Why your AI coding agent should never see your API keys

A developer has released Trustless, an open-source CLI that prevents AI coding agents from exposing API keys and other secrets. The tool injects credentials into subprocesses while sanitizing output, proxies HTTP requests with per-host credentials, and scans outbound LLM calls for secret patterns. It addresses the risk that agents, which read source and config and transmit summaries to third-party APIs, can leak secrets through prompt injection or verbose logs.

Your AI coding agent needs your API keys. It needs them to call services, to test integrations, to run your stack. So you give it .env files, or you export keys into the environment, or you paste them into config files the agent can read. That means your secrets live inside the agent's context window — the same window where a prompt-injected instruction or an overly verbose debug log can leak them to an attacker or an untrusted model endpoint. This isn't theoretical. If you've used Claude Code or OpenCode for more than a few days, you've probably seen a tool call dump an environment variable, or a log line that echoes a connection string. Most of the time nothing bad happens. "Most of the time" is a bad security posture. AI agents are the first software that reads your source, your config, and your secrets , then sends summaries of what it read to a third-party API. With traditional software, the principle was simple: secrets live in the process environment, code reads them at runtime, nobody reads them back out. With agents, there is no such boundary — the agent both reads the environment and transmits what it knows. Three concrete leak vectors: .env and includes values in a later prompt to an external model. You can't audit this; it's in the model's training/inference pipeline.The solutions fall into a few buckets: .env hidingI ended up building a small CLI Go, zero external deps with three layers: Subprocess injection with output sanitization. trustless run -- cmd resolves secrets from my existing pass store and injects them as env vars. After the command runs, stdout/stderr is scanned and secret values are replaced — including base64 and URL-encoded variants. The agent sees the command output, not the keys. HTTP proxy with per-host injection. For services that take headers or query params EDINET, e-Stat, xAI, OpenRouter , trustless proxy injects the right credential per host. The agent points at 127.0.0.1:8080 and forgets about keys entirely. DLP reverse proxy for LLM calls. trustless serve puts a scanning proxy in front of OpenAI-compatible endpoints. Outbound requests are checked against secret patterns keyword → regex → entropy, gitleaks-compatible rules and masked in-flight before they leave the machine. This is the layer that catches the "agent decided to include the key in a request" case. Why not a new vault? Because I already had pass. The CLI reads the existing store, so there was zero migration. Bitwarden is supported too, with OAuth token auto-refresh for Google/Lark. The agent gets capabilities, not credentials. That's the whole trick. If you want to look at the code: trustless is MIT-licensed at https://github.com/ikkun1222/trustless https://github.com/ikkun1222/trustless — 321 tests, race-detector clean, cosign-signed releases. It's one implementation of this model; the threat model discussion is more valuable than the tool itself.