llm-guard and Resk-LLM
These two tools are competitors, with LLM-Guard offering a significantly more mature and widely adopted security toolkit for LLM interactions compared to Resk-LLM's less established protective layer for API calls.
About llm-guard
protectai/llm-guard
The Security Toolkit for LLM Interactions
Provides modular input and output scanners for LLM pipelines—including prompt injection detection, secret redaction, toxicity analysis, and factual consistency checking—deployable as a Python library or standalone API. Uses a composable scanner architecture enabling fine-grained control over which security checks run on user inputs and model outputs. Integrates with OpenAI's API and other LLM providers through straightforward configuration.
About Resk-LLM
Resk-Security/Resk-LLM
Resk is a robust Python library designed to enhance security and manage context when interacting with LLMs. It provides a protective layer for API calls, safeguarding against common vulnerabilities and ensuring optimal performance. And safe layer again Prompt Injection.
Provides multi-layered defense through heuristic pattern matching, vector database semantic similarity checks against known attacks, and specialized detectors for PII, doxxing, invisible text, and malicious URLs. Integrates with OpenAI, Anthropic, Cohere, DeepSeek, and OpenRouter via a unified RESK orchestrator, plus FastAPI and HuggingFace frameworks, with optional lightweight scikit-learn alternatives to PyTorch dependencies. Includes canary token injection for detecting data leaks in responses and REGEX-based pattern management for custom security rules.
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