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Title: SEESAW: a tool for detecting memory vulnerabilities in protocol stack implementations
As the number of Internet of Things (IoT) devices proliferate, an in-depth understanding of the IoT attack surface has become quintessential for dealing with the security and reliability risks. IoT devices and components execute implementations of various communication protocols. Vulnerabilities in the protocol stack implementations form an important part of the IoT attack surface. Therefore, finding memory errors in such implementations is essential for improving the IoT security and reliability. This paper presents a tool, SEESAW, that is built on top of a static analysis tool and a symbolic execution engine to achieve scalable analysis of protocol stack implementations. SEESAW leverages the API model of the analyzed code base to perform component-level analysis. SEESAW has been applied to the USB and Bluetooth modules within the Linux kernel. SEESAW can reproduce known memory vulnerabilities in a more scalable way compared to baseline symbolic execution.  more » « less
Award ID(s):
1942235
NSF-PAR ID:
10436569
Author(s) / Creator(s):
;
Date Published:
Journal Name:
MEMOCODE'21
Page Range / eLocation ID:
126 to 133
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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