UAF bugs: if the developer forgets to increase the counter for a newly created reference, the program may prematurely free the actively used object, rendering other references dangling pointers. We call this problem reference miscounting. By proposing an omissionaware counting model, we developed an automatic method, FREEWILL, to diagnose UAF bugs. FREEWILL first reproduces a UAF bug and collects related execution trace. Then, it identifies the UAF object and related references. Finally, FREEWILL compares reference operations with our model to detect reference miscounting. We evaluated FREEWILL on 76 real-world UAF bugs and it successfully confirmed reference miscounting as root causes for 48 bugs and dangling usage for 18 bugs. FREEWILL also identified five null-pointer dereference bugs and failed to analyze five bugs. FREEWILL can complete its analysis within 15 minutes on average, showing its practicality for diagnosing UAF bugs.

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