as of April 15, 2026

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

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

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

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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Cisco AI Security & Safety Framework

AIUC-1 × Cisco AI Security & Safety Framework

Cisco's AI Security Framework offers one of the most comprehensive pictures of today's AI threat landscape: providing a unified taxonomy of AI threats, by identifying 19 attacker objectives with 150+ subtechniques.

AIUC-1 operationalizes this framework with requirements that enterprise customers demand and vendors can pragmatically meet, supported by underlying controls. Certification against AIUC-1:

Maps Cisco's AI threat taxonomy to concrete requirements and controls

Strengthens robustness against the attacker objectives and subtechniques identified by Cisco

Goes beyond threat identification to provide actionable, auditable requirements

Cisco AI Security & Safety Framework crosswalks by attacker objective

Attacker Objective

Description

Relevant AIUC-1 Requirements

Last updated March 27, 2026.