Claude Skill

Benchmark prompt-injection attacks defenses and recovery pipelines before trusting an LLM app with Open Prompt Injection

Run structured prompt-injection attack and defense experiments against an LLM-integrated app before production by measuring attack success and testing detection or recovery pipelines.

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Part of agentskillexchange/skills — 249 skills

Install

skills CLI npx skills add https://github.com/agentskillexchange/skills/tree/main/skills/benchmark-prompt-injection-attacks-defenses-and-recovery-pipelines-before-trusting-an-llm-app-with-open-prompt-injection
Claude Code claude plugin marketplace add https://llmmart.ai/marketplace.json && claude plugin install agentskillexchange-skills@llmmart
Git git clone https://github.com/agentskillexchange/skills.git

The skills CLI installs just this skill, for any of its supported agents. Claude Code installs the whole agentskillexchange/skills collection as a plugin from our marketplace. Git is the plain clone.

Skill manifest

Benchmark prompt-injection attacks defenses and recovery pipelines before trusting an LLM app with Open Prompt Injection

Run structured prompt-injection attack and defense experiments against an LLM-integrated app before production by measuring attack success and testing detection or recovery pipelines.

Prerequisites

Conda-managed Python environment, upstream repository checkout, model API credentials as configured upstream, target task and attack configuration files

Installation

Use the upstream install or setup path that matches your environment:

  • conda env create -f environment.yml --name my_custom_env
  • conda activate my_custom_env

Requirements and caveats from upstream:

  • Required Python packages

  • python

Basic usage or getting-started notes:

Documentation

Source

Files (skills)
  • SKILL.md 2.2 KB
    ---
    name: "Benchmark prompt-injection attacks defenses and recovery pipelines before trusting an LLM app with Open Prompt Injection"
    slug: "benchmark-prompt-injection-attacks-defenses-and-recovery-pipelines-before-trusting-an-llm-app-with-open-prompt-injection"
    description: "Run structured prompt-injection attack and defense experiments against an LLM-integrated app before production by measuring attack success and testing detection or recovery pipelines."
    github_stars: 429
    verification: "security_reviewed"
    source: "https://github.com/liu00222/Open-Prompt-Injection"
    author: "liu00222"
    publisher_type: "individual"
    category: "Security & Verification"
    framework: "Multi-Framework"
    tool_ecosystem:
      github_repo: "liu00222/Open-Prompt-Injection"
      github_stars: 429
    ---
    
    # Benchmark prompt-injection attacks defenses and recovery pipelines before trusting an LLM app with Open Prompt Injection
    
    Run structured prompt-injection attack and defense experiments against an LLM-integrated app before production by measuring attack success and testing detection or recovery pipelines.
    
    ## Prerequisites
    
    Conda-managed Python environment, upstream repository checkout, model API credentials as configured upstream, target task and attack configuration files
    
    ## Installation
    
    Use the upstream install or setup path that matches your environment:
    - conda env create -f environment.yml --name my_custom_env
    - conda activate my_custom_env
    
    Requirements and caveats from upstream:
    - ## Required Python packages
    - python
    
    Basic usage or getting-started notes:
    - Then activate the environment:
    - ### A simple demo
    - Before you start, go to './configs/model\_configs/palm2\_config.json' and replace the API keys with your real keys. Please refer to Google's official site for how to obtain an API key for PaLM2. For Meta's Llama model...
    
    - Source: https://github.com/liu00222/Open-Prompt-Injection
    - Extracted from upstream docs: https://raw.githubusercontent.com/liu00222/Open-Prompt-Injection/HEAD/README.md
    
    ## Documentation
    
    - https://github.com/liu00222/Open-Prompt-Injection
    
    ## Source
    
    - [Agent Skill Exchange](https://agentskillexchange.com/skills/benchmark-prompt-injection-attacks-defenses-and-recovery-pipelines-before-trusting-an-llm-app-with-open-prompt-injection/)
    

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