DIVE: A Multi-Label Smart Contract Vulnerability Dataset
Authors/Creators
Description
📄 Dataset Description
The DIVE dataset was constructed from raw data collected via the Etherscan API, using three main endpoints to capture:
-
🧩 Contract-level metadata
-
🧾 Account-level information
-
⚙️ Opcodes
DIVE integrates a wide variety of smart contract features, organized into two separate datasets:
-
DIVE_PRE_Data (pre-deployment features)
-
DIVE_POST_Data (post-deployment features)
Each dataset is available in two formats: Raw and Preprocessed. Following multiple preprocessing steps, the final processed versions provide:
-
22,330 smart contracts (samples)
-
221 features in DIVE_PRE_Data
-
176 features in DIVE_POST_Data
🏷️ Multi-Label Vulnerability Annotation
Since a single contract can exhibit multiple vulnerabilities, DIVE is structured as a multi-label dataset. Vulnerability labels were generated through the MultiTagging framework, which analyzes each contract’s source code using a suite of six established tools: MAIAN, Mythril, Semgrep, Slither, Solhint, and VeriSmart. All tools were executed with consistent versions and configurations, aligned with the MultiTagging project specifications.
🛡️ Vulnerability Labels (DASP Top 10 Categories)
The dataset includes labels mapped to the first 8 categories of the DASP Top 10 vulnerability taxonomy:
-
Reentrancy
-
Access Control
-
Arithmetic Issues (Integer Overflow/Underflow)
-
Unchecked Call Return Values
-
Denial of Service (DoS)
-
Bad Randomness
-
Front Running
-
Time Manipulation (Timestamp Dependence)
🎯 Applications
The DIVE dataset is primarily intended for smart contract vulnerability detection through security analysis and machine learning.
Beyond this, its rich feature set and multi-label structure enable research across multiple domains, including:
-
Vulnerability Detection
-
Representation Learning
-
Transfer & Domain Adaptation
-
Feature Interpretability
-
Anomaly Detection
📦 Package Contents
-
DIVE_Raw_Data.zip – PRE- and POST-deployment unprocessed attributes.
-
DIVE_Processed_Data.zip – PRE- and POST-deployment data ready for ML tasks.
-
DIVE_Labels.zip –
-
DIVE_Labels.csv: Final multi-label vulnerability annotations. -
Tool_Results.csv: Per-tool vulnerability flags mapped to DASP categories.
-
-
Feature list.xlsx – Comprehensive feature catalog (name, type, description, category).
-
EDA_and_Profiling_Reports.zip – Exploratory data analysis, profiling reports, and feature distribution plots for both PRE and POST datasets.
Files
DIVE_Labels.zip
Files
(1.2 GB)
| Name | Size | |
|---|---|---|
|
md5:ace7aaebd19e040ca78f578fb5ecc6cf
|
253.9 kB | Preview Download |
|
md5:03af6da3e7427ca2f780f6e9b4d10c0e
|
16.3 MB | Preview Download |
|
md5:23b9557e9de3fb6ce3e636a097c64bfd
|
546.7 MB | Preview Download |
|
md5:de4e30d8f219599a8030c558afa9dc2b
|
594.0 MB | Preview Download |
|
md5:7938743c46ef4301d3f6cb38cfd21b37
|
45.4 kB | Download |
Additional details
Related works
- Is published in
- Data paper: 10.1038/s41597-026-07025-5 (DOI)
Software
- Repository URL
- https://github.com/DIVE4Data/DIVE.git
- Programming language
- Python
- Development Status
- Active