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Chapters/Discussion.tex
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The primary goal of this thesis was to assess the security posture and behavioral consistency of commercial eSIM-on-SIM products through differential testing. To this end, we developed a custom black-box testing framework capable of performing APDU-level fuzzing, structured \gls{asn1} mutation, and trace-based cross-device comparisons. Our evaluation was conducted on eight commercially available eSIM-on-SIM cards from three distinct vendors, revealing a diverse and fragmented implementation landscape.
Our findings indicate substantial architectural differences across implementations. For instance, some cards, such as the one from estk.me, omit the standard \gls{isdr} application altogether and instead expose functionality solely via the \gls{usat} interface. This approach also offers a privately hosted \gls{rlpa} server for provisioning \cite{estkme_rlpa-server_2025}, circumventing the \acposs{gsma} standardized infrastructure and raising questions regarding compliance and security. In contrast, other implementations (e.g., 5ber, Xesim, eSIM.me) do include \gls{isdr} support, but use vendor-specific \glspl{aid}, deviating from the default identifiers specified in SGP.22. These differences complicate interoperability and testing, while also highlighting the absence of a uniform baseline across implementations.
Our findings indicate substantial architectural differences across implementations. For instance, some cards, such as the one from estk.me, omit the standard \gls{isdr} application altogether and instead expose functionality solely via the \gls{usat} interface. This approach also offers a privately hosted \gls{rlpa} server for provisioning \cite{estkme_rlpa-server_2025}, circumventing the \glsposs{gsma} standardized infrastructure and raising questions regarding compliance and security. In contrast, other implementations (e.g., 5ber, Xesim, eSIM.me) do include \gls{isdr} support, but use vendor-specific \glspl{aid}, deviating from the default identifiers specified in SGP.22. These differences complicate interoperability and testing, while also highlighting the absence of a uniform baseline across implementations.
A key contribution of our work is the observation of divergent behaviors in response to identical \gls{rsp} inputs. Mutated \gls{asn1} payloads triggered undefined behavior in several cards, including silent failures, unexpected success responses, and inconsistent status words. In multiple instances, we observed malformed requests that bypassed expected validation routines, particularly during the certificate authentication phase. One notable case revealed a likely certificate validation bypass, where corrupted `AuthenticateServerRequest` messages were accepted despite invalid or tampered certificates. This suggests that parts of the certificate verification pipeline were either improperly implemented or incorrectly reused from prior sessions without sufficient integrity checks.
The implications of such inconsistencies are significant. Bypassing certificate validation undermines the trust model of the \gls{gsma} \gls{rsp} architecture, as the certificate chain rooted in the \gls{gsma} \gls{ca} can no longer be reliably enforced. An attacker able to craft malicious authentication messages, potentially by compromising or emulating an \gls{lpa}, could install rogue profiles onto the \gls{euicc}. While a valid \gls{gsma}-signed profile is still required, this opens the door for profile injection attacks, man-in-the-middle (MITM) provisioning manipulation, and potentially persistent compromise of the device. Previous research, such as that by \textref{lisowski_simurai_2024}, has demonstrated the feasibility of malicious \gls{sim} cards. However, their work focused on runtime behavior and not on provisioning vulnerabilities. Our findings extend this threat model by targeting the provisioning pipeline itself.
The implications of such inconsistencies are significant. Bypassing certificate validation undermines the trust model of the \gls{gsma} \gls{rsp} architecture, as the certificate chain rooted in the \gls{gsma} \gls{ca} can no longer be reliably enforced. An attacker able to craft malicious authentication messages, potentially by compromising or emulating an \gls{lpa}, could install rogue profiles onto the \gls{euicc}. While a valid \gls{gsma}-signed profile is still required, this opens the door for profile injection attacks, man-in-the-middle (MITM) provisioning manipulation, and potentially persistent compromise of the device. Previous research, such as that by \textcite{lisowski_simurai_2024}, has demonstrated the feasibility of malicious \gls{sim} cards. However, their work focused on runtime behavior and not on provisioning vulnerabilities. Our findings extend this threat model by targeting the provisioning pipeline itself.
Several cards also revealed additional security concerns. One exposed undocumented endpoints for firmware updates that fall outside the \gls{gp} command set, suggesting the existence of non-standard, vendor-specific mechanisms for critical operations. The presence of undefined error states, typically in the form of generic status words (\eg, \texttt{6F00}) or generic Errors (\eg, \texttt{UndefinedError}), indicates insufficient internal error handling. In some cases, malformed inputs resulted in successful operations, pointing to either faulty \gls{asn1} decoding or logical flaws in the parsing routines.
@@ -80,6 +80,6 @@ To mitigate the certificate reuse issue observed, we recommend stricter cryptogr
\paragraph{Future Work}
Several directions for future research emerge from this work. First, the \gls{lpa} implementation could be extended to support SGP.31 and SGP.41 specific functionality, enabling testing of \gls{iot}-specific provisioning flows and factory provisioning procedures. Second, to achieve full-loop fuzzing, future versions of the framework could integrate a self-hosted \gls{smdpp} server equipped with test certificates and profiles. This would allow end-to-end testing of the complete \gls{rsp} lifecycle. Finally, improvements to the fuzzing engine, such as incorporating a hypothesis rule based state machine, which would directly compare the fuzzing behaviour of a custom \gls{smdpp} server and \gls{euicc} implementation against propriatary ones.
Several directions for future research emerge from this work. First, the \gls{lpa} implementation could be extended to support SGP.31/SGP.32 and SGP.41/SGP.42 specific functionality, enabling testing of \gls{iot}-specific provisioning flows and factory provisioning procedures. Second, to achieve full-loop fuzzing, future versions of the framework could integrate a self-hosted \gls{smdpp} server equipped with test certificates and profiles. This would allow end-to-end testing of the complete \gls{rsp} lifecycle. Finally, improvements to the fuzzing engine, such as incorporating a hypothesis rule based state machine, which would directly compare the fuzzing behaviour of a custom \gls{smdpp} server and \gls{euicc} implementation against propriatary ones.