---
license: mit
configs:
- config_name: vulnerable-w-explanations
  data_files: db-vulnerable.csv
  default: true
- config_name: verified-functions
  data_files: db-verified.csv
language:
- en
tags:
- finance
pretty_name: Smart Contract Vulnerabilities with Explanations
size_categories:
- 1K<n<10K
---

These datasets serve as a basis for other datasets in this family which are built for tasks like *Classification* or *Seq2Seq generation*.


# 1. Smart Contract Vulnerabilities with Explanations (`vulnerable-w-explanations`)
This repository offers two datasets of `Solidity` functions,
This dataset comprises vulnerable `Solidity` functions audited by 5 auditing companies:

([Codehawks](https://www.codehawks.com/), [ConsenSys](https://consensys.io/), [Cyfrin](https://www.cyfrin.io/), [Sherlock](https://www.sherlock.xyz/), [Trust Security](https://www.trust-security.xyz/)). These audits are compiled by [Solodit](https://solodit.xyz/).

## Usage
```python
from datasets import load_dataset
dataset = load_dataset(
  "msc-smart-contract-audition/vulnerable-functions-base",
  split='train',
  escapechar='\\',
)
```

| Field | Description |
|-|-|
| 1. `name` | Title of audit report                                                                                 |
| 2. `severity` | Severity of vulnerability (`Low`, `Medium`, `High`) |
| 3. `description` | Description/Explanation of the vulnerability |
| 4. `recommendation` | Recommended mitigation of the vulnerability |
| 5. `impact` | Explains how the vulnerability affects the smart contract (Optional) |
| 6. `function` | Raw vulnerable *solidity* code (*Sometimes this could be inaccurate. Best efforts were made to clean-up the dataset but some rows might include other programming languages e.g. javascript*) |


# 2. Verified functions (`verified-functions`)
This repository also includes a dataset with functions with no known vulnerabilities. They were scraped-off from [Etherscan](https://etherscan.io). 
Specifically, the functions are a part of the top 500 auditted contracts holding at least `1 ETH`.

## Usage
```python
from datasets import load_dataset
dataset = load_dataset(
  "msc-smart-contract-audition/vulnerable-functions-base",
  name="verified-functions",
  split='train',
  escapechar='\\',
)
```

| Field | Description |
|-|-|
| 1. `function` | Raw solidity code |

# Additional Info
- The newline characters are escaped (i.e. `\\n`)
- The dataset has a single split `train` (hence the adjusted loading isntructions).