Alternatives
Products that do what AgentFirewall does
Project AI agents from unsafe actions before they execute.
- 1

- 2

- 3

blocks multi-step tool-call chains that leak data
Jun 2026 · github.com
- 4

- 5

- 6

- 7

- 8

AI-powered firewall that instantly blocks malicious Web3.
Jul 2026 · guardfast.vercel.app
- 9SY
Jul 2026 · github.com
- 10IB
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…
Jan 2026 · github.com
- 11

- 12

- 13
ArgusAI ▲7AI firewall for LLM calls, MCP tools, and agentic workflows
Jul 2026 · argusai-tau.vercel.app
- 14

Block dangerous AI agent actions before execution
Jul 2026 · relay-security-lemon.vercel.app
- 15

100% stable headless browser kit for AI Agents(Linux, macOS)
Jun 2026 · github.com
- 16
The AI agent firewall: catches hijacks that pass every rule
Jul 2026 · agentguard-dusky.vercel.app
- 17

- 18

- 19FO
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…
Mar 2026 · github.com
- 20

- 21

Stop AI agents from doing things they shouldn't.
28d ago · sanjaynandanj.github.io
- 22

- 23OS
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…
Oct 2025 · archestra.ai
- 24

Ranked by how close each launch is in meaning, then by votes. Refine with a description →