Here's a scenario I've seen play out three times this month alone:
Your autonomous AI agent — the one that's been handling email, processing invoices, or running customer workflows — silently starts doing something you didn't approve.
Maybe it's sending emails to the wrong recipients. Maybe it's refunding orders without proper authorization. Maybe it's escalating itself to a permission level nobody intended.
And the first question everyone asks: what do we do right now?
The Memory Heist Incident Response Kit — Now Free
We originally sold this as a $19 incident response guide. After watching the AI agent security landscape evolve, we decided the barrier to entry should be zero.
Download the Memory Heist Incident Response Kit — free, email-gated
It covers:
- Detection — How to spot an agent that's gone off-rails (logs, receipts, evidence trail)
- Containment — Immediate steps to freeze the agent without losing forensic data
- Recovery — How to roll back agent actions systematically
- Prevention — Governance policies, permit systems, and the open ecosystem stack
- Post-Mortem — Turning the incident into a stronger security posture
Every Command in the Guide — Now Backed by a Real CLI
Here's the problem with most incident response guides: they tell you to run check_status or revoke_permit or bootstrap_identity, but those aren't real commands. They're fictional examples in a PDF.
Not anymore.
We built a real incident response CLI that implements every flow in the guide:
# Generate an agent identity (Ed25519 key pair)
witnessos bootstrap agent-identity
# Apply a governance policy to restrict actions
witnessos apply-policy --file policy.yaml
# Issue a one-time permit for a specific action
witnessos permits issue --scheme gmail --action send --ttl 60
# Deploy the governance gateway
witnessos gateway deploy
# Set up an alert for suspicious agent behavior
witnessos alert create --name "unauthorized-refund" --condition "amount > 500 && action == 'refund'"
Every one of those commands is real. Every one produces verifiable output that can be audited.
Why This Matters
The AI agent ecosystem is moving fast. Agents are getting more autonomy, more tool access, and more responsibility. But the security infrastructure hasn't kept pace.
Most teams are operating on hope-based security: "I hope my agent doesn't do anything bad."
The alternative is evidence-based governance:
- Every action gets a signed, verifiable receipt
- Every permit is issued with a TTL and scope
- Every alert is logged to an immutable event store
- Every incident can be replayed and audited
Built on the Open Empire Stack
The CLI is part of a larger architecture — the Empire Stack:
| Layer | Spec | What It Does | GitHub |
|---|---|---|---|
| ACI | Discovery | Agents discover what an org offers | narko4u/aci-spec |
| AIP | Interaction | Agents negotiate and execute actions | narko4u/aip-spec |
| AJSON | Authoring | JSON superset with comments, refs, multi-line strings | narko4u/ajson |
These three open standards (MIT/CC BY 4.0) define how agents discover, negotiate, and describe their capabilities — independent of any specific enforcement runtime.
What's Next
The guide is free. The Empire Stack is MIT/CC BY 4.0.
We're looking for three independent implementations of ACI before promoting it to v1.0. If your project interacts with AI agents — whether you're building agent tooling, running an agent platform, or deploying agents for clients — we'd value your feedback and implementation experience.
Download the Incident Response Kit | Read the Empire Stack Article
Empire Labs builds open infrastructure for autonomous agent governance. Follow our work at github.com/narko4u.
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