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April 17, 2026International Journal of Software Engineering and Knowledge Engineering0 citations

SyzCrash: Crash-Context-Guided Directed Fuzzing for Exploitability Risk Assessment of Linux Kernel Bugs

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BLBingzheng LiXYXiaokang YinSLShengli Liu

Key Points

  • Evaluate a new framework, SyzCrash, for assessing the exploitability risk of Linux kernel vulnerabilities.
  • Introduced a directed fuzzing framework utilizing post-crash traces.
  • Employed a loadable kernel module with a panic_notifier hook for capturing crash data.
  • Combined context similarity feedback with a two-phase mutation strategy for effective risk assessment.
  • Achieved a 72.22 percent escalation success rate in bug risk enhancement.
  • Outperformed existing methods in terms of speed and efficacy.
  • Successfully uncovered hidden security risks in a benchmark of 108 real-world Linux kernel bugs.

Abstract

The surge in Linux kernel vulnerabilities poses a significant challenge for security analysts, as the scale of bug reports far outstrips manual patching capacity. Assessing the exploitability risk of Linux kernel bugs is vital for prioritizing bug repair efforts, yet the first discovered crash report provides a limited view of the bug’s exploitability risk, potentially underestimating its true security impact. We introduce SyzCrash, a directed fuzzing framework that utilizes post-crash traces to guide the exploitability risk escalation in the Linux kernel. To mitigate kernel panic instability, SyzCrash employs a loadable kernel module with panicₙotifier hook to capture post-crash kCOV and ftrace data. By combining context similarity feedback with a two-phase mutation strategy, the framework preserves the original crash context while systematically exploring proximate execution paths. Evaluation on a benchmark of 108 real-world Linux kernel bugs shows that SyzCrash achieves a 72. 22 percent escalation success rate in bug risk escalation, outperforming state-of-the-art approaches in both efficacy and speed. These results highlight its capability to systematically uncover hidden security risks and assist developers in bug prioritization and patching.

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Cite This Study

Li et al. (2026) studied this question.

synapsesocial.com/papers/69e1cf1b5cdc762e9d858126https://doi.org/10.1142/s0218194026500336
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