Dynamic Mitigation Solution Based on eBPF Against Kernel Heap Vulnerabilities
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TP311

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    Abstract:

    Kernel heap vulnerability is currently one of the main threats to operating system security. User-space attackers can leak or modify sensitive kernel information, disrupt kernel control flow, and even gain root privilege by triggering a vulnerability. However, due to the rapid increase in the number and complexity of vulnerabilities, it often takes a long time from when a vulnerability is first reported to when the developer issues a patch, and kernel mitigation mechanisms currently adopted are usually steadily bypassed. Therefore, this study proposes an eBPF-based dynamic mitigation framework for kernel heap vulnerabilities, so as to reduce kernel security risks during the time window fixing. The framework adopts data object space randomization to assign random addresses to the data objects involved in vulnerability reports at each allocation. In addition, it takes full advantage of the dynamic and secure features of eBPF to inject space-randomized objects into the kernel during runtime, so the attacker cannot place any attack payload accurately, and the heap vulnerabilities are almost unexploitable. This study evaluates 40 real kernel heap vulnerabilities and collects 12 attacks that bypass the existing mitigation mechanisms for further analysis and tests. As a result, it verifies that the dynamic mitigation framework provides sufficient security. Performance tests show that even under severe conditions, the four types of data objects only cause performance loss of about 1% and negligible memory loss to the system, and there is almost no additional performance loss when the number of protected objects increases. Compared with related work, the mechanism in this study has a wider scope of application and stronger security, and it does not require vulnerability patches issued by security experts. Furthermore, it can generate mitigation procedures according to vulnerability reports and has a broad application prospect.

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王子成,郭迎港,钟炳南,陈越琦,曾庆凯.基于eBPF的内核堆漏洞动态缓解机制.软件学报,2024,35(7):3332-3354

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History
  • Received:September 05,2022
  • Revised:November 18,2022
  • Adopted:
  • Online: August 30,2023
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