.png){kind=icon}
返回
xFuzz: Machine Learning Guided Cross-Contract Fuzzing
.png){kind=icon}
OA
AI
DOI：10.1109/TDSC.2022.3182373.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Smart contract transactions are increasingly interleaved by cross-contract calls. While many tools have been developed to identify a common set of vulnerabilities, the cross-contract vulnerability is overlooked by existing tools. Cross-contract vulnerabilities are exploitable bugs that manifest in the presence of more than two interacting contracts. Existing methods are however limited to analyze a maximum of two contracts at the same time. Detecting cross-contract vulnerabilities is highly non-trivial. With multiple interacting contracts, the search space is much larger than that of a single contract. To address this problem, we present xFuzz, a machine learning guided smart contract fuzzing framework. The machine learning models are trained with novel features (e.g., word vectors and instructions) and are used to filter likely benign program paths. Comparing with existing static tools, machine learning model is proven to be more robust, avoiding directly adopting manually-defined rules in specific tools. We compare xFuzz with three state-of-the-art tools on 7,391 contracts. xFuzz detects 18 exploitable cross-contract vulnerabilities, of which 15 vulnerabilities are exposed for the first time. Furthermore, our approach is shown to be efficient in detecting non-cross-contract vulnerabilities as well-using less than 20% time as that of other fuzzing tools, xFuzz detects twice as many vulnerabilities.
Keyword:
Cross-contract vulnerability
fuzzing
machine learning
smart contract
期刊
IF:
7.5
论文数:
2.6K
被引数:
9.6K
机构
引用论文
Ultrafast Absorption Changes of the Lhcii Carotenoids upon Selective Excitation of the Chlorophylls
PREAI
分享收藏分享收藏Genetic polymorphisms at 19q13.33 are associated with [−2]proPSA (p2PSA) levels and provide additional predictive value to prostate health index for prostate cancer.png)
The Prostate
OAAI
The ProstateIF0
OAAI分享收藏
查看更多内容