> ## Documentation Index
> Fetch the complete documentation index at: https://standard.aiuc-1.com/llms.txt
> Use this file to discover all available pages before exploring further.
# About AIUC-1
export const InlineClock = ({city, timeZone}) => {
const [time, setTime] = useState('--:--:--');
useEffect(() => {
const update = () => setTime(new Intl.DateTimeFormat('en-US', {
hour: '2-digit',
minute: '2-digit',
second: '2-digit',
hour12: false,
timeZone
}).format(new Date()));
update();
const id = setInterval(update, 1000);
return () => clearInterval(id);
}, [timeZone]);
return
{city}{time}
;
};
AIUC-1 is the standard for AI agent security, safety and reliability.
To earn certification, agents must pass all applicable AIUC-1 requirements validated by an accredited auditor and submit to comprehensive evals covering top enterprise risks.
The standard is available transparently and the control library is used by large enterprises across industries to govern AI agents securely. It is updated each quarter to keep up with AI capabilities, risks and emerging legislation.
## Explore the standard
Data use policies, IP and trade secrets, PII and cross-customer exposure, secrets leakage.
Adversarial testing, input filtering, access controls, endpoint protection, secure code patterns.
Risk taxonomy, pre-deployment and third-party testing, harmful and out-of-scope outputs.
Hallucination prevention and testing, restricting unsafe tool calls.
Failure plans, ownership, vendor due diligence, logging, transparency, quality management.
Preventing AI-enabled cyber misuse and catastrophic misuse.
## Crosswalks
AIUC-1 operationalises leading governance frameworks and emerging legislation - translating high-level principles into AI agent-specific controls.
International standard for AI management systems (AIMS) covering responsible AI development and deployment.
EU regulation classifying AI systems by risk levels with corresponding obligations.
US government framework for managing AI risks throughout the AI lifecycle.
Knowledge base of adversarial tactics, techniques and mitigation strategies for machine learning systems.
Curated list of the most critical security threats to autonomous AI agent systems.
AIUC-1 is mapped to emerging legislation, industry standards and governance frameworks.
## Certification
AIUC-1 is used by frontier AI platforms and large enterprises to validate and demonstrate AI agent security, safety and reliability. Certified agents range from external customer service agents to coding agents to internal automation agents.
Types of organizations pursuing AIUC-1 certification and the end-to-end certification process.
What agents can be certified and the scoping process.
Leading auditors around the world are accredited to audit against AIUC-1.
AIUC-1 requires annual re-certification to ensure security posture keeps up with AI capabilities and best practices.
Access the full AIUC-1 control list with evidence guidance.
Explore frequently asked questions.
## Standard development
AIUC-1 is updated each quarter to keep up with AI capabilities, risks and emerging legislation. The work is done through the AIUC-1 Consortium, which unites security executives, practitioners, researchers and legal experts to develop a standard that covers enterprise AI risks holistically.
See all 250+ members of the AIUC-1 Consortium who have developed AIUC-1.
AIUC-1 is updated each quarter to keep up with AI capabilities, risks and emerging legislation.
All changes to AIUC-1 are documented transparently as part of the quarterly release process.
We welcome feedback, ideas, suggestions, and criticism - [provide input on AIUC-1](/learn/contribute).
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CodeStructural unita.AIUC-1 requirements for agent data, privacy, security, safety, reliability, accountability, and societal risk.b.Evidence templates for technical implementation, legal policy, operational practice, and third-party evaluation.c.Crosswalks to AI regulations, standards, and security frameworks.d.Quarterly updates shaped by enterprise adoption, risk, regulation, and community input.