Title : Precise and Scalable Detection of Double-Fetch Bugs in OS Kernels.

Speaker : Prof. Taesoo Kim ( Georgia Tech )
Date : 2018. 12. 18(Tue) 17:00 ~ 18:00
Location : #201, Woojung Building

Abstract :
During system call execution, it is common for operating system kernels to read userspace memory multiple times (multi-reads). A critical bug may exist if the fetched userspace memory is subject to change across these reads, i.e., a race condition, which is known as a double-fetch bug. Prior works have attempted to detect these bugs both statically and dynamically. However, due to their improper assumptions and imprecise definitions regarding double-fetch bugs, their multi-read detection is inherently limited and suffers from significant false positives and false negatives. For example, their approach is unable to support device emulation, inter-procedural analysis, loop handling, etc. More importantly, they completely leave the task of finding real double-fetch bugs from the haystack of multi-reads to manual verification, which is expensive if possible at all.

In this paper, we first present a formal and precise definition of double-fetch bugs and then implement a static analysis system - Deadline - to automatically detect double-fetch bugs in OS kernels. Deadline uses static program analysis techniques to systematically find multi-reads throughout the kernel and employs specialized symbolic checking to vet each multi-read for double-fetch bugs. We apply Deadline to Linux and FreeBSD kernels and find 23 new bugs in Linux and one new bug in FreeBSD. We further propose four generic strategies to patch and prevent double-fetch bugs based on our study and the discussion with kernel maintainers.

Precise and Scalable Detection of Double-Fetch Bugs in OS Kernels.
Meng Xu, Chenxiong Qian, Kangjie Lu, Michael Backes, and Taesoo Kim.
In Proceedings of the 39th IEEE Symposium on Security and Privacy (S&P 2018), San Francisco, CA, May 2018.

Bio :
Taesoo Kim is a Catherine M. and James E. Allchin Early Career, Assistant Professor in the School Computer Science at Georgia Tech. He also serves as the director of the Georgia Tech Systems Software and Security Center (GTS3). He is genuinely interested in building a system that has underline principles for why it should be secure. Those principles include the design of a system, analysis of its implementation, and clear separation of trusted components. His thesis work, in particular, focused on detecting and recovering from attacks on computer systems. He has developed tools that would detect intrusion and discover which parts of the operating system could have been affected, allowing a systems administrator to recover from an attack without excessive manual effort. His thesis work has been a foundation of a company, Nerati, where he has co-founded with colleagues during his graduate study. He holds a BS from KAIST (2009), a SM (2011) and a Ph.D. (2014) from MIT, all in CS.