# I’m building **Cerbère-AG**, a security evidence layer for AI agents.

> Source: <https://dev.to/christopher_dikesa/im-building-cerbere-ag-a-security-evidence-layer-for-ai-agents-fgh>
> Published: 2026-09-26 19:27:56+00:00

[I’m building](//app.cerbereag.site) **Cerbère-AG**, a security evidence layer for AI agents.

Most AI security tools focus on what goes **into** the model: prompt injection, malicious inputs, jailbreaks, etc.

I’m focusing on what happens **after the model decides to act**.

Cerbère-AG observes and controls agent actions across tool calls, including:

The idea is simple:

**Don’t just ask whether an agent is safe to talk to. Ask whether it is safe to let it act.**

I’m looking for developers and teams running AI agents in real or realistic environments to test Cerbère-AG and tell me where it fails.

I’m especially interested in **design partners** who can give real-world feedback on agent workflows, policies, approvals, and failure cases.

If you build AI agents, security tooling, MCP integrations, or autonomous workflows:

→ Give me your feedback: what would you expect a production-grade agent security layer to catch that Cerbère currently doesn't?

And if you find the project useful, a ⭐ on GitHub helps people discover it.

I’m more interested in **breaking it and finding its weaknesses** than in compliments.

If you have an agent that you think could expose a real failure mode, send it my way.