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Automated Security Analysis of Firmware
KTH, School of Electrical Engineering and Computer Science (EECS).
2022 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Internet of Things (IoT) devices are omnipresent in both industries and our homes. These devices are controlled by a software called firmware. Firmware like any other software may contain security vulnerabilities and the sole entity responsible to provide secure firmware is the vendor of the device. There are many analysis reports for individual devices that have found vulnerabilities however this is a manual process and unscalable. Several tools exist today for security analysis but usually with focus on a single aspect of firmware analysis. In this thesis, to better understand challenges with respect to automation of securityfocused analysis of firmware images in largescale, a framework is implemented by combining a number of existing tools using both static and dynamic analysis. A dataset of 241 firmware images from 7 vendors was collected. After evaluation of the framework on the dataset, it was shown that 85 images contained several known vulnerabilities which for some images a high percentage of these already were known before the firmware release date. 

Abstract [sv]

Internet of Things (IoT) enheter är allestädes närvarande i både industrier och våra hem. Dessa enheter styrs av en programvara som kallas firmware. Firmware som alla andra programvara kan innehålla säkerhetsbrister och den enda entiet som är ansvarig för att tillhandahålla säker firmware är leverantören av enheten. Det finns många analysrapporter för enskilda enheter som har hittat sårbarheter men detta är en manuell process och oskalbar. Flera verktyg finns idag för säkerhetsanalys men oftast med fokus på en enda aspekt av firmwareanalys. I denna avhandling, för att bättre förstå utmaningar med avseende på automatisering av säkerhet fokuserad analys av firmwarebilder i stor skala, implementeras ett ramverk genom att kombinera ett antal befintliga verktyg med både statisk och dynamisk analys. A datauppsättning av 241 firmwarebilder från 7 leverantörer samlades in. Efter utvärdering av ramverket på datamängden visades det att 85 bilder innehöll flera kända sårbarheter som för vissa bilder en hög andel av dessa redan var kända före releasedatumet för den fasta programvaran.

Place, publisher, year, edition, pages
2022. , p. 47
Series
TRITA-EECS-EX ; 2022:367
Keywords [en]
Firmware Security, Automation, Static Analysis, Dynamic Analysis, Security Vulnerability
Keywords [sv]
Firmwaresäkerhet, automation, statisk analys, dynamisk analys, säkerhet
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-320355OAI: oai:DiVA.org:kth-320355DiVA, id: diva2:1704788
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Available from: 2022-10-20 Created: 2022-10-19 Last updated: 2022-10-20Bibliographically approved

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CiteExportLink to record
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