DocumentCode
1797834
Title
Vulnerability mining of Cisco router based on fuzzing
Author
Fengjiao Li ; Luyong Zhang ; Dianjun Chen
Author_Institution
Key Lab. of Universal Wireless Commun., Minist. of Educ., Beijing Univ. of Posts & Telecommun., Beijing, China
fYear
2014
fDate
15-17 Nov. 2014
Firstpage
649
Lastpage
653
Abstract
Router security analysis plays a vital role in maintaining network security. However, IOS, which runs in Cisco routers, has been proved carrying serious security risks. And in order to improve security, we need to conduct vulnerability mining on IOS. Currently, Fuzzing, as a simple and effective automated test technology, is widely used in vulnerability discovery. In this paper, we introduce a novel testing framework for Cisco routers. Based on this framework, we first generate test cases with Semi-valid Fuzzing Test Cases Generator (SFTCG), which considerably improves the test effectiveness and code coverage. After that, we develop a new Fuzzer based on SFTCG and then emulate Cisco router in Dynamips, which makes it easy to interact with GDB or IDA Pro for debugging. In order to supervise the Target, we employ a Monitor Module to check the status of the router regularly. Finally, through the experiment on ICMP protocol in IOS, we find the released vulnerabilities of Ping of Death and Denial of Service, which demonstrates the effectiveness of our proposed Fuzzer.
Keywords
computer network security; routing protocols; transport protocols; Cisco router mining; Denial of Service; GDB; ICMP protocol; IDA; IOS; SFTCG; dynamip; internet control message protocol; monitor module; network security; router security risk analysis; semivalid fuzzing test case generator; target supervision; Communication networks; Debugging; Monitoring; Routing protocols; Security; Testing; Cisco IOS; Fuzzing; SFTCG; Vulnerability;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems and Informatics (ICSAI), 2014 2nd International Conference on
Conference_Location
Shanghai
Print_ISBN
978-1-4799-5457-5
Type
conf
DOI
10.1109/ICSAI.2014.7009366
Filename
7009366
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