# Hacking Google reCAPTCHA v3 using Reinforcement Learning

arXiv: https://arxiv.org/abs/1903.01003 · HTML: https://mlsanity.com/paper/1903.01003/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 Mar 2019.

## Built on by (most cited first, 3 of 3)

- [GAN-Aimbots: Using Machine Learning for Cheating in First Person Shooters](https://mlsanity.com/paper/2205.07060/) (2022)
- [COGNITION: From Evaluation to Defense against Multimodal LLM CAPTCHA Solvers](https://mlsanity.com/paper/2512.02318/) (2025)
- [In-Application Defense Against Evasive Web Scans through Behavioral Analysis](https://mlsanity.com/paper/2412.07005/) (2024)

## Abstract (arXiv)

We present a Reinforcement Learning (RL) methodology to bypass Google reCAPTCHA v3. We formulate the problem as a grid world where the agent learns how to move the mouse and click on the reCAPTCHA button to receive a high score. We study the performance of the agent when we vary the cell size of the grid world and show that the performance drops when the agent takes big steps toward the goal. Finally, we used a divide and conquer strategy to defeat the reCAPTCHA system for any grid resolution. Our proposed method achieves a success rate of 97.4% on a 100x100 grid and 96.7% on a 1000x1000 screen resolution.