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Update on Overleaf.

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nb72soza Bittner
2025-06-13 21:37:10 +00:00
committed by node
parent d957b8fcef
commit a530e35137
2 changed files with 14 additions and 2 deletions
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12
Chapters/Evaluation.tex
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@@ -14,6 +14,18 @@
% estk.me does not offer an isd-r for regular interaction with our lpa implmenetation -> tesing is limited
% 9esim v2 offers both -> only testing isd-r not USAT for RSP related communication
% data fuzzing
% data fuzzing was performed on all esim except the estk.me esim since this card does not offer an isd-r
% each fuzzing test was performed on all esims one after one
% findings
% during the development of the tracer, we noticed that some esim used different aids to select the isd-r when intercepting the traffic
% xesim, 5ber and esim.me use different aids
% esim.me offers both their custom aid and the common aid to select the isd-r
%
\begin{table}[ht]
\centering

4
Chapters/Implementation.tex
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@@ -213,7 +213,7 @@ Known \glspl{adf} for \gls{isdr} observed during analysis:
\item 5Ber.esim: \texttt{A0000005591010FFFFFFFF8900050500}
\item Xesim: \texttt{A0000005591010FFFFFFFF8900000177}
\item esim.me: \texttt{A0000005591010000000008900000300}
\end{itemize}
\end{itemize}as
The decoded response data is further processed using \texttt{pydantic} data classes. These enable structured parsing of values including Base64-encoded strings, bitfields, version types, and more. Custom encoders/decoders are used to simplify readability and downstream data processing. For bit fields, a mixin is used to allow checking for specific feature flags via simple accessors.
@@ -338,7 +338,7 @@ The mutation engine supports both \textit{deterministic} and \textit{random} mut
\item \textbf{Truncate:} Removes the tail of the \gls{apdu}.
\end{itemize}
Deterministic mode ensures reproducibility by always mutating the same offset, while the random mode selects targets dynamically. This allows us to explore both fixed and variable fuzzing behavior.
Deterministic mode ensures reproducibility by always mutating the same offset, while the random mode selects targets dynamically. This allows us to explore both fixed and variable fuzzing behavior. Both modes behave similar to the deterministic and non-deterministic mutation modes used in AFLPlusPlus.
\subsubsection*{Fuzzing Workflow}