Benchmark Prompt Injection Attacks Defenses And Recovery Pipelines Before Trusting An Llm App With Open Prompt Injection
ASecurity
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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---
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/)