Divide and Conquer based Symbolic Vulnerability Detection

Fuente: arXiv
Guardado en:
Detalles Bibliográficos
Autores principales: Scherb, Christopher, Heitz, Luc Bryan, Grieder, Hermann
Formato: Preprint
Publicado: 2024
Materias:
Acceso en línea:
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
_version_ 1866914057674555392
author Scherb, Christopher
Heitz, Luc Bryan
Grieder, Hermann
author_facet Scherb, Christopher
Heitz, Luc Bryan
Grieder, Hermann
contents In modern software development, vulnerability detection is crucial due to the inevitability of bugs and vulnerabilities in complex software systems. Effective detection and elimination of these vulnerabilities during the testing phase are essential. Current methods, such as fuzzing, are widely used for this purpose. While fuzzing is efficient in identifying a broad range of bugs and vulnerabilities by using random mutations or generations, it does not guarantee correctness or absence of vulnerabilities. Therefore, non-random methods are preferable for ensuring the safety and security of critical infrastructure and control systems. This paper presents a vulnerability detection approach based on symbolic execution and control flow graph analysis to identify various types of software weaknesses. Our approach employs a divide-and-conquer algorithm to eliminate irrelevant program information, thus accelerating the process and enabling the analysis of larger programs compared to traditional symbolic execution and model checking methods.
format Preprint
id arxiv_https___arxiv_org_abs_2409_13478
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Divide and Conquer based Symbolic Vulnerability Detection
Scherb, Christopher
Heitz, Luc Bryan
Grieder, Hermann
Cryptography and Security
In modern software development, vulnerability detection is crucial due to the inevitability of bugs and vulnerabilities in complex software systems. Effective detection and elimination of these vulnerabilities during the testing phase are essential. Current methods, such as fuzzing, are widely used for this purpose. While fuzzing is efficient in identifying a broad range of bugs and vulnerabilities by using random mutations or generations, it does not guarantee correctness or absence of vulnerabilities. Therefore, non-random methods are preferable for ensuring the safety and security of critical infrastructure and control systems. This paper presents a vulnerability detection approach based on symbolic execution and control flow graph analysis to identify various types of software weaknesses. Our approach employs a divide-and-conquer algorithm to eliminate irrelevant program information, thus accelerating the process and enabling the analysis of larger programs compared to traditional symbolic execution and model checking methods.
title Divide and Conquer based Symbolic Vulnerability Detection
topic Cryptography and Security
url https://arxiv.org/abs/2409.13478