Introduction
The Valhall-ai/prompt-injection-mitigations repository is a comprehensive collection of techniques aimed at mitigating prompt injection attacks in AI applications. It emphasizes the importance of not solely relying on these techniques as a catch-all solution, but rather as part of a layered defense strategy. The document outlines various mitigation techniques, categorized by their approach and effectiveness, and highlights the necessity of maintaining clear trust boundaries in software design.
Key Features
- Diverse Mitigation Techniques: Includes methods such as paraphrasing, threat intel-driven sanitization, and model diversification.
- Categorization: Techniques are categorized based on their active/passive nature, cost, time overhead, and focus (input/output).
- Literature and Resources: Provides references to relevant literature and free/open-source mitigation suites like Rebuff.ai.
Benefits
- Enhanced Security: Aims to protect AI applications from prompt injection attacks through a multi-layered defense.
- Awareness: Raises awareness about the limitations of prompt injection mitigations and the importance of robust software design.
- Community Contribution: Encourages contributions and discussions to improve the repository and its techniques.
