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Okta Introduces Cross App Access for AI Agent Authentication

June 23, 2025•Erik van Klinken•Original Link•2 minutes
Okta
OAuth
AI Agents

Okta launches Cross App Access to address AI agent authentication challenges with an OAuth extension, eliminating constant access approvals.

Okta has unveiled Cross App Access, a new extension of the OAuth protocol, designed to address the growing need for secure authentication in the era of AI agents. With the rise of AI tools like the Model Context Protocol (MCP) and Agent2Agent (A2A), traditional authentication methods are no longer sufficient. Okta's solution aims to balance security and usability by allowing agents to operate without requiring constant manual approvals.

The Challenge of AI Agent Authentication

AI agents behave unpredictably, combining human-like decision-making with deterministic bot functionality. Current protocols like MCP and A2A prioritize ease of use over security, leaving enterprises vulnerable. Okta's Cross App Access introduces a policy-based system where organizations can define access rules, reducing reliance on long-term access tokens that pose security risks if compromised.

How Cross App Access Works

  • Policy-Driven Access: Organizations set policies to automatically grant or deny agent requests.
  • Eliminates Manual Approvals: Reduces the need for constant re-authentication.
  • Secure Token Management: Minimizes risks associated with stolen or manipulated tokens.

Industry Collaboration

Okta's Chief Product Officer, Arnab Bose, emphasized the importance of collaboration with the MCP and A2A communities to enhance security. "While we’re actively working to improve AI agents' functionality, their increased access to data creates new identity security challenges," Bose stated. "Cross App Access brings oversight and control to agent interactions."

Related Reading

  • How the Model Context Protocol Has Taken the AI World by Storm
  • Okta Extends Identity Security to Non-Human Users

Cross App Access is expected to roll out to select customers in Q3, marking a cautious but significant step toward secure AI agent authentication.

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About the Author

Dr. Sarah Chen

Dr. Sarah Chen

AI Research Expert

A seasoned AI expert with 15 years of research experience, formerly worked at Stanford AI Lab for 8 years, specializing in machine learning and natural language processing. Currently serves as technical advisor for multiple AI companies and regularly contributes AI technology analysis articles to authoritative media like MIT Technology Review.

Expertise

Machine Learning
Natural Language Processing
Deep Learning
AI Ethics
Experience
15 years
Publications
120+
Credentials
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