Visual-Adversarial-Examples-Jailbreak-Large-Language-Models
Repository for visual adversarial examples that jailbreak large language models
GraphCanon updated Oct 4, 2026 · GitHub synced Oct 4, 2026
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Decision brief
This tool focuses on generating and studying visual adversarial examples designed to exploit vulnerabilities in large language models such as MiniGPT-4.
Good fit when
- If your goal is to research the resilience of Large Language Models against visual inputs that could mislead or 'jailbreak' their usual behavior.
- For scholars and researchers studying model security and robustness, particularly focusing on how image data can affect language models.
Avoid when
- Avoid using this tool if your objective does not involve security testing or research concerning visual-linguistic interactions with large language models.
- If you are looking to enhance general-purpose AI applications without considering adversarial attacks, other frameworks would be more appropriate.
Observed Jul 16, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Dormant (874d since push)
- As of Oct 4, 2026
- Provenance
- Not a fork · Personal account
- As of Oct 4, 2026
- Security (OSV)
- No lockfile
- As of Jul 11, 2026
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install Visual-Adversarial-Examples-Jailbreak-Large-Language-ModelsSimilar tools
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Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
This repository contains work related to creating and analyzing visual adversarial examples aimed at disrupting the functioning of large language models, specifically showcasing attacks on MiniGPT-4.
Capability facts
- Languages
- python
Source: github.language · Oct 4, 2026
Categories
Tags
README
Installation We take MiniGPT 4 (13B) as the sandbox to showcase our attacks. The following installation instructions are adapted from the MiniGPT 4 repository. 1. Set up the environment 2. Prepare the pretrained weights for MiniGPT 4 As we directly inherit the MiniGPT 4 code base...
For agents
This page has a .md twin and JSON over the API.