LLM-Guard 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, LLM-Guard ensures that your interactions with LLMs remain safe and secure.
LLM Guard by Protect AI is a comprehensive tool designed to fortify the security of Large Language Models (LLMs).
Documentation | Playground | Changelog
By offering sanitization, detection of harmful language, prevention of data leakage, and resistance against prompt injection attacks, LLM-Guard ensures that your interactions with LLMs remain safe and secure.
Begin your journey with LLM Guard by downloading the package:
pip install llm-guard
Important Notes:
python --version.python -m pip install --upgrade pip.Examples:
LLM Guard is an open source solution. We are committed to a transparent development process and highly appreciate any contributions. Whether you are helping us fix bugs, propose new features, improve our documentation or spread the word, we would love to have you as part of our community.
Join our Slack to give us feedback, connect with the maintainers and fellow users, ask questions, get help for package usage or contributions, or engage in discussions about LLM security!
We're eager to provide personalized assistance when deploying your LLM Guard to a production environment.
FAQs
LLM-Guard 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, LLM-Guard ensures that your interactions with LLMs remain safe and secure.
We found that llm-guard demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 2 open source maintainers collaborating on the project.
Did you know?
Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
Security News
Snyk's use of malicious npm packages for research raises ethical concerns, highlighting risks in public deployment, data exfiltration, and unauthorized testing.
Research
Security News
Socket researchers found several malicious npm packages typosquatting Chalk and Chokidar, targeting Node.js developers with kill switches and data theft.
Security News
pnpm 10 blocks lifecycle scripts by default to improve security, addressing supply chain attack risks but sparking debate over compatibility and workflow changes.