Open-Prompt-Injection
Open-Prompt-Injection is an open-source toolkit designed for benchmarking and evaluating prompt injection attacks and defenses in LLM-integrated applications. The repository provides various functionalities including but not limited to:
- Attack Implementations: Supports several attack strategies - naive, escape, ignore, fake_comp, and combine.
- Defense Mechanisms: Configurations for defenses are provided, ensuring a robust testing environment.
- Compatibility: Currently supports PaLM2 with plans for expanding compatibility with other models like Llama and GPT in the future.
- User-Friendly Interface: Provides simple code snippets to aid users in implementing and testing integrations.
Key Features
- Benchmarking framework for prompt injection attacks.
- Comprehensive implementations for attacks and defenses.
- Example usage through Python code snippets for easy integration.
- Documentation and citation for academic reference.
Benefits
- Aids researchers and developers in understanding prompt injection vulnerabilities.
- Facilitates secure LLM usage through integrated attack and defense tactics.
Highlights
- Supports fine-tuning with external models.
- Detailed configurations and customizable API key management for different models.