VIPER_code
Breaking Visual Reasoning CAPTCHAs with VIPER: A Structured Vision-Language Attack Framework VIPER_code is an academic and practical Python framework designed for the analysis and attack of Visual Reasoning CA
Breaking Visual Reasoning CAPTCHAs with VIPER: A Structured Vision-Language Attack Framework
VIPER_code is an academic and practical Python framework designed for the analysis and attack of Visual Reasoning CAPTCHAs (VRC). It implements a structured, modular vision-language attack pipeline that supports a range of CAPTCHA types — including six major VRC datasets and various non-VRC challenges. The framework enables automated evaluation and experimentation with large language models (LLMs) to break CAPTCHAs in a highly configurable manner.
File & Directory Structure
First, unzip all the compressed files.
| File/Folder | Description |
|---|---|
main.py | Main entry for experiment orchestration and accuracy testing. Supports command-line arguments to select LLM providers and datasets dynamically. |
environment_variable.py | LLM API and environment configuration. You must edit this file before running any experiment. |
r1_and_r2_main.py | Script for running “r1” (Direct VLM) and “r2” (YOLO+VLM) series experiments. Configurable via command-line arguments. |
solvers/ | Modular solver scripts organized by LLM provider. |
├── gpt/ | Solvers using OpenAI GPT models (e.g., gpt/xiaodun.py). |
├── deepseek/ | Solvers using DeepSeek models (e.g., deepseek/geetest.py). |
├── grok/ | Solvers using Grok models. |
└── kimi/ | Solvers using Kimi models. |
r1_r2/ | Contains the core logic scripts for r1 and r2 experiments (tools_r1.py, tools_r2.py). |
tools_*.py | Other utility scripts. |
best_28.pt | <sp📤 Share this pageFound this useful? Share it with your network. Files are hosted on the source repository. Click download to access the full dataset. Qi, Minfeng (2026). VIPER_code. https://doi.org/10.5281/zenodo.18191465
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