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It is an open-source toolkit for monitoring Large Language Models (LLMs). It extracts signals from prompts & responses, ensuring safety & security. | It is a self-hardening prompt injection detector. It is designed to protect AI applications from prompt injection (PI) attacks through a multi-stage defense. |
Text quality;
Relevance metrics;
Sentiment analysis;
A comprehensive tool for LLM observability | Filter out potentially malicious input before it reaches the LLM;
Use a dedicated LLM to analyze incoming prompts and identify potential attacks;
Store embeddings of previous attacks in a vector database;
Attack signature learning |
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GitHub Stars 954 | GitHub Stars 1.4K |
GitHub Forks 70 | GitHub Forks 117 |
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It is a robust static analysis framework for validating that LLM-generated structured output is safe. It currently supports SQL.

It is a comprehensive tool designed to fortify the security of Large Language Models (LLMs). By offering sanitization, detection of harmful language, prevention of data leakage, and resistance against prompt injection attacks, it ensures that your interactions with LLMs remain safe and secure.

It is an open-source Python package for specifying structure and type, validating and correcting the outputs of large language models (LLMs).