TRACER : signature-based static analysis for detecting recurring vulnerabilitiesTRACER: 반복되는 오류를 탐지하기 위한 시그니처 기반 정적 분석 시스템

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Similar software vulnerabilities recur because developers reuse existing vulnerable code, or make similar mistakes when implementing the same logic. Recently, various analysis techniques have been proposed to find syntactically recurring vulnerabilities via code reuse. However, limited attention has been devoted to semantically recurring ones that share the same vulnerable behavior in different code structures. In this paper, we present a general analysis framework, called TRACER, for detecting such recurring vulnerabilities. The main idea is to represent vulnerability signatures as traces over interprocedural data dependencies. TRACER is based on a taint analysis that can detect various types of vulnerabilities. For a given set of known vulnerabilities, the taint analysis extracts vulnerable traces and establishes a signature database of them. When a new unseen program is analyzed, TRACER compares all potentially vulnerable traces reported by the analysis with the known vulnerability signatures. Then, TRACER reports a list of potential vulnerabilities ranked by the similarity score. We evaluate TRACER on 273 Debian packages in C/C++. Our experiment results demonstrate that TRACER is able to find 112 previously unknown vulnerabilities with 6 CVE identifiers assigned.
Advisors
Heo, Kihongresearcher허기홍researcher
Description
한국과학기술원 :정보보호대학원,
Publisher
한국과학기술원
Issue Date
2023
Identifier
325007
Language
eng
Description

학위논문(석사) - 한국과학기술원 : 정보보호대학원, 2023.2,[iv, 35 p. :]

Keywords

software security▼aprogram analysis▼asoftware engineering; 소프트웨어 보안▼a프로그램 분석▼a소프트웨어 공학

URI
http://hdl.handle.net/10203/309632
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=1032990&flag=dissertation
Appears in Collection
IS-Theses_Master(석사논문)
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