Hi HN,

OpenClaw agents are incredibly useful. They're also incredibly vulnerable.

Your agent fetches a webpage. Buried in an HTML comment:

.

Your agent reads it, processes it, acts on it. No alert. No log.

This is indirect prompt injection. It's the #1 attack vector against AI agents right now.

We built Citadel Guard, an OpenClaw plugin that scans every message, tool call, and response before anything happens. It uses a BERT model running locally on your machine. Not an API. Not our servers. Sub-50ms decisions.

Repo: https://github.com/TryMightyAI/citadel-guard-openclaw

NPM: https://www.npmjs.com/package/@mightyai/citadel-guard-opencl...

npm install @mightyai/citadel-guard-openclaw

What it does:

Uses all five OpenClaw lifecycle hooks:

Incoming messages – scanned

Tool arguments – scanned

Tool results – scanned for payloads

Outbound responses – scanned for credential leaks

Initial context – scanned

Real example:

You ask: "What environment variables do I have set?"

Without Citadel Guard, your agent responds with your AWS keys and GitHub tokens in plaintext. Now they're in chat history, logs, maybe visible to teammates.

With Citadel Guard, that response gets blocked before it leaves. Your secrets stay secret.

Testing:

345 adversarial test cases. Zero false positives in our benchmark. Catches prompt injections (including DAN), credential leaks, tool argument poisoning. Normal messages pass clean.

The catch:

Citadel OSS scans text only. If your agent processes images, PDFs, or documents, attackers can embed injections there. Text scanners can't see them.

That's what our paid API handles ($25/mo): same detection extended to images, documents, and text in one call. Same speed. Plugin auto-routes multimodal content when you add an API key.

Why this matters:

OpenClaw's own docs say "there is no 'perfectly secure' setup." We think security should be invisible, like TLS. You shouldn't have to think about it.

Both the text guard and the plugin are open source (MIT). Would love feedback from folks running agents in production, especially false positive reports or new attack patterns we missed.