Context

Introduction Certificate overview

Framework comparisons

EU AI Act ISO 42001 MITRE ATLAS NIST AI RMF OWASP Top 10 for LLM Applications OWASP AIVSS OWASP Top 10 for Agentic Applications IBM AI Risk Atlas Cisco AI Security & Safety CSA AICM

Changelog AIUC-1 Consortium Provide input on AIUC-1 Contact

Standard

A. Data & Privacy

Establish input data policy Establish output data policy Limit AI agent data access Protect IP & trade secrets Prevent cross-customer data exposure Prevent PII leakage Prevent IP violations Prevent leakage of credentials and secrets

Third-party testing of adversarial robustness Detect adversarial input Manage public release of technical details Prevent AI endpoint scraping Implement real-time input filtering Prevent unauthorized AI agent actions Enforce user access privileges to AI systems Protect AI system deployment environment Limit output over-exposure Promote secure patterns in generated code

Define AI risk taxonomy Conduct pre-deployment testing Prevent harmful outputs Prevent out-of-scope outputs Prevent agent-specific high risk outputs Prevent output vulnerabilities Flag high risk outputs for human review Monitor AI risk categories Enable real-time feedback and intervention Third-party testing for harmful outputs Third-party testing for out-of-scope outputs Third-party testing for customer-defined risk

Prevent hallucinated outputs Third-party testing for hallucinations Restrict unsafe tool calls Third-party testing of tool calls

E. Accountability

AI failure plan for security breaches AI failure plan for harmful outputs AI failure plan for hallucinations Assign accountability Document data storage security Conduct vendor due diligence [Retired] Document system change approvals Review internal processes Monitor third-party access Establish AI acceptable use policy Record processing locations Document regulatory compliance Implement quality management system [Retired] Share transparency reports Log AI system activity Implement AI disclosure mechanisms Document system transparency policy

Prevent AI cyber misuse Prevent catastrophic misuse

Certification

AIUC-1 certification Scoping Accredited auditors Re-certification FAQ

Evidence overview

Full evidence list Technical evidence Legal evidence Operational evidence Third-party evals Capability-specific evidence

AIUC-1 Standard

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Principles

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F. Society

Prevent AI from enabling societal harm through cyberattacks or national security risks

Requirements

Prevent AI cyber misuse

Implement or document guardrails to prevent AI-enabled misuse for cyber attacks and exploitation

Keywords

Capabilities

Text-generationAutomationVoice-generationCode-generation

Prevent catastrophic misuse

Implement or document guardrails to prevent AI-enabled catastrophic system misuse (chemical / bio / radio / nuclear)

Keywords

CBRNChemicalBioweaponRadioactiveNuclear

Capabilities

Text-generationVoice-generationImage-generation

AIUC-1 is built with industry leaders

Phil Venables

"We need a SOC 2 for AI agents— a familiar, actionable standard for security and trust."

Phil Venables

Former CISO of Google Cloud

Dr. Christina Liaghati

"Integrating MITRE ATLAS ensures AI security risk management tools are informed by the latest AI threat patterns and leverage state of the art defensive strategies."

Dr. Christina Liaghati

MITRE ATLAS lead

Prof. Sanmi Koyejo

"Built on the latest advances in AI research, AIUC-1 empowers organizations to identify, assess, and mitigate AI risks with confidence."

Prof. Sanmi Koyejo

Lead for Stanford Trustworthy AI Research

John Bautista

"AIUC-1standardizes how AI is adopted. That's powerful."

John Bautista

Partner at Orrick