Framework to analyze and exploit the smart home IoT firmware

Thousands of smart gadgets are linked to the internet each month, and due to various privacy and security issues, such devices may be vulnerable to evil attackers. Currently, there are around 8 billion devices online, and by the beginning of 2025, there will likely be 25 to 35 billion IoT devices globally. Despite this, the security of the devices is not receiving any more attention. Since operating system (OS) and hardware security have improved recently, researchers and hackers now seek vulnerabilities in other areas, such as firmware. When the firmware on many IoT devices isn't updated, it leaves them open to cyberattacks. The period when the Mirai Botnet was widely used is one of the situations in which we may have heard about firmware security. By gaining access to the equipment using the default credentials, the Mirai Botnet infects devices. Therefore, to analyze the firmware's contents for alteration during runtime, the authors of this research performed reverse engineering on it. Authors have exploited the smart home IoT firmware using our framework that identified ten critical network-based vulnerabilities within the firmware, with five vulnerabilities scoring a maximum CVSS score of 10.0 and the remaining five scoring 9.8, highlighting significant threats to smart home IoT devices. In addition, examining the firmware binaries demonstrates the widespread usage of dangerous functions like sprintf and strcpy in addition to the absence of critical security features like NX, PIE, RELRO, and stack protection. By offering a thorough analysis of the vulnerabilities and suggesting best practices for boosting the security of smart home IoT firmware, the results add to the body of information already in existence.

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Institutions

Publication Details

Journal
Measurement Sensors
Published
2024-11-26
DOI
https://doi.org/10.1016/j.measen.2024.101406
Citations
11
Primary Topic
Advanced Malware Detection Techniques
Type
article
Field-Weighted Citation Impact
3.85
Controls
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article

Framework to analyze and exploit the smart home IoT firmware

Keshav Kaushik, Susheela Dahiya, Akashdeep Bhardwaj
11 citations
Measurement Sensors
Advanced Malware Detection Techniques
3.85
article

Framework to analyze and exploit the smart home IoT firmware

Keshav Kaushik, Susheela Dahiya, Akashdeep Bhardwaj
article en
11 citations

Abstract

Thousands of smart gadgets are linked to the internet each month, and due to various privacy and security issues, such devices may be vulnerable to evil attackers. Currently, there are around 8 billion devices online, and by the beginning of 2025, there will likely be 25 to 35 billion IoT devices globally. Despite this, the security of the devices is not receiving any more attention. Since operating system (OS) and hardware security have improved recently, researchers and hackers now seek vulnerabilities in other areas, such as firmware. When the firmware on many IoT devices isn't updated, it leaves them open to cyberattacks. The period when the Mirai Botnet was widely used is one of the situations in which we may have heard about firmware security. By gaining access to the equipment using the default credentials, the Mirai Botnet infects devices. Therefore, to analyze the firmware's contents for alteration during runtime, the authors of this research performed reverse engineering on it. Authors have exploited the smart home IoT firmware using our framework that identified ten critical network-based vulnerabilities within the firmware, with five vulnerabilities scoring a maximum CVSS score of 10.0 and the remaining five scoring 9.8, highlighting significant threats to smart home IoT devices. In addition, examining the firmware binaries demonstrates the widespread usage of dangerous functions like sprintf and strcpy in addition to the absence of critical security features like NX, PIE, RELRO, and stack protection. By offering a thorough analysis of the vulnerabilities and suggesting best practices for boosting the security of smart home IoT firmware, the results add to the body of information already in existence.

Measurement SensorsVol. 37
University of Petroleum and Energy Studies (IN), Graphic Era University (IN)
Industry, innovation and infrastructure
Openalex Percentile: Top 5%
Advanced Malware Detection Techniques
3.85
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Framework to analyze and exploit the smart home IoT firmware — Keshav Kaushik, Susheela Dahiya, et al. · Measurement Sensors (2024) | TGRS Research Map | TGRS