If you're building LLM agents that use tools, you're probably worried about prompt injection attacks that can hijack those tools. We were too, and found that solutions like prompt-based filtering or secondary "guard" LLMs can be unreliable.
Our thesis is that agent security should be handled at the network level between the agent and the LLM, just like a traditional web application firewall.
So we built Archestra Platform: an open-source gateway that acts as a secure proxy for your AI agents. It's designed to be a deterministic firewall against common attacks. The two core features right now are:
1) Dynamic Tool Engine: This is the key idea. Archestra restricts which tools an agent can even see or call based on the context source. If the context comes from an untrusted tool, the agent won't have access to high-privilege tools like execute_code or send_email. 2) Dual LLM Sanitization: An isolated LLM acts as a "sanitizer" for incoming data, stripping potentially malicious instructions before they're passed to the primary agent.
It’s framework-agnostic (works with LangChain, N8N, etc.), self-hostable (Kubernetes). We're just getting started and have more security features planned.
We'd love for you to take a look at the repo, try it out, and give us your feedback.
