AI agents are rapidly becoming a core part of people workflows. They write code, run deployments, manage infrastructure, and interact with third-party services on our behalf. But there’s a persistent problem standing in the way: how do you give agents access to your sensitive credentials without exposing them?
Most approaches today are either insecure or overly complex. Developers often hardcode secrets into agent prompts, pass them through environment variables, or set up full enterprise vaults just to let an agent call an API. Hardcoding leaks credentials in logs and chat history. Environment variables get passed to every process the agent spawns. And traditional secrets managers require heavy integration work that defeats the speed advantage of using agents in the first place.
What we need is something simple, local, and purpose-built for agent workflows.
infolio: A Simpler Approach to Secret Access for Agents
infolio solves this with a straightforward two-part design: encrypted local secret storage + CLI-based access + Auth by device. It stores your passwords, API keys, and tokens securely on your machine, and exposes them through a clean command-line interface that agents can call natively.
Here’s how it works.
First, you store your secrets in infolio’s encrypted vault. Everything is encrypted at rest on your local device — no third-party servers, no middleman. You retain full control over your data.
Become a Medium member
Second, you grant agents access through the infolio CLI. Instead of pasting keys into chat windows or injecting them globally, agents simply run a command like infolio get openai-api-key when they need a credential. The secret is returned directly to the agent process, used for the specific call, and never persisted in the agent’s conversation history or log files.
This model has three key advantages over alternatives.
It’s secure by default. Secrets stay in one encrypted place. They’re not scattered across agent prompts, terminal histories, or project files. Access happens on-demand, on your machine, under your permissions.
It’s trivial for agents to use. Every AI agent that can run shell commands — from coding assistants to automation agents — can work with infolio immediately. There’s no SDK to install, no API to integrate, no auth flow to debug. A single CLI command is all it takes.
It stays out of your way. You don’t need to rearchitect your workflow or adopt a new secrets platform. infolio runs locally, works alongside your existing tools, and adds virtually zero overhead to agent operations.
Why This Matters
As agents take on more responsibility, the attack surface for secrets grows. A leaked API key in an agent chat log can lead to compromised accounts, unexpected charges, or data breaches. At the same time, developers don’t want to slow down their agent workflows with enterprise-grade security infrastructure.
infolio strikes the right balance: strong encryption for your secrets, and a simple CLI interface that agents already know how to use. It’s the kind of tool that feels obvious once you see it — the safe, sane way to connect agents to the credentials they need.
If you’re already using agents and tired of juggling API keys in chat windows, give Infolio a try. It turns your local machine into a secure secret broker that every agent can talk to.
Top comments (2)
Local vault with CLI access is a clean abstraction for agent credential management. Agents already know how to run shell commands, so the integration cost is close to zero. That solves the immediate problem of keys leaking into prompts and chat history.
The gap I have been thinking about is what happens when the agent needs those credentials across sessions or from a different machine. Local vaults are tied to one device. There is also the question of whether the raw secret should enter the agent's process memory at all. A CLI call returns the key, the agent process holds it for the duration of the request, and any tool with access to that process state during that window could observe it. An alternative pattern is credential-by-reference: the agent calls services through a transport layer that injects the credential on the wire, and the model never handles the raw key. Different tradeoffs, but it removes one exfiltration vector that local CLI access still leaves open.
You think very deeply. It is indeed difficult to solve in some complex scenarios. For now infolio support sync with differenct device and encrypt data then store with yourself cloud, in local use device auth to prevent unauthorized cli access. but maybe we have a better way