LogoAISecKit
  • Search
  • Collection
  • Category
  • Tag
  • Blog
  • Pricing
  • Submit
LogoAISecKit

Newsletter

Join the Community

Subscribe to our newsletter for the latest news and updates

LogoAISecKit

Curated directory of 1700+ AI tools, models, frameworks, MCP servers, and cybersecurity resources

GitHub
Product
  • Search
  • Collection
  • Category
  • Tag
Resources
  • Blog
  • Pricing
  • Submit
Company
  • About Us
  • Privacy Policy
  • Terms of Service
  • Sitemap
Copyright © 2026 All Rights Reserved.
Sponsored Resources
  1. Home
  2. Category
  3. PromptInjectionBench
icon of PromptInjectionBench

PromptInjectionBench

A repository for benchmarking prompt injection attacks against AI models like GPT-4 and Gemini.

Visit Website
image for PromptInjectionBench
Visit Website

Introduction

Overview

PromptInjectionBench is a comprehensive repository designed for analyzing prompt injection attacks on various AI models, including OpenAI's GPT-4 and Gemini Pro. The repository automates the benchmarking process using Python, allowing users to send prompts from the Hugging Face Jailbreak dataset to different language models, collecting and tabulating results systematically.

Key Features
  • Model Comparison: Benchmarking capabilities against multiple models, including the latest Gemini-1.5 Pro and Azure OpenAI GPT-4.
  • Structured Outputs: Utilization of structured outputs to obtain more reliable results without complicated pattern matching.
  • Automation: Automated prompt testing and results gathering for efficient analysis of language model vulnerabilities.
  • Docker Support: Easy setup and deployment using Docker containers, streamlining the testing process.
  • LICENSE: Code is provided under the Apache License 2.0, encouraging usage and modifications.
Benefits
  • Enhanced Security Insight: Helps in understanding how different models respond to potential jailbreak prompts, which is crucial for improving model safety and moderation.
  • Community Contribution: Open-source nature allows contributions from the developer community, fostering better security practices over time.
  • Educational Resource: Serves as a valuable educational tool for researchers and developers interested in LLM vulnerabilities.
Highlights

The project actively monitors changes in model behavior over time, providing insights into how different language models handle malicious prompts. Users can easily run their analysis by setting up the environment with required API keys and simply invoking a few commands.

Back

Information

  • Publisher
    AISecKit
  • Websitegithub.com
  • Published date2025/04/27

Categories

  • AI Models
  • Input Validation & Filtering
  • Prompt Injection Defense

Tags

  • Prompt Injection
  • Model Robustness
  • Jailbreak Detection
  • Security Auditing
  • LLM

More Products

image of Nano Bananary
AI ModelsAI Application PlatformsAI Video Tools
Visit Website
icon of Nano Bananary

Nano Bananary

Nano Bananary is an AI batch image and video generator with 142 effects.

Text-to-VideoGenerative AI
image of Awesome Public Datasets
AI ModelsAI Application PlatformsAI Productivity Tools
Visit Website
icon of Awesome Public Datasets

Awesome Public Datasets

A topic-centric list of HQ open datasets for various fields and applications.

image of dive-into-llms
AI ModelsAI Development Frameworks
Visit Website
icon of dive-into-llms

dive-into-llms

《动手学大模型Dive into LLMs》系列编程实践教程, a free programming tutorial series on large models.

Open SourceLLMAI EducationGenerative AI