update paper

SemSEpaper/exercise.bib

-@INPROCEEDINGS{9678888,
+@INPROCEEDINGS{smartian,
 	author={Choi, Jaeseung and Kim, Doyeon and Kim, Soomin and Grieco, Gustavo and Groce, Alex and Cha, Sang Kil},
 	booktitle={2021 36th IEEE/ACM International Conference on Automated Software Engineering (ASE)}, 
 	title={SMARTIAN: Enhancing Smart Contract Fuzzing with Static and Dynamic Data-Flow Analyses}, 
 	pages={227-239},
 	doi={10.1109/ASE51524.2021.9678888}}
 
-@inproceedings{10.1145/3578527.3578538,
+@inproceedings{fuzzdrivegen,
 	author = {Pani, Siddhasagar and Nallagonda, Harshita Vani and Vigneswaran and Medicherla, Raveendra Kumar and Rajan M},
 	title = {SmartFuzzDriverGen: Smart Contract Fuzzing Automation for Golang},
 	year = {2023},
 	series = {ISEC '23}
 }
 
-@inproceedings {217464,
+@inproceedings {teether,
 	author = {Johannes Krupp and Christian Rossow},
 	title = {{teEther}: Gnawing at Ethereum to Automatically Exploit Smart Contracts},
 	booktitle = {27th USENIX Security Symposium (USENIX Security 18)},
 	month = aug
 }
 
-@inproceedings{10.1145/3243734.3243780,
+@inproceedings{securify,
 	author = {Tsankov, Petar and Dan, Andrei and Drachsler-Cohen, Dana and Gervais, Arthur and B\"{u}nzli, Florian and Vechev, Martin},
 	title = {Securify: Practical Security Analysis of Smart Contracts},
 	year = {2018},
 	location = {Toronto, Canada},
 	series = {CCS '18}
 }
+
+@MISC{
+	doughoyte,
+	author = {doughoyte},
+	title = {MerdeToken: It's Some Hot Shit},
+	note = {\url{https://github.com/Arachnid/uscc/tree/master/submissions-2017/doughoyte} [Accessed: Oct. 27th 2023]}
+}
+
+@misc{CiteDrive2022,
+	title        = {CiteDrive brings reference management to Overleaf},
+	author       = {CiteDrive, Inc},
+	year         = 2022,
+	note         = {\url{https://www.citedrive.com/overleaf} [Accessed: (Use the date of access)]}
+}

SemSEpaper/exercises.aux

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SemSEpaper/exercises.bbl

 \begin{thebibliography}{1}
 
-\bibitem{9678888}
+\bibitem{smartian}
 Jaeseung Choi, Doyeon Kim, Soomin Kim, Gustavo Grieco, Alex Groce, and Sang~Kil
   Cha.
 \newblock Smartian: Enhancing smart contract fuzzing with static and dynamic
 \newblock In {\em 2021 36th IEEE/ACM International Conference on Automated
   Software Engineering (ASE)}, pages 227--239, 2021.
 
-\bibitem{217464}
+\bibitem{doughoyte}
+doughoyte.
+\newblock Merdetoken: It's some hot shit.
+\newblock
+  \url{https://github.com/Arachnid/uscc/tree/master/submissions-2017/doughoyte}
+  [Accessed: Oct. 27th 2023].
+
+\bibitem{teether}
 Johannes Krupp and Christian Rossow.
 \newblock {teEther}: Gnawing at ethereum to automatically exploit smart
   contracts.
 \newblock In {\em 27th USENIX Security Symposium (USENIX Security 18)}, pages
   1317--1333, Baltimore, MD, August 2018. USENIX Association.
 
-\bibitem{10.1145/3578527.3578538}
+\bibitem{fuzzdrivegen}
 Siddhasagar Pani, Harshita~Vani Nallagonda, Vigneswaran, Raveendra~Kumar
   Medicherla, and Rajan M.
 \newblock Smartfuzzdrivergen: Smart contract fuzzing automation for golang.
   Conference}, ISEC '23, New York, NY, USA, 2023. Association for Computing
   Machinery.
 
-\bibitem{10.1145/3243734.3243780}
+\bibitem{securify}
 Petar Tsankov, Andrei Dan, Dana Drachsler-Cohen, Arthur Gervais, Florian
   B\"{u}nzli, and Martin Vechev.
 \newblock Securify: Practical security analysis of smart contracts.

