📄️ Aim Security
Quick Start
📄️ Aporia
Use Aporia to detect PII in requests and profanity in responses
📄️ Azure Content Safety Guardrail
LiteLLM supports Azure Content Safety guardrails via the Azure Content Safety API.
📄️ Bedrock Guardrails
If you haven't set up or authenticated your Bedrock provider yet, see the Bedrock Provider Setup & Authentication Guide.
📄️ CrowdStrike AIDR
The CrowdStrike AIDR guardrail uses configurable detection policies to identify
📄️ Custom Code Guardrail
Write custom guardrail logic using Python-like code that runs in a sandboxed environment.
📄️ Custom Guardrail
Use this if you want to write code to run a custom guardrail
📄️ DynamoAI Guardrails
LiteLLM supports DynamoAI guardrails for content moderation and policy enforcement on LLM inputs and outputs.
📄️ EnkryptAI Guardrails
LiteLLM supports EnkryptAI guardrails for content moderation and safety checks on LLM inputs and outputs.
📄️ Gray Swan Cygnal Guardrail
Use Gray Swan Cygnal to continuously monitor conversations for policy violations, indirect prompt injection (IPI), jailbreak attempts, and other safety risks.
📄️ Guardrails AI
Use Guardrails AI (guardrailsai.com) to add checks to LLM output.
📄️ HiddenLayer Guardrails
LiteLLM ships with a native integration for HiddenLayer. The proxy sends every request/response to HiddenLayer’s /detection/v1/interactions endpoint so you can block or redact unsafe content before it reaches your users.
📄️ IBM Guardrails
LiteLLM works with IBM's FMS Guardrails for content safety. You can use it to detect jailbreaks, PII, hate speech, and more.
📄️ Javelin Guardrails
Javelin provides AI safety and content moderation services with support for prompt injection detection, trust & safety violations, and language detection.
📄️ Lakera AI
Supported endpoints: The Lakera v2 integration only supports the chat completions endpoint (/v1/chat/completions). It is not supported for the Responses API, /v1/messages, MCP, A2A, or other proxy endpoints.
📄️ Lasso Security
Use Lasso Security to protect your LLM applications from prompt injection attacks, harmful content generation, and other security threats through comprehensive input and output validation.
📄️ Google Cloud Model Armor
LiteLLM supports Google Cloud Model Armor guardrails via the Model Armor API.
📄️ Noma Security
Use Noma Security to protect your LLM applications with comprehensive AI content moderation and safety guardrails.
📄️ Onyx Security
Quick Start
📄️ OpenAI Moderation
Overview
📄️ Pangea
The Pangea guardrail uses configurable detection policies (called recipes) from its AI Guard service to identify and mitigate risks in AI application traffic, including:
📄️ PANW Prisma AIRS
LiteLLM supports PANW Prisma AIRS (AI Runtime Security) guardrails via the Prisma AIRS Scan API. This integration provides Security-as-Code for AI applications using Palo Alto Networks' AI security platform.
📄️ PII, PHI Masking - Presidio
Overview
📄️ Pillar Security
Pillar Security integrates with LiteLLM Proxy via the Generic Guardrail API, providing comprehensive AI security scanning for your LLM applications.
📄️ In-memory Prompt Injection Detection
LiteLLM Supports the following methods for detecting prompt injection attacks
📄️ Qualifire
Use Qualifire to evaluate LLM outputs for quality, safety, and reliability. Detect prompt injections, hallucinations, PII, harmful content, and validate that your AI follows instructions.
📄️ ✨ Secret Detection/Redaction (Enterprise-only)
❓ Use this to REDACT API Keys, Secrets sent in requests to an LLM.
📄️ LiteLLM Tool Permission Guardrail
LiteLLM provides the LiteLLM Tool Permission Guardrail that lets you control which tool calls a model is allowed to invoke, using configurable allow/deny rules. This offers fine-grained, provider-agnostic control over tool execution (e.g., OpenAI Chat Completions toolcalls, Anthropic Messages tooluse, MCP tools).
📄️ Zscaler AI Guard
Overview