AuthorizedOps: Secure AI Agent with Token Vault

An AI agent that securely performs actions across apps using Auth0 Token Vault with user consent and approval.

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Inspiration

Most AI tools today are great at suggesting things — but they stop there. They don’t actually take action across the tools we use every day. The main limitation isn’t capability — it’s security, access, and trust.

I wanted to explore what it would look like if an AI agent could not only understand intent, but also safely act on behalf of a user — without exposing credentials or losing control.

That’s where Auth0 Token Vault becomes powerful. It enables a new model where AI agents can operate with secure, permissioned access instead of direct credentials.

Bonus Blog: https://jayapragashdakshnamurthy.substack.com/p/authorized-to-act-securing-ai-agents Demo Video: https://youtu.be/cudUaOzXxgI

Demo Access

Login using Google with the demo account:

[authorizedops.demo@gmail.com]

No password is required within the app.

This application uses Auth0 with Google OAuth, so authentication is securely delegated. All connected services (like GitHub) are user-scoped via Token Vault and do not expose personal credentials.

For full experience, refer to the demo video if login is not required.

What it does

AuthorizedOps is an AI agent that can perform real tasks across connected applications like Google Calendar, GitHub, and Slack.

For example, it can: Review your schedule for the day Analyze your GitHub pull requests and priorities Generate a structured summary Draft or send updates to Slack

The key difference is that the agent doesn’t act blindly. It first generates a plan, presents it to the user, and executes only after explicit approval. All access to external services is securely handled through Auth0 Token Vault, ensuring the agent never directly handles or stores sensitive credentials.

How we built it

AuthorizedOps is built using a modern, production-style architecture: Frontend: Next.js (App Router) for interactive UI and approval workflows Backend: Node.js API routes for orchestration and execution AI Layer: LLM-based agent (OpenAI / Claude) for planning and reasoning Authentication: Auth0 for AI Agents Token Management: Auth0 Token Vault (secure OAuth storage and access) Integrations: Google Calendar, GitHub, Slack Auth0 manages authentication and securely stores tokens, allowing the AI agent to access external APIs using scoped, short-lived permissions only when required — without exposing sensitive credentials.

Challenges we ran into

The biggest challenge was designing a system that is both powerful and secure.

  • OAuth flows across multiple providers can become complex quickly
  • Managing tokens safely without exposing them requires careful design
  • Designing a safe execution model for AI-driven actions
  • Balancing a smooth user experience with strict security boundaries

Auth0 Token Vault significantly simplified token handling and reduced the risk of insecure implementations.

Accomplishments that we're proud of

  • Built an AI agent that performs real actions, not just suggestions
  • Successfully integrated multiple external services in a secure way
  • Implemented a human-in-the-loop approval flow
  • Achieved a complete end-to-end working system within the hackathon timeline
  • Demonstrated a production-safe architecture for AI agents

What we learned

One of the biggest takeaways is that building AI agents isn’t just about the AI itself. Security, authorization, and user trust are equally critical. We also learned how complex token management and integrations can be — and how much platforms like Auth0 simplify this process. This project reinforced that the future of AI agents depends on safe execution models, not just intelligent reasoning.

What's next for AuthorizedOps: Secure AI Agent with Token Vault

There’s a lot we’d like to expand:

  • Add more integrations (Jira, Notion, email, etc.)
  • Improve approval workflows (e.g., smarter or conditional approvals)
  • Introduce detailed logging and audit trails
  • Explore partial automation with strong guardrails The long-term goal is to move toward AI agents that can reliably assist with real-world work while remaining secure, transparent, and fully under user control. AuthorizedOps demonstrates a production-ready architecture for agentic AI by separating reasoning, authorization, and execution using Auth0 Token Vault — enabling powerful automation without compromising security or user trust.

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Updates

posted an update —

Just wrapped up and submitted AuthorizedOps — Secure AI Agent with Token Vault.

I’ve always felt most AI tools stop at suggestions. They help you think, but they don’t actually do the work.

This project explores what it would take for an AI agent to safely take action across real tools like GitHub and Google Calendar.

The key focus was not just building the agent — but making it secure.

Instead of exposing credentials, everything runs through Auth0 Token Vault with scoped access and a simple approval step before execution.

Flow is straightforward: Plan → Approve → Execute

Demo: https://youtu.be/cudUaOzXxgI
Blog: https://jayapragashdakshnamurthy.substack.com/p/authorized-to-act-securing-ai-agents

Would love to hear thoughts or feedback.

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