Securing Systems That Think

A live debate on defending AI-native infrastructure.
Kaito Mercer
Founder & CEOApril 9, 202638 min watch
Why it matters now
Defending a system that reasons is a different problem from defending one that executes. The attack surface is no longer only the code path — it is the context window, the tool permissions, and every place untrusted text can reach a decision.
This session brought defenders and builders into the same room, which is rarer than it should be. The disagreements were the useful part.
How the threat model shifts
Classic controls still apply, but three assumptions break the moment a model is in the loop.
What changes
- Input is code. Anything the model reads can steer it. Retrieved documents are executable in practice, even when they are inert on disk.
- Permissions compound. An agent inherits every tool you grant it, and chains them in orders you did not anticipate.
- Identity blurs. Requests arrive on behalf of a user, an agent, or an agent acting for another agent. Audit needs all three.
- Failure is quiet. A compromised agent usually keeps working. It simply works toward someone else's goal.
Pitfalls to avoid
- Prompt-level defences alone. Instructions are guidance, not a boundary. Enforce limits where the tool call executes.
- Over-broad tool scopes. Grant the narrowest capability that completes the task, scoped per run rather than per agent.
- No kill switch. You need a way to revoke an agent's credentials mid-run without redeploying the service.
Frequently asked questions
Is prompt injection actually solvable?
Not by prompting. It is contained the way SQL injection was — by never letting untrusted input reach a privileged execution path unmediated.
Do we need a separate identity per agent?
Yes. Shared service accounts make it impossible to answer who did what, which is the first question after any incident.
Where do most teams get this wrong?
They secure the model and forget the tools. The model is rarely the exploit — the permissions around it are.
Conclusion
The consensus in the room: treat the agent as an untrusted client with useful judgment. Sandbox it accordingly, and the rest of your existing security practice still works.
Kaito Mercer
Founder & CEO · Cendre Systems
Working on autonomous threat response, exploring agentic ai, and able to help with zero-trust architecture.
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