llm-guard

LM protection framework

A security toolkit designed to protect interactions with large language models from various threats and vulnerabilities.

The Security Toolkit for LLM Interactions

GitHub

1k stars
19 watching
165 forks
Language: Python
last commit: almost 2 years ago
Linked from 1 awesome list

adversarial-machine-learningchatgptlarge-language-modelsllmllm-securityllmopsprompt-engineeringprompt-injectionsecurity-toolstransformers

Backlinks from these awesome lists:

Related projects:

RepositoryDescriptionStars
safellama/plexiglassA toolkit to detect and protect against vulnerabilities in Large Language Models.122
protectai/rebuffProtects AI applications from prompt injection attacks through multiple layers of defense1,144
lostoxygen/llm-confidentialityEvaluates the confidentiality of Large Language Models integrated with external tools and services30
aiplanethub/beyondllmAn open-source toolkit for building and evaluating large language models267
ai-hypercomputer/maxtextA high-performance LLM written in Python/Jax for training and inference on Google Cloud TPUs and GPUs.1,557
wgryc/phasellmA framework for managing and testing large language models to evaluate their performance and optimize user experiences.451
melih-unsal/demogptA comprehensive toolset for building Large Language Model (LLM) based applications1,733
flagai-open/aquila2Provides pre-trained language models and tools for fine-tuning and evaluation439
deadbits/vigil-llmA security scanner for Large Language Model prompts to detect potential threats and vulnerabilities326
leondz/lm_risk_cardsA set of tools and guidelines for assessing the security vulnerabilities of language models in AI applications28
victordibia/llmxAn API that provides a unified interface to multiple large language models for chat fine-tuning79
damo-nlp-sg/m3examA benchmark for evaluating large language models in multiple languages and formats93
internlm/openaoeEnables users to engage with multiple large language models simultaneously and access their APIs256
opengvlab/lammA framework and benchmark for training and evaluating multi-modal large language models, enabling the development of AI agents capable of seamless interaction between humans and machines.305