题名 | SAEG: Stateful Automatic Exploit Generation |
作者 | |
通讯作者 | Zhang, Yinqian |
DOI | |
发表日期 | 2024
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会议名称 | 29th European Symposium on Research in Computer Security, ESORICS 2024
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ISSN | 0302-9743
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EISSN | 1611-3349
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ISBN | 9783031709029
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会议录名称 | |
卷号 | 14985 LNCS
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页码 | 127-145
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会议日期 | September 16, 2024 - September 20, 2024
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会议地点 | Bydgoszcz, Poland
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出版者 | |
摘要 | The field of Automatic Exploit Generation (AEG) plays a pivotal role in the assessment of software vulnerabilities, automating the analysis for exploit creation. Although AEG systems are instrumental in probing for vulnerabilities, they often lack the capability to contend with defense mechanisms such as vulnerability mitigation, which are commonly deployed in target environments. This shortfall presents significant challenges in exploitation. Additionally, most frameworks are tailored to specific vulnerabilities, rendering their extension a complex process that necessitates in-depth familiarity with their architectures. To overcome these limitations, we introduce the SAEG framework, which streamlines the repetitious aspects of existing exploit templates through a modular and extensible state machine that builds upon the concept of an Exploit Graph. SAEG can methodically filter out impractical exploitation paths by utilizing current information and the target program’s state. Additionally, it simplifies the integration of new information leakage methods with minimal overhead and handles multi-step exploitation procedures, including those requiring the leakage of sensitive data. We demonstrate a prototype of SAEG founded on symbolic execution that can simultaneously explore heap and stack vulnerabilities. This prototype can explore and combine leakage and exploitation effectively, generating complete exploits to obtain shell access for binary files across i386 and x86_64 architectures. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. |
学校署名 | 第一
; 通讯
|
语种 | 英语
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收录类别 | |
EI入藏号 | 20243917080485
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EI主题词 | Program debugging
|
EI分类号 | :1106.1
; :1106.2
|
来源库 | EV Compendex
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引用统计 | |
成果类型 | 会议论文 |
条目标识符 | http://sustech.caswiz.com/handle/2SGJ60CL/841067 |
专题 | 工学院_斯发基斯可信自主研究院 南方科技大学 工学院_计算机科学与工程系 |
作者单位 | Department of Computer Science and Engineering, Research Institute of Trustworthy Autonomous Systems, Southern University of Science and Technology, Shenzhen, China |
第一作者单位 | 斯发基斯可信自主系统研究院; 计算机科学与工程系 |
通讯作者单位 | 斯发基斯可信自主系统研究院; 计算机科学与工程系 |
第一作者的第一单位 | 斯发基斯可信自主系统研究院; 计算机科学与工程系 |
推荐引用方式 GB/T 7714 |
Wu, Yifan,Li, Yinshuai,Zhu, Hong,et al. SAEG: Stateful Automatic Exploit Generation[C]:Springer Science and Business Media Deutschland GmbH,2024:127-145.
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条目包含的文件 | 条目无相关文件。 |
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