State Consistency Checking for Non-reentrant Function Based on Taint Assisted Symbol Execution

Yu, Bo; Yang, Qiang; Song, Congxi

doi:10.1007/978-3-030-21373-2_40

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

2019

DOI: 10.1007/978-3-030-21373-2_40

|View full text |Cite

State Consistency Checking for Non-reentrant Function Based on Taint Assisted Symbol Execution

Bo Yu

Qiang Yang

Congxi Song

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2022

Publication Types

Select...

Other1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

(1 citation statement)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In future, Dynamic taint analysis 24,25 can further explore the control dependencies of functions. In addition, our current API sequence is fixed, and new uses of the API sequence can also be explored because this allows for more comprehensive fuzz testing of the library.…”

mentioning

confidence: 99%

AutoGenD: fuzz driver generation for binary libraries without header files and symbol information

Wan

Wei

Tang

2022

International Conference on Network Communication and Information Security (ICNCIS 2022)

View full text Add to dashboard Cite

Fuzz testing technology is widely used in vulnerability mining. However, there is less research on fuzz testing specifically for libraries. Both public libraries and private libraries that come with commercial software may have security risks. In the past, testing a library required manual writing of drivers, which required testers to be familiar with the library and take a lot of time. Existing techniques mostly rely on static analysis of source code or focus on binary libraries which rely on header files, but no research in the case without header files and symbol information. In that case, there is faced with three major problems:1) We do not have accurate information (such as the number and types of function parameters) about library functions. 2) The control and data dependencies among API functions are complex. 3) Effectively integrate the information to automatically generate a driver that can correctly perform fuzz testing. We propose AutoGenD to address the problem for libraries without source code, header files, and symbol information. First of all, we obtain the library function information based on the static analysis technology. Then, we obtain the data of the library function parameters through dynamic analysis technology. Finally, we take the template method to synthesize the driver. Through experiments, the driver generated by AutoGenD can effectively trigger existing vulnerabilities (11 bugs). The results indicate that it has the ability to automatically generate a fuzz driver.

show abstract

mentioning

confidence: 99%

AutoGenD: fuzz driver generation for binary libraries without header files and symbol information

Wan

Wei

Tang

2022

International Conference on Network Communication and Information Security (ICNCIS 2022)

View full text Add to dashboard Cite

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

hi@scite.ai

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

State Consistency Checking for Non-reentrant Function Based on Taint Assisted Symbol Execution

Cited by 1 publication

References 16 publications

AutoGenD: fuzz driver generation for binary libraries without header files and symbol information

AutoGenD: fuzz driver generation for binary libraries without header files and symbol information

Contact Info

Product

Resources

About