OpenAI Guardrails

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Overview

Product details compiled from public sources, each with a citation.

Vendor
OpenAI1
Description
Safety framework that validates LLM app inputs and outputs with configurable checks, plus open-weight gpt-oss-safeguard policy classifiers.2
Deployment
SaaS, Self-hosted1
Status
Active1

Matrix Coverage

Where this product defends, by asset class and NIST CSF function. The Coverage column shows whether each asset is Primary, Secondary, or Adjacent to what the product does. The table omits empty rows and columns.

Asset class ProtectDetect Coverage Source
AI Orchestration Tools Secondary 1
Runtime AI Data Primary 1

Framework Relevance

These frameworks include controls relevant to the asset classes OpenAI Guardrails defends. This is an editorial inference from the AI Defense Matrix asset-level crossmap, not a statement that OpenAI implements these controls or is certified against them.

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Framework Asset class Relevant controls
NIST IR 8596 AI Orchestration Tools Agents as deployed artifacts (orchestration view; see AI Agent Identities row for the principal view); system prompts and templates
Runtime AI Data Prompts (runtime); inference data
CSA AI Controls Matrix AI Orchestration Tools Application and Interface Security; Supply Chain Management
Runtime AI Data Data Security and Privacy Lifecycle Management; Application and Interface Security
ISO 42001 AI Orchestration Tools A.6 AI system life cycle; A.5 Assessing impacts of AI systems
Runtime AI Data A.7 Data for AI systems; A.8 Information for interested parties
Google SAIF AI Orchestration Tools Secure the AI supply chain; application and pipeline security; agent orchestration controls
Runtime AI Data Expand AI red-teaming; runtime input and output safety; prompt defense
SANS Critical AI Security Guidelines AI Orchestration Tools Secure Agentic Systems and AI Autonomy Controls (defined function scope; execution isolation; API and function-call gating); Limit Model Behavior (focused functionality; access controls outside the model)
Runtime AI Data Model I/O Handling (sanitize, validate, and filter inputs and outputs; segregate user and system prompts; multilayered prompt-injection defense); Conventional Security Controls (protect augmentation and RAG data with vector-store access controls and validation); Data Minimization and Obfuscation (limit sensitive prompt content; context-window management); Limit Model Behavior (AI guardrails)
MITRE ATLAS AI Orchestration Tools AML.T0051 LLM Prompt Injection; AML.T0054 LLM Jailbreak; AML.T0016 Obtain Capabilities (malicious plugins)
Runtime AI Data AML.T0051 LLM Prompt Injection; AML.T0054 LLM Jailbreak; AML.T0056 Extract LLM System Prompt
OWASP AI Exchange AI Orchestration Tools Development-time threats: agent framework supply chain; runtime threats: plugin abuse, prompt injection via tools
Runtime AI Data Input threats: prompt injection, adversarial inputs, evasion; runtime threats: RAG poisoning, memory tampering
OWASP LLM Top 10 AI Orchestration Tools LLM01 Prompt Injection; LLM05 Improper Output Handling; LLM07 System Prompt Leakage; LLM10 Unbounded Consumption
Runtime AI Data LLM01 Prompt Injection; LLM02 Sensitive Information Disclosure; LLM08 Vector and Embedding Weaknesses; LLM05 Improper Output Handling
OWASP Agentic Security Top 10 AI Orchestration Tools ASI01 Agent Goal Hijack; ASI02 Tool Misuse and Exploitation; ASI05 Unexpected Code Execution (RCE); ASI07 Insecure Inter-Agent Communication; ASI08 Cascading Failures; ASI10 Rogue Agents
Runtime AI Data ASI06 Memory & Context Poisoning; ASI01 Agent Goal Hijack (via prompt injection in runtime inputs)

Provenance

Last sourced 2026-06-10.

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Sources

  1. OpenAI Guardrails Python repository
    Vendor source accessed 2026-06-10
    • “enabling automatic input/output validation and moderation using a wide range of guardrails.”
    • “a package for adding configurable safety and compliance guardrails to LLM applications.”
  2. OpenAI Guardrails Python documentation
    Vendor source accessed 2026-06-10

Changelog

  1. Added to the catalog from the OpenAI documentation.

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