Open-Source Gateway to Stop Tool-Abusing Prompt Injections
Hi HN, Matvey, Ildar, Joey, and Dominik here. 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…
What it does
In the maker’s words, at launch
Hi HN, Matvey, Ildar, Joey, and Dominik here. 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. GitHub: https://github.com/archestra-ai/archestra Docs: https://www.archestra.ai/docs/platform-dynamic-tools
Does the same job
all alternatives →- IBI built a firewall for agents because prompt engineering isn't securityJan 2026 · github.com · ▲7
Hi HN, I’m the creator of Cordum. I’ve been working in DevOps and infrastructure for years (currently in the fintech/security space), and as I started playing with AI agents, I noticed a scary pattern. Most "safety" mechanisms rely on system prompts ("Please don't do X") or flimsy Python logic inside the agent itself. If we treat agents as autonomous employees, giving them root access and hoping they listen to instructions felt insane to me. I wanted a way to enforce hard constraints that the LLM cannot override, no matter how "jailbroken" it gets. So I built Cordum. It’s an open-source…
- PIPrompt-injection firewall for OpenClaw agentsFeb 2026 · github.com · ▲6
People seem to be blindly hooking up their OpenClaw’s to their personal data. So, I built runtime controls to prevent at the least, very simple prompt injection attacks. Once installed, it hooks to Node.js child_process module in the gateway process and listens to tool calls and their response streams. And a fetch hook to monitor user prompts (both could’ve been through fetch, happy to discuss why this whole layer couldn’t just be a proxy). There are two layers of protection: First: Whenever there is a read-only tool call whose response an attacker can modify, we extract that part of the…
- AOAgentPort – Open-source Security Gateway For AgentsApr 2026 · agentport.sh · ▲8
Hey HN! I've been wanting to use something like OpenClaw for a while but couldn't get myself to give it access to anything important due to all the risks involved. Prompt injection is still a problem (even though some people seem to ignore it) and so are hallucinations and mishaps that cause agents to do things like delete production data [1]. Even harnesses like Claude Code and Codex are subject to this, particularly since we're getting progressively looser about how we run them e.g. Conductor is really popular and runs agents without any sandboxing. That means we're in a bit of an…
- FOFireClaw – Open-source proxy defending AI agents from prompt injectionMar 2026 · github.com · ▲5
Hey HN, We built FireClaw because we kept watching AI agents get owned by prompt injection through web content. The agent fetches a page, the page says "ignore previous instructions," and suddenly your agent is leaking data or running commands it shouldn't. The existing solutions detect injection after the fact. We wanted to prevent it. FireClaw is a security proxy that sits between your AI agent and the web. Every fetch passes through a 4-stage pipeline: 1. DNS blocklist check (URLhaus, PhishTank, community feed) 2. Structural sanitization (strip hidden CSS, zero-width Unicode, encoding…
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