niklas/master_thesis
1
0
Fork 0
mirror of https://sharelatex.tu-darmstadt.de/git/681e0e7a3a9c7c9c6b8bb298 synced 2025-12-08 05:27:59 +00:00
Code Issues Packages Projects Releases Wiki Activity

Update on Overleaf.

Browse Source
This commit is contained in:
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
Download Patch File Download Diff File Expand all files Collapse all files

4
Chapters/Implementation.tex
View File

@@ -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}