Pith. sign in

REVIEW 3 cited by

Security Analysis Methods on Ethereum Smart Contract Vulnerabilities: A Survey

Not yet reviewed by Pith; the record is open.

Re-run · record.json Download PDF Read on arXiv ↗

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 1908.08605 v3 pith:7WLLSHYR submitted 2019-08-22 cs.CR

Purathani Praitheeshan , Lei Pan , Jiangshan Yu , Joseph Liu , Robin Doss This is my paper
classification cs.CR
keywords smartvulnerabilitiescontractssecurityanalysissoftwareattacksethereum
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

Smart contracts are software programs featuring both traditional applications and distributed data storage on blockchains. Ethereum is a prominent blockchain platform with the support of smart contracts. The smart contracts act as autonomous agents in critical decentralized applications and hold a significant amount of cryptocurrency to perform trusted transactions and agreements. Millions of dollars as part of the assets held by the smart contracts were stolen or frozen through the notorious attacks just between 2016 and 2018, such as the DAO attack, Parity Multi-Sig Wallet attack, and the integer underflow/overflow attacks. These attacks were caused by a combination of technical flaws in designing and implementing software codes. However, many more vulnerabilities of less severity are to be discovered because of the scripting natures of the Solidity language and the non-updateable feature of blockchains. Hence, we surveyed 16 security vulnerabilities in smart contract programs, and some vulnerabilities do not have a proper solution. This survey aims to identify the key vulnerabilities in smart contracts on Ethereum in the perspectives of their internal mechanisms and software security vulnerabilities. By correlating 16 Ethereum vulnerabilities and 19 software security issues, we predict that many attacks are yet to be exploited. And we have explored many software tools to detect the security vulnerabilities of smart contracts in terms of static analysis, dynamic analysis, and formal verification. This survey presents the security problems in smart contracts together with the available analysis tools and the detection methods. We also investigated the limitations of the tools or analysis methods with respect to the identified security vulnerabilities of the smart contracts.

Discussion (0). Sign in to comment.

Forward citations

Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection

    cs.CR 2025-07 conditional novelty 5.0 of 10

    SAEL combines LLM predictions, LLM-generated explanations, and code features via an adaptive mixture-of-experts gate and reports state-of-the-art F1 on four smart contract vulnerability benchmarks.

  2. Smart-LLaMA-DPO: Reinforced Large Language Model for Explainable Smart Contract Vulnerability Detection

    cs.CR 2025-06 conditional novelty 5.0 of 10

    A LLaMA-3.1-8B model trained with continual pre-training, supervised fine-tuning, and direct preference optimization reports state-of-the-art accuracy and F1 for smart contract vulnerability detection and explanation.

  3. FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning

    cs.LG 2025-07 reject novelty 4.0 of 10

    A LinUCB contextual bandit selects federated aggregation rules online based on update variance, cosine similarity, and mean norm, claiming superior accuracy and tunable risk posture.

Pith tools