Rebuff

Rebuff AI is a self-hardening prompt injection detector. It is designed to protect AI applications from prompt injection (PI) attacks through a multi-layered defense.

PI attacks are a type of adversarial attack where the attacker crafts a malicious prompt to trick the AI model into generating harmful or misleading output. For example, an attacker might craft a prompt that asks the AI model to generate a fake news article or to write a code snippet that contains a security vulnerability.

Rebuff AI uses a variety of techniques to detect and defend against PI attacks, including:

• Heuristics: Rebuff AI uses a set of heuristics to filter out potentially malicious input before it reaches the AI model.
• LLM-based detection: Rebuff AI also uses a dedicated LLM to analyze incoming prompts and identify potential attacks.
• VectorDB: Rebuff AI stores embeddings of previous attacks in a vector database to recognize and prevent similar attacks in the future.
• Canary tokens: Rebuff AI adds canary tokens to prompts to detect leakages, allowing the framework to store embeddings about the incoming prompt in the vector database and prevent future attacks.

Rebuff AI is a powerful tool that can help to protect AI applications from PI attacks. It is still under development, but it has already been shown to be effective in detecting and preventing a wide range of PI attacks.

Rebuff AI can be used in a variety of settings, including:

• Natural language processing (NLP) applications: Rebuff AI can be used to protect NLP applications from PI attacks, such as text generation, translation, and question answering applications.
• Machine learning (ML) applications: Rebuff AI can also be used to protect ML applications from PI attacks, such as image classification, object detection, and machine translation applications.
• Web applications: Rebuff AI can be used to protect web applications from PI attacks, such as chatbots, virtual assistants, and search engines.

Rebuff AI is a valuable tool for anyone who is developing or using AI applications. It can help to protect these applications from PI attacks and make them more secure and reliable.