SemSEpaper/exercises.blg

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SemSEpaper/exercises.tex

 \usepackage{xspace}
 \usepackage{todonotes}
 \usepackage{listings}
-\newcommand{\true}{true}
-\newcommand{\false}{false}
 \usepackage[ruled,linesnumbered]{algorithm2e} % Enables the writing of pseudo code.
+\usepackage{float}% http://ctan.org/pkg/float
 
-   \pagestyle{plain}
-   \bibliographystyle{plain}
+\newcommand{\true}{true}
+\newcommand{\false}{false}
+\pagestyle{plain}
+\bibliographystyle{plain}
 
 
 \title{192.127 Seminar in Software Engineering (Smart Contracts) \\
 
 \author{\textbf{*** YOUR NAME AND STUDENT ID ***}}
 
-  \newtheorem{theorem}{Theorem}
-  \newtheorem{lemma}[theorem]{Lemma}
-  \newtheorem{corollary}[theorem]{Corollary}
-  \newtheorem{proposition}[theorem]{Proposition}
-  \newtheorem{conjecture}[theorem]{Conjecture}
-  \newtheorem{definition}[theorem]{Definition}
-  \newtheorem{example}[theorem]{Example}
-  \newtheorem{remark}[theorem]{Remark}
-  \newtheorem{exercise}[theorem]{Exercise}
+\newtheorem{theorem}{Theorem}
+\newtheorem{lemma}[theorem]{Lemma}
+\newtheorem{corollary}[theorem]{Corollary}
+\newtheorem{proposition}[theorem]{Proposition}
+\newtheorem{conjecture}[theorem]{Conjecture}
+\newtheorem{definition}[theorem]{Definition}
+\newtheorem{example}[theorem]{Example}
+\newtheorem{remark}[theorem]{Remark}
+\newtheorem{exercise}[theorem]{Exercise}
 
 
 \renewcommand{\labelenumi}{(\alph{enumi})}
 
 \subsection{Solidity storage layout}
 
-Any contract's storage is a continuous 256-bit address space consisting of 32-bit values. In order to implement dynamically sized data structures like maps and arrays, Solidity distributes their entries in a pseudo-random location. Due to the vast 256-bit range of addresses collisions are statistically extremely improbable and of no practical relevance.
+Any contract's storage is a continuous 256-bit address space consisting of 32-bit values. In order to implement dynamically sized data structures like maps and arrays, Solidity distributes their entries in a pseudo-random location. Due to the vast 256-bit range of addresses collisions are statistically extremely improbable and of little practical relevance in safely implemented contracts.
 
 \medspace
 
-In the case of a dynamic array at variable slot $p$, data is written to continuous locations starting at $keccak(p)$. The array itself contains the length information.
+In the case of a dynamic array at variable slot $p$, data is written to continuous locations starting at $keccak(p)$. The array itself contains the length information as an $uint256$ value. Even enormous arrays are unlikely to produce collisions due to the vast address space, although an improperly managed array may store data to an unbounded user-controlled offset, thereby allowing arbitrary overwriting of data.
 
 \medspace
 
-For maps stored in variable slot $p$ the data for index $k$ can be found at $keccak(k . p)$ where $.$ is the concatenation operator.
+For maps stored in variable slot $p$ the data for index $k$ can be found at $keccak(k . p)$ where $.$ is the concatenation operator. This is a statistically safe approach, as the chance of intentionally finding a value for $keccak(k . p)$ s.t. for a known stored variable $x$, $keccak(k . p) == storage\_address(x)$ is about one in $2^{256}$ and $keccak$ is believed to be a cryptographically secure hash function.
 
 \subsection{The Weakness}
 
-Any unchecked array write is potentially dangerous, as the storage-location of all variables is publicly known and an unconstrained array index can be reverse engineered to target them.
+Any unchecked array write is potentially dangerous, as the storage-location of all variables is publicly known and an unconstrained array index can be reverse engineered to target them. This can be achieved by using the known array storage location $p$, target-variable $x$, and computing the offset-value $o$ such that $keccac(p) + o == storage\_address(x)$.
+
+\medspace
+
+A trivial example of such a vulnerable write operation is shown in Algorithm 1.
 
