---
license: cc-by-nc-4.0
pretty_name: CaptchaArena
task_categories:
- image-text-to-text
language:
- en
tags:
- captcha
- gui-agent
- computer-use
- multimodal
- vision-language
- benchmark
size_categories:
- 10K<n<100K
extra_gated_heading: "Request access to CaptchaArena"
extra_gated_description: "CaptchaArena is released under CC BY-NC 4.0 for non-commercial academic research only. The paper is on arXiv (2609.31957), and access requests are now being reviewed."
extra_gated_prompt: "By requesting access you agree to use CaptchaArena solely for non-commercial academic research; commercial use is prohibited. The authors review each request manually, so please give your affiliation and intended research use. Access may be revoked in case of misuse or violation of these terms."
extra_gated_fields:
  Full name: text
  Affiliation / Institution: text
  Email: text
  Intended research use: text
  I confirm I will use this dataset for non-commercial academic research only: checkbox
  I confirm I will NOT use this dataset for any commercial purpose: checkbox
extra_gated_button_content: "Request access"
---

# CaptchaArena

<p align="center"><b>A Large-Scale, Fine-Grained Dataset for Training Computer-Use Agents on Interactive CAPTCHAs</b></p>

<p align="center">
  <a href="https://x0x0x00.github.io/">Zhenhao Zhang</a><sup>1,*</sup>, Zhaoyu Fan<sup>2</sup>, Haohan Ying<sup>3</sup>, Jingwen Hu<sup>3</sup>, Hancen Fan<sup>1</sup>,<br>
  Junhao Zhou<sup>4</sup>, Zitian Chen<sup>1</sup>, <a href="https://ffmpbgrnn.github.io/">Linchao Zhu</a><sup>2,†</sup><br>
  <sup>1</sup>Columbia University &nbsp;·&nbsp; <sup>2</sup>Zhejiang University<br>
  <sup>3</sup>University of Rochester &nbsp;·&nbsp; <sup>4</sup>University of Illinois at Urbana-Champaign<br>
  <sup>*</sup>Project lead &nbsp;·&nbsp; <sup>†</sup>Corresponding author
</p>

<p align="center">
  <a href="https://arxiv.org/abs/2609.31957"><img src="https://img.shields.io/badge/arXiv-2609.31957-b31b1b.svg" alt="arXiv"></a>
  <a href="https://github.com/X0X0X00/CaptchaArena"><img src="https://img.shields.io/badge/Code-GitHub-181717.svg?logo=github" alt="Code"></a>
  <a href="https://huggingface.co/datasets/ZHEN-04/CaptchaArena-Trajectories"><img src="https://img.shields.io/badge/Dataset-CaptchaArena--Trajectories-orange.svg" alt="Trajectories"></a>
  <a href="https://huggingface.co/ZHEN-04/CaptchaAgent"><img src="https://img.shields.io/badge/Model-CaptchaAgent-yellow.svg" alt="Model"></a>
  <a href="https://creativecommons.org/licenses/by-nc/4.0/"><img src="https://img.shields.io/badge/License-CC%20BY--NC%204.0-lightgrey.svg" alt="License: CC BY-NC 4.0"></a>
</p>

![The 20 CAPTCHA types](https://raw.githubusercontent.com/X0X0X00/CaptchaArena/main/assets/overview.jpg)

## Overview

CaptchaArena is a large-scale, fine-grained dataset for training computer-use agents on interactive CAPTCHAs.

- **50K puzzles** across **20 CAPTCHA types** and **5 interaction modes**.
- **Execution-verified**: every solution is replayed against the environment's verifier.
- **Fine-grained supervision**: an executable action solution for every puzzle, and pixel-mask annotations for irregular targets.
- **Live interaction**: agents observe the page through a fixed 1280×1080 viewport and act with low-level pointer and keyboard actions.

| Interaction mode | CAPTCHA types |
|---|---|
| Single-click | Geometry Click, Misleading Click, Pick Area, Place Dot, Select Animal |
| Multi-click | Bingo, Click Order, Image Recognition, Patch Select, Unusual Detection |
| Arrow-cycle | Connect Icon, Coordinates, Dart Count, Image Matching, Object Match, Path Finder, Rotation Match |
| Real-time | Hold Button, Slide Puzzle |
| Text-entry | Dice Count |

## Data

| | Train | Val | Test | Total |
|---|--:|--:|--:|--:|
| Puzzles per type | 2,100 | 200 | 200 | 2,500 |
| Puzzles | 42,000 | 4,000 | 4,000 | 50,000 |

Each split has one folder per type, named `<Split>/<Type>_<N>/` (e.g. `Train/Bingo_2100/`, `Test/Bingo_200/`). A folder holds the puzzle images and two label files:

- `ground_truth.json`: the answer and the fields needed to render the puzzle.
- `ground_truth_cu.json`: the same entries plus `answer_cu`, the solution as an executable action sequence.

```bash
hf auth login
hf download ZHEN-04/CaptchaArena --repo-type dataset --local-dir data
```

## Intended use

CaptchaArena runs entirely in a self-hosted environment; no experiment interacts with a live CAPTCHA service. Its imagery is generated or openly licensed. Because CAPTCHA solving is a dual-use capability, the dataset is released for agent research and the study of CAPTCHA robustness, not for bypassing protections on services you do not own.

## License

Released under CC-BY-NC-4.0 (Creative Commons Attribution–NonCommercial 4.0). Non-commercial academic research use only — commercial use is prohibited. Access is gated: you must request access and agree to these terms before downloading. Please attribute when using this dataset.

## Citation

If you use CaptchaArena, please cite:

```bibtex
@article{zhang2026captchaarena,
  title   = {CaptchaArena: A Large-Scale, Fine-Grained Dataset for Training Computer-Use Agents on Interactive CAPTCHAs},
  author  = {Zhang, Zhenhao and Fan, Zhaoyu and Ying, Haohan and Hu, Jingwen and Fan, Hancen and Zhou, Junhao and Chen, Zitian and Zhu, Linchao},
  journal = {arXiv preprint arXiv:2609.31957},
  year    = {2026}
}
```