LLM Guard vs Sanctum Runtime

LLM Guard is a self-hosted security toolkit for checking interactions with large language models. It scans prompts and outputs for concerns such as prompt injection, secrets, personally identifiable information, toxicity, bias, malicious URLs, and factual consistency. It can sanitize interactions, detect harmful language, help prevent data leakage, and resist prompt injection attacks. The documentation includes examples for the OpenAI SDK, LangChain, LiteLLM, and LlamaIndex. In the OpenAI examples, prompts and responses are scanned; a streaming example also checks response chunks. LLM Guard can run as an API, and custom scanners can be added. Installation uses `pip install llm-guard` and requires Python 3.9 or higher. It is free and listed under the MIT License, with API, Linux, and self-hosted platforms. The repository was archived on July 9, 2026, is read-only, and is no longer actively developed or maintained. Production deployment assistance is directed to GitHub issues, Slack, and [email protected].

Sanctum Runtime is middleware that checks actions from AI agents, robots, and automated systems before they are carried out. It evaluates proposed actions against policies and can approve them, ask for verification, or block them. Operators can review, approve, deny, or escalate actions through web and mobile workflows. The product describes behavioral monitoring, audit logs, policy history, and decision trails for runtime visibility and incident review. Its open-core runtime supports local policy checks and offline verification, including local Ollama risk scoring. Documented integrations include OpenAI, Claude/MCP, Gemini-style function calling, DeepSeek, Grok, Bedrock-compatible endpoints, NVIDIA NIM, custom agents, and local runtimes. Developers can use Node and Python SDKs, an MCP wrapper, ROS2-oriented policy packs, and smart-home and embodied-agent templates. The repository is described as MIT-licensed and self-hostable; a hosted console and proxy path are also available. The product identifies itself as embedded runtime middleware, not a standalone consumer app or robot controller. Some enterprise capabilities, including fleet orchestration and organization-wide policy sync, are private.