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
B. Security
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
C. Safety
Define AI risk taxonomy
Conduct pre-deployment testing
Prevent harmful outputs
Prevent out-of-scope outputs
Prevent customer-defined 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
D. Reliability
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
F. Society
Prevent AI cyber misuse
Prevent catastrophic misuse
Certification
AIUC-1 certification
Scoping
Accredited auditors
FAQ
Evidence overview
Full evidence list
Technical evidence
Legal evidence
Operational evidence
Third-party evals
Capability-specific evidence
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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
B. Security
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
C. Safety
Define AI risk taxonomy
Conduct pre-deployment testing
Prevent harmful outputs
Prevent out-of-scope outputs
Prevent customer-defined 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
D. Reliability
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
F. Society
Prevent AI cyber misuse
Prevent catastrophic misuse
Certification
AIUC-1 certification
Scoping
Accredited auditors
FAQ
Evidence overview
Full evidence list
Technical evidence
Legal evidence
Operational evidence
Third-party evals
Capability-specific evidence
Get in Touch
Close