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https://github.com/softsec-kaist/smartian-artifact
Artifacts for Smartian, a grey-box fuzzer for Ethereum smart contracts.
https://github.com/softsec-kaist/smartian-artifact
Last synced: about 1 month ago
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Artifacts for Smartian, a grey-box fuzzer for Ethereum smart contracts.
- Host: GitHub
- URL: https://github.com/softsec-kaist/smartian-artifact
- Owner: SoftSec-KAIST
- License: mit
- Created: 2021-09-27T04:03:48.000Z (about 3 years ago)
- Default Branch: main
- Last Pushed: 2024-07-24T07:48:10.000Z (5 months ago)
- Last Synced: 2024-07-24T09:12:52.675Z (5 months ago)
- Language: Solidity
- Homepage:
- Size: 5.9 MB
- Stars: 12
- Watchers: 5
- Forks: 8
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- License: LICENSE.md
Awesome Lists containing this project
README
Smartian Artifact
========
[Smartian](https://github.com/SoftSec-KAIST/Smartian) is a grey-box fuzzer for
Ethereum smart contracts. This repository contains artifacts for the
experiments in our paper in ASE 2021, "Smartian: Enhancing Smart Contract
Fuzzing with Static and Dynamic Data-Flow Analyses".
# Changes
The original version of artifact at the time publication is tagged with
[v1.0](https://github.com/SoftSec-KAIST/Smartian-Artifact/releases/tag/v1.0).
The latest commit uses Ubuntu 20.04 to use net8.0 for Smartian. As a result, we
had to stop the support of ILF and Manticore in this repository. FYI, the last
version that uses Ubuntu 18.04 is commit
[a2d9ba](https://github.com/SoftSec-KAIST/Smartian-Artifact/commits/a2d9ba).
# Structure
We run all our experiments in a dockerized environment. In
[docker-setup](./docker-setup), we provide various files required to build the
docker image. The [benchmarks](./benchmarks) directory contains benchmarks we
used for the experiments. In [scripts](./scripts), you can find scripts to run
the experiments and analyze their results.
# Setup
We assume that your system has Docker installed. Also, you should be able to run
the `docker` command without `sudo`. The following command will build the
docker image name 'smartian-artifact', using our [Dockerfile](./Dockerfile).
```
$ ./build.sh
```
Next, check the `MAX_INSTANCE_NUM` configurations parameter in
[scripts/run\_experiment.py](./scripts/run_experiment.py) script.
We ran the experiments in a server machine with 88 cores, so this parameter is
currently set to 72. Make sure that this parameter value is lower than the
number of cores in your machine.
# Evaluation of the impact of data-flow-analyses
To reproduce the experiment in Section V.B of our paper, you can run the
following script. This script internally executes `run_experiment.py` to run
Smartian with four different modes explained in the paper. Here, the script
argument specifies the number of repetition for the experiment.
```
$ ./scripts/test_dfa_impact.sh 5
```
After the above command finishes, you will obtain the `output/result-dfa-impact`
directory that contains the raw data. For instance, `dfa` subdirectory contains
the result of running Smartian with both static and dynamic analyses enabled
(which is the default mode).
```
$ ls output/result-dfa-impact/
dfa dynamic nodfa static
$ ls output/result-dfa-impact/dfa/
B1-smartian-1 B1-smartian-2 B1-smartian-3 B1-smartian-4 B1-smartian-5
```
Now, you can parse the experiment results as below. You may also take a look at
`plot_cov.py`, `count_b1_alarm.py`, and `measure_overhead.py` scripts to get
more statistics.
```
$ python scripts/plot_b1_cve.py output/result-dfa-impact/dfa/*
```
# Comparison between Smartian and other tools
Similarly, you can use the following scripts to reproduce the experiment in
Section V.C of our paper, which compares Smartian against other testing tools.
```
$ ./scripts/test_B1_compare.sh 5
$ ./scripts/test_B2_compare.sh 5
```
Then, you will get the raw data under `output/result-B1-compare` and
`output/result-B2-compare`.
```
$ ls output/result-B1-compare/
mythril sFuzz smartian
$ ls output/result-B2-compare/
mythril sFuzz smartian
```
To obtain the results in our paper, you may refer to the following commands.
```
$ python scripts/plot_b1_cve.py output/result-B1-compare/smartian/*
$ python scripts/plot_b2_bug.py output/result-B2-compare/smartian/*
$ python scripts/count_b2_alarm.py output/result-B2-compare/smartian/*
```
# Large-scale experiment with Smartian
Lastly, we also provide the script for the large-scale experiment in Section
V.D of the paper.
```
$ ./scripts/test_large_scale.sh 1
$ python scripts/count_b3_alarm.py output/result-large-scale/B3-smartian-1/
```