LLM Guard — Input/Output Security Toolkit

LLM Guard — Input/Output Security Toolkit

LLM Guard is a comprehensive security layer for LLM-powered applications, providing both input (prompt) and output (response) scanners that can be dropped in-line with any LLM call. It is built and maintained by ProtectAI and is widely used in production AI pipelines.

Key Features

• Input scanners: prompt injection detector, ban-topics filter, ban-substrings, anonymize (PII), token limit enforcement, regex guardrails
• Output scanners: no-refusal detector, relevance check, JSON/code validation, sensitive-data redaction, factual consistency
• Synchronous + async APIs; OpenAI-compatible
• Integrates with LangChain, LlamaIndex, and bare-metal OpenAI clients
• Self-hosted — no data leaves your infrastructure

Quick Start

from llm_guard import scan_prompt, scan_output
from llm_guard.input_scanners import PromptInjection, Anonymize
from llm_guard.output_scanners import Sensitive

scanned_prompt, results = scan_prompt(
    scanners=[PromptInjection(), Anonymize()],
    prompt="Ignore previous instructions and...",
)
print(scanned_prompt, results)

npx ai-supply add llm-guard-input-output-security

Curated mirror of the open-source LLM Guard (MIT). Get it from the source.