Characterization of linux kernel behavior under errors

Gu, Weining; Kalbarczyk, Zbigniew; Ravishankar,; Iyer, K. B. Priya; Yang, Zhenyu

doi:10.1109/dsn.2003.1209956

Cited by 45 publications

(1 citation statement)

References 15 publications

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“…The collection and analysis of UaF exploits in the wild will be our future work. Lastly, another line of empirical study that is marginally related to ours is the fault tolerance and recovery of software in face of triggered errors and bugs [56,104]. In summary, while there have been a bunch of existing empirical studies on software bugs, none of them have focused on UaF.…”

Section: Related Workmentioning

confidence: 87%

All Use-After-Free Vulnerabilities Are Not Created Equal: An Empirical Study on Their Characteristics and Detectability

Chen,

Liu,

Xiao

et al. 2023

Proceedings of the 26th International Symposium on Research in Attacks, Intrusions and Defenses

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Over the past decade, use-after-free (UaF) has become one of the most exploited types of vulnerabilities. To address this increasing threat, we need to advance the defense in multiple directions, such as UaF vulnerability detection, UaF exploit defense, and UaF bug fix. Unfortunately, the intricacy rooted in the temporal nature of UaF vulnerabilities makes it quite challenging to develop effective and efficient defenses in these directions. This calls for an in-depth understanding of real-world UaF characteristics. This paper presents the first comprehensive empirical study of UaF vulnerabilities, with 150 cases randomly sampled from multiple representative software suites, such as Linux kernel, Python, and Mozilla Firefox. We aim to identify the commonalities, root causes, and patterns from realworld UaF bugs, so that the empirical results can provide operational guidance to avoid, detect, deter, and fix UaF vulnerabilities. Our main finding is that the root causes of UaF bugs are diverse, and they are not evenly or equally distributed among different software. This implies that a generic UaF detector/fuzzer is probably not an optimal solution. We further categorize the root causes into 11 patterns, several of which can be translated into simple static detection rules to cover a large portion of the 150 UaF vulnerabilities with high accuracy. Motivated by our findings, we implement 11 checkers in a static bug detector called Palfrey. Running Palfrey on the code of popular open source software, we detect 9 new UaF vulnerabilities. Compared with state-of-the-art static bug detectors, Palfrey outperforms in coverage and accuracy for UaF detection, as well as time and memory overhead. CCS CONCEPTS• Security and privacy → System security; Bug-finding, debugging.

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Section: Related Workmentioning

confidence: 87%

All Use-After-Free Vulnerabilities Are Not Created Equal: An Empirical Study on Their Characteristics and Detectability

Chen,

Liu,

Xiao

et al. 2023

Proceedings of the 26th International Symposium on Research in Attacks, Intrusions and Defenses

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Benchmarking the Impact of Faulty Drivers: Application to the Linux Kernel

Kanoun

Spainhower

2008

Dependability Benchmarking for Computer Systems

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Dependability concerns, encompassing robustness assessment, are essential questions to answer before a developer can make the decision whether to integrate off-the-shelf (OTS) components into a dependable system. Here, and in what follows, robustness is understood as the degree to which a system operates correctly in the presence of exceptional inputs or stressful environmental conditions, in compliance with the generic definition (dependability with respect to external faults) given in [Aviz ienis et al. 2004].From a cost-effectiveness viewpoint, operating systems and kernels are privileged OTS components as candidates for integration into a system. However, integrators are often reluctant to make such a move without obtaining a deeper knowledge and understanding about such a component beyond functional issues, in particular with respect to its failure modes and its behavior in the presence of faults. Due to the opacity that is often attached to the commercial offer and to the difficulty and significant cost associated with the availability of the source code, the Open Source option, for which access to the source code is granted, is progressively making its way as an attractive and promising alternative. Also, results of many studies have shown that Open Source solutions did not exhibit significantly more critical failure modes and in some cases they were even found to demonstrate behaviors superior to commercial options [Koopman and DeVale 1999, Marsden et al. 2002, Vieira & Madeira 2003; see also Chapter 5 for the latter. In this chapter, we will simply denote such components (either commercial or Open Source) as OTS components.In the past years, several experimental studies have addressed this important issue from different perspectives [Koopman and DeVale 1999 (see also Chapter 11), . This has also led to the proposal of tentative dependability benchmarking approaches, aimed at characterizing the robustness of computer systems Dependability Benchmarking for Computer Systems.

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Bad Memory Blocks Exclusion in Linux Operating System

Surmacz

Zawistowski

2011

Advances in Intelligent and Soft Computing

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Characterization of linux kernel behavior under errors

Cited by 45 publications

References 15 publications

All Use-After-Free Vulnerabilities Are Not Created Equal: An Empirical Study on Their Characteristics and Detectability

All Use-After-Free Vulnerabilities Are Not Created Equal: An Empirical Study on Their Characteristics and Detectability

Benchmarking the Impact of Faulty Drivers: Application to the Linux Kernel

Bad Memory Blocks Exclusion in Linux Operating System

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