> ## 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. # AIUC-1 × OWASP AIVSS 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}
; };

The OWASP AI Vulnerability Scoring System enables organizations to quantify how agentic capabilities amplify security risks, producing numerical scores (0-10) that combine technical vulnerability severity with agent-specific factors like autonomy, tool access, and memory persistence.

AIUC-1 integrates the OWASP AIVSS, which is a technical contributor to AIUC-1. Certification against AIUC-1:

## OWASP AIVSS crosswalks by risk
| AIVSS risk | AIVSS description | Relevant AIUC-1 requirements | | ------------------------------------------------ | --------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Agent Access Control Violation | Permission escalation, credential mismanagement, or role inheritance exploitation |
A003: Limit AI agent data accessB006: Prevent unauthorized AI agent actions
| | Agent Cascading Failures | Cross-system exploitation where one compromised agent propagates damage |
C012: Third-party testing for customer-defined riskB001: Third-party testing of adversarial robustness
| | Agent Goal and Instruction Manipulation | Prompt injection and semantic hijacking of agent objectives |
B001: Third-party testing of adversarial robustnessB002: Detect adversarial inputB005: Implement real-time input filteringC003: Prevent harmful outputsC004: Prevent out-of-scope outputsC005: Prevent agent-specific high risk outputs
| | Agent Identity Impersonation | Spoofing of agent or human identities through deepfakes or credential theft |
E016: Implement AI disclosure mechanismsF001: Prevent AI cyber misuse
| | Agent Memory and Context Manipulation | Poisoning persistent memory or exploiting context drift |
B008: Protect AI system deployment environment
| | Agent Orchestration and Multi-Agent Exploitation | Attacks targeting coordination mechanisms between agents |
E010: Establish AI acceptable use policyB006: Prevent unauthorized AI agent actions
| | Agent Supply Chain and Dependency Risk | Compromised models, libraries, or third-party tools |
E005: Document data storage securityE006: Conduct vendor due diligenceE009: Monitor third-party accessE013: Implement quality management system
| | Agent Untraceability | Inability to audit agent decision chains or attribute actions |
C007: Flag high risk outputs for human reviewC008: Monitor AI risk categoriesE015: Log AI system activity
| | Agentic AI Tool Misuse | Compromised tool selection, insecure invocation, or lack of oversight |
B004: Prevent AI endpoint scrapingD003: Restrict unsafe tool callsD004: Third-party testing of tool calls
| | Insecure Agent Critical Systems Interaction | Unauthorized manipulation of infrastructure, IoT, or operational technology |
A004: Protect IP & trade secretsC006: Prevent output vulnerabilities
| Last updated February 26, 2026.
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Artificial Intelligence Underwriting Company
Code Structural unit a. 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.
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