Exaggerated Error Handling Hurts! An In-Depth Study and Context-Aware Detection

Aditya Pakki, Kangjie Lu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Scopus citations

Abstract

Operating system (OS) kernels frequently encounter various errors due to invalid internal states or external inputs. To ensure the security and reliability of OS kernels, developers propose a diverse set of mechanisms to conservatively capture and handle potential errors. Existing research has thus primarily focused on the completeness and adequacy of error handling to not miss the attention. However, we find that handling an error with an over-severe level (e.g., unnecessarily terminating the execution) instead hurts the security and reliability. In this case, the error-handling consequences are even worse than the error it attempts to resolve. We call such a case Exaggerated Error Handling (EEH). The security impacts of EEH bugs vary, including denial-of-service, data losses, broken control-flow integrity, memory leaks, etc. Despite its significance, detecting EEH remains an unexplored topic. In this paper, we first conduct an in-depth study on EEH. Based on the findings of the study, we then propose an approach, EeCatch, to detect EEH bugs in a context-aware manner. EeCatch accurately identifies errors and extracts their contexts (both spatial and temporal), and automatically infers the appropriate severity level for error handling. Using the inferred severity level, EeCatch finally detects EEH bugs in which the used error handling exceeds the inferred severity level. By analyzing the whole Linux kernel, EeCatch reports hundreds of potential EEH bugs that may cause security issues such as crashing the system. After evaluating 104 cases reported by EeCatch, we manually confirmed 64 EEH bugs and submitted patches for all of them. Using our patches, Linux maintainers have fixed 48 reported EEH bugs, confirming the effectiveness of EeCatch. To the best of our knowledge, we are the first to systematically study and detect EEH bugs. We hope the findings could raise the awareness of the critical consequences of EEH bugs to help developers avoid them.

Original languageEnglish (US)
Title of host publicationCCS 2020 - Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security
PublisherAssociation for Computing Machinery
Pages1203-1218
Number of pages16
ISBN (Electronic)9781450370899
DOIs
StatePublished - Oct 30 2020
Event27th ACM SIGSAC Conference on Computer and Communications Security, CCS 2020 - Virtual, Online, United States
Duration: Nov 9 2020Nov 13 2020

Publication series

NameProceedings of the ACM Conference on Computer and Communications Security
ISSN (Print)1543-7221

Conference

Conference27th ACM SIGSAC Conference on Computer and Communications Security, CCS 2020
Country/TerritoryUnited States
CityVirtual, Online
Period11/9/2011/13/20

Bibliographical note

Funding Information:
We thank our shepherd, Herbert Bos, and the anonymous reviewers for their helpful suggestions and comments. We are grateful to Linux maintainers for providing prompt feedback on patching bugs. This research was supported in part by the NSF awards CNS-1815621 and CNS-1931208. Any opinions, findings, conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of NSF.

Publisher Copyright:
© 2020 ACM.

Keywords

  • bug detection
  • exaggerated error handling
  • os kernel bug
  • static analysis

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