---
license: mit
language:
  - en
size_categories:
  - n<1K
tags:
  - security
  - pentesting
  - vulnerability-assessment
  - ground-truth
  - benchmark
pretty_name: EthiBench Ground Truth
configs:
  - config_name: paygoat
    data_files:
      - split: test
        path: data/paygoat_gt.jsonl
  - config_name: vulnbank
    data_files:
      - split: test
        path: data/vulnbank_gt.jsonl
  - config_name: xben
    data_files:
      - split: test
        path: data/xben_gt.jsonl
  - config_name: all
    data_files:
      - split: test
        path: data/*_gt.jsonl
default_config_name: all
---

# EthiBench Ground Truth

Expert-annotated ground-truth vulnerability entries for the [EthiBench](https://github.com/ethiack/ethibench) evaluation framework — a practical evaluation protocol for AI pentesting agents, shifting assessment from task completion to validated vulnerability discovery.

📄 **Paper:** [From Controlled to the Wild: Evaluation of Pentesting Agents for the Real-World](https://arxiv.org/abs/2605.10834)

## Dataset Summary

This dataset contains **108 expert-annotated ground-truth vulnerability entries** across 3 open-source web application targets. These entries serve as the reference set for evaluating AI pentesting agents using the EthiBench framework.

| Target | Config | GT Entries | Repository |
|--------|--------|-----------|------------|
| **vuln-bank** | `vulnbank` | 60 | [Commando-X/vuln-bank](https://github.com/Commando-X/vuln-bank) |
| **PAYGoat** | `paygoat` | 28 | [stuxctf/PAYGoat](https://github.com/stuxctf/PAYGoat) |
| **XBEN-090** | `xben` | 20 | [xbow-engineering/validation-benchmarks](https://github.com/xbow-engineering/validation-benchmarks/tree/main/benchmarks/XBEN-090-24) |

## ⚠️ Target Version Alignment

The ground truth was annotated against **specific pinned versions** of the target apps. Two of the upstream repos have since diverged, so **`git clone <latest main>` will not reproduce the benchmarked target** — use the pinned versions below.

| Target | Pinned version to use | Why |
|--------|-----------------------|-----|
| **vuln-bank** | Commit **`b1962823`** ("disabled query in transactions", 2025-07-23) **+ de-hinting patch** (see [EthiBench docs](https://github.com/ethiack/ethibench#vuln-bank-de-hinting-patch)). | `main` later added a merchant-payments module, a GraphQL API, marketing pages and tests — extra attack surface not in the GT. |
| **PAYGoat** | Commit **`69589b4`** ("Add ticket scenario", 2025-08-04), i.e. before "update to v2" (`0cd0077`). | "v2" adds a whole business-accounts module (extra controllers, routes, models and dashboard pages). |
| **XBEN-090-24** | Latest `main` is fine — the XBEN benchmarks are frozen. | Unchanged upstream. |

See the [full EthiBench repository](https://github.com/ethiack/ethibench) for the vuln-bank de-hinting patch and detailed setup instructions.

## Data Schema

Each entry is a JSON object with the following fields:

| Field | Type | Description |
|-------|------|-------------|
| `id` | string | Unique UUID identifier |
| `name` | string | Short vulnerability title |
| `description` | string | Detailed technical description |
| `category` | string | Vulnerability category |
| `additional_info` | string | CWE classification (e.g., "CWE-89: SQL Injection") |
| `cvss` | float | CVSS 4.0 base score |
| `cvss_vector` | string | Full CVSS 4.0 vector string |
| `subset_name` | string | Human-readable target name |
| `target_id` | string | Machine-readable target identifier |

## Usage

```python
from datasets import load_dataset

# Load all targets
dataset = load_dataset("ethiack/ethibench-gt")

# Load a specific target
paygoat = load_dataset("ethiack/ethibench-gt", "paygoat")
vulnbank = load_dataset("ethiack/ethibench-gt", "vulnbank")
xben = load_dataset("ethiack/ethibench-gt", "xben")

# Example: inspect entries
for entry in paygoat["test"]:
    print(f"{entry['name']} (CVSS {entry['cvss']}): {entry['additional_info']}")
```

## Use with EthiBench

This ground truth is designed to be used with the [EthiBench evaluation framework](https://github.com/ethiack/ethibench). Install and run:

```bash
pip install ethibench
ethibench evaluate <experiment_dir> --dataset data/dataset.yaml --gt-dir data/
```

See the [full documentation](https://github.com/ethiack/ethibench) for details on the evaluation pipeline, matching algorithm, and metrics.

## Citation

If you use this dataset, please cite:

```bibtex
@misc{conde2026controlledwildevaluationpentesting,
      title={From Controlled to the Wild: Evaluation of Pentesting Agents for the Real-World},
      author={Pedro Conde and Henrique Branquinho and Valerio Mazzone and Bruno Mendes and André Baptista and Nuno Moniz},
      year={2026},
      eprint={2605.10834},
      archivePrefix={arXiv},
      primaryClass={cs.AI},
      url={https://arxiv.org/abs/2605.10834},
}
```

## License

This dataset is released under the [MIT License](LICENSE).

---

**Disclaimer:** This content is intended for educational purposes and authorized security testing only. Users are responsible for ensuring compliance with applicable laws and regulations.