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Update on Overleaf.

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nb72soza Bittner
2025-07-06 10:44:03 +00:00
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Chapters/RelatedWork.tex
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@@ -38,7 +38,7 @@ To support this, they demonstrate how their framework enables fuzz testing by em
Using their emulation framework, the authors discovered multiple high-impact memory corruption vulnerabilities in baseband implementations. These were exploited via spyware-like payloads reminiscent of the \textit{SIMjacker} attack~\cite{enea_simjacker_2019}, remotely installed onto the \gls{sim} card. This spyware exfiltrates information to the attacker without requiring user interaction. Their findings underscore the seriousness of hostile SIMs as an attack vector and argue that such threat models should be incorporated into mobile security considerations.
\textcite{ahmed_security_2024} present a formal model of the \gls{rsp} protocol based on the SGP.22 specification. The model is developed using \texttt{ProVerif} to verify the security properties of remote profile provisioning. Although many of the identified failure modes require strong attacker capabilities—such as compromise of \gls{tls} private keys—the study highlights a particularly practical issue: the absence of a robust mechanism to verify user intent. An attacker could initiate a profile download to a victim's \gls{euicc} without user consent, provided they have access to the device or provisioning channel, resulting in unauthorized profile installation.
\textcite{ahmed_security_2024} present a formal model of the \gls{rsp} protocol based on the SGP.22 specification. The model is developed using \texttt{ProVerif}~\cite{blanchet_efficient_2001} to verify the security properties of remote profile provisioning. Although many of the identified failure modes require strong attacker capabilities—such as compromise of \gls{tls} private keys—the study highlights a particularly practical issue: the absence of a robust mechanism to verify user intent. An attacker could initiate a profile download to a victim's \gls{euicc} without user consent, provided they have access to the device or provisioning channel, resulting in unauthorized profile installation.
\textcite{ahmed_transparency_2021} critiques the centralized trust model underlying the \gls{rsp} ecosystem. The study emphasizes that the entire trust infrastructure hinges on the \gls{pki} used by the \gls{gsma} to certify \gls{smdpp} domains. A breach of any single \gls{smdpp} server could allow an attacker to issue cloned or rogue profiles of that operator to attacker controlled \glspl{euicc}. To address this, the authors propose the SIM Profile Transparency Protocol (SPTP), a protocol designed to enhance transparency and trust in the provisioning process.
@@ -66,7 +66,7 @@ The \texttt{pySim} suite comprises five primary scripts: \texttt{pySim-shell}, \
The \texttt{pySim-trace} script provides a tracing utility and protocol decoder for \gls{sim} card-related communication. It integrates with \texttt{SIMtrace2} to intercept and decode communication between a user device and the \gls{sim} card. This functionality is limited to passive recording and does not support active injection or modification of messages.
The \texttt{pySim-smdpp} script serves as a proof-of-concept implementation of the SGP.22 \gls{smdpp} server component. Notably, \texttt{pySim} does not implement the full SGP.22 protocol stack on the client side (i.e., communication between the \gls{euicc} and the \gls{smdpp} server); its SGP.22 functionality is restricted to the server role only.
The \texttt{pySim-smdpp} script serves as a proof-of-concept implementation of the SGP.22 \gls{smdpp} server component. Notably, \texttt{pySim} does not implement the full SGP.22 protocol stack on the client side (\ie, communication between the \gls{euicc} and the \gls{smdpp} server), although its SGP.22 functionality is restricted to the server role only.
While \texttt{pySim} provides useful standalone utilities, its usability as a general-purpose library is limited. The internal architecture is not optimized for external scripting, requiring substantial effort to perform even basic tasks programmatically. As such, \texttt{pySim} is best suited for interactive use via its provided command-line tools rather than as a cleanly structured library for automation or integration.
@@ -106,7 +106,7 @@ Overall, \texttt{SIMtrace2} is a versatile tool both for passive analysis and ac
Due to its C-language base, \texttt{lpac} is widely adopted across various platforms through language-specific wrappers. It forms the core of several \gls{lpa} implementations, including \texttt{EasyEuicc}, \texttt{OpenEuicc}, \texttt{MiniLPA}, and others~\cite{icedtangerine_easylpac_2025, petercxy_openeuicc_nodate, esimmoe_minilpa_nodate}. It also exposes a command-line interface, allowing users to interact with the \gls{lpa} directly for debugging or automation purposes.
However, \texttt{lpac} only supports SGP.22 version 2.2.2, whereas the most recent version (3.1) introduces several enhancements, especially targeted at \gls{iot} \gls{esim} use cases, including additional return values and extended feature support \cite{gsma_sgp22_2025}. Furthermore, while the software is considered mature and widely usable, its extensibility remains limited. Key components such as \gls{asn1} decoding and encoding are implemented manually without leveraging standardized libraries.
However, \texttt{lpac} only supports SGP.22 version 2.2.2, whereas the most recent version (3.1) introduces several enhancements, especially targeted at \gls{iot} \gls{esim} use cases, including additional return values and extended feature support \cite{gsma_sgp22_2025}. Furthermore, while the software is considered mature and widely usable, its extensibility remains limited. Key components such as \gls{asn1} decoding and encoding are implemented manually without leveraging standardized libraries like \texttt{asn1c}~\cite{walkin_asn1c_2025}.
\paragraph{SIMTester}