How I stopped storing sensitive tokens in my database and built a security-first AI system
I built a multi-agent AI assistant that needed access to user data like Gmail, Google Calendar, and Notion.
At first, I thought I had it figured out.
I encrypted OAuth tokens myself and stored them in my database.
It worked… but something didn’t feel right.
The problem with “DIY security.”
During the Auth0 “Authorized to Act: Auth0 for AI Agents” hackathon, I took a step back and reviewed my setup.
My system (Londoolink AI) is built with FastAPI + LangGraph and generates personalized daily briefings using multiple agents:
- 📧 Gmail Agent
- 📅 Calendar Agent
- 📝 Notion Agent
- 📱 Social Agent
To do that, it relies on OAuth tokens.
And that’s where things got risky.
My original approach:
- AES-256 encryption for tokens
- Tokens stored in my database
- Custom refresh handling
It worked… but it wasn’t scalable or truly secure.
What I realized
I was responsible for things I shouldn’t be owning:
- 🔐 Encryption key management
- 🔄 Token refresh logic
- 📊 Audit trails (basically none)
- 👀 No visibility into token usage
- ⚠️ No proper control for sensitive actions
In short:
I was rebuilding a security system from scratch… badly.
The switch: Auth0 Token Vault
That’s when I found Auth0 Token Vault.
And it changed everything.
Instead of managing tokens myself:
- Auth0 handles token storage securely
- Built-in token refresh just works
- Full audit logs out of the box
- Tokens never touch my database
- Easy to enforce secure access patterns
It basically turns token management into a secure API call.
The result
- 🔒 More secure by design
- 📈 Easier to scale
- 🧾 Fully auditable
- 🤝 Much more user trust
Most importantly:
I stopped worrying about whether I was “doing security right” and started focusing on building features.
About the project
Londoolink AI is a multi-agent assistant that reduces information overload by generating personalized daily briefings from your connected tools.
🙌 Shoutout
Big shoutout to the Auth0 team for building tools that make secure AI development actually practical.
Read the full story
If you want the deeper breakdown, architecture details, and implementation steps, read the full post here:
Shakiran.hashnode.dev
Let’s talk
Have you built AI agents before?
How are you handling auth + token security?
I’d love to hear your approach 👇
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