 \lstset{style=mystyle}
-\begin{algorithm}
+\begin{algorithm}[H]
 	\begin{lstlisting}[language=Octave]
 	pragma solidity 0.4.25;
 	
 	\caption{A completely unchecked array write}
 \end{algorithm}
 
-In the following example the $pop$ function incorrectly checks for an array $length >= 0$, thereby allowing the value to underflow when called with an empty array. Once this weakness is exploited $update$ in Algorithm 2 behaves just like $write$ did in Algorithm 1. 
+\medspace
+
+In the following example (Algorithm 2) the $pop$ function incorrectly checks for an array $length >= 0$, thereby allowing the $length$ value to underflow when called with an empty array. Once this weakness is triggered, $update$ in Algorithm 2 behaves just like $write$ did in Algorithm 1. 
+
+\medspace
 
 \lstset{style=mystyle}
-\begin{algorithm}
+\begin{algorithm}[H]
 	\begin{lstlisting}[language=Octave]
-		pragma solidity 0.4.25;
+	pragma solidity 0.4.25;
+	
+	contract MyContract {
+		address private owner;
+		uint[] private arr;
+		
+		constructor() public {
+			arr = new uint[](0);
+			owner = msg.sender;
+		}
+		
+		function push(value) {
+			arr[arr.length] = value;
+			arr.length++;
+		}
 		
-		contract MyContract {
-			address private owner;
-			uint[] private arr;
-			
-			constructor() public {
-				arr = new uint[](0);
-				owner = msg.sender;
-			}
-			
-			function push(value) {
-				arr[arr.length] = value;
-				arr.length++;
-			}
-			
-			function pop() {
-				require(arr.length >= 0);
-				arr.length--;
-			}
-			
-			function update(unit index, uint value) {
-				require(index < arr.length);
-				arr[index] = value;
-			}
+		function pop() {
+			require(arr.length >= 0);
+			arr.length--;
 		}
+		
+		function update(unit index, uint value) {
+			require(index < arr.length);
+			arr[index] = value;
+		}
+	}
 	\end{lstlisting}
 	\caption{An incorrectly managed array length}
 \end{algorithm}
 
 \section{Code properties and automatic detection}
 
-summarize the code properties that tools are looking for so that they can detect the weakness
+Automatic detection tools can be broadly categorized into ones employing static analysis and those who use fuzzing, i.e. application of semi-random inputs. Notable static analysis tools include Securify \cite{securify} and teEther \cite{teether} which both function in a similar manner:
+
+\medspace
+
+Initially, the given EVM byte-code is disassembled into a control-flow-graph (CFG). In the second step, the tools identify potentially risky instructions. In the case of arbitrary writes, the instruction of note is $sstore(k,v)$ where both $k$ and $v$ are input-controlled. The tools differ in the way they identify whether or not the values are input-controlled. 
+
+\medspace
+
+In the case of Securify \cite{securify}, the CFG is translated into what the authors call "semantic facts" to which an elaborate set of so-called security patterns is applied. These patterns consist of building blocks in the form of predicates, which allows the tool to simply generate output based on the (transitively) matched patterns.
+
+\medspace
+
+teEther \cite{teether} employs a similar approach, but instead the authors opt to build a graph of dependent variables. If the graph arrives at a $sstore(k,v)$ instruction and a path can be found leading to user-controlled inputs, the tool infers a set of constraints which are then used to automatically generate an exploit.
+
+\medspace
+
+The fuzz-driven approach to vulnerability detection is more abstract, as general-purpose fuzzing tools generally don't have knowledge of the analysed program. For the tool SmartFuzzDriverGenerator \cite{fuzzdrivegen}, a multitude of these fuzzing libraries can be used. The problem at hand is, however, that the technique cannot interface with a smart contract out of the box. The "glue" between fuzzer and program is called a driver, hence the name of "driver-generator".
+
+\medspace
+
+SmartFuzzDriverGenerator aims to automatically generate such a driver by %TODO: I have no idea how it does this actually%
+
+\medspace
+
+The Smartian tool \cite{smartian} attempts to find a middle-ground between static and dynamic analysis by first transforming the EVM bytecode into control-flow facts. Based on this information, a set of seed-inputs is generated that are expected to have a high probability of yielding useable results. Should no exploit be found, the seed-inputs are then mutated in order to yield a higher code coverage. %TODO: This is probably extemely inprecise and should be re-written%
 
 \section{Exploit sketch}
 
-sketch ways to potentially exploit the different variants of the weakness.
+\cite{doughoyte}
+%TODO: just explain what this guy does: https://github.com/Arachnid/uscc/tree/master/submissions-2017/doughoyte%
 
-%remove this later%
-\cite{10.1145/3243734.3243780}
-\cite{10.1145/3578527.3578538}
-\cite{217464}
-\cite{9678888}
 
 \bibliography{exercise.bib}