Alternatives
Products that do what PromptGuard does
The firewall for AI prompts. Drop-in security for LLM apps.
- 1
Prompt-injection firewall for prod LLM apps
Jul 2026 · insightits.com
- 2OS
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
- 3
- 4
- 5
- 6
- 7
- 8
- 9
Block malicious web content before it reaches your AI.
Jan 2026
- 10
- 11
- 12
- 13
- 14
- 15
"Your LLM's last line of defence against the internet."
May 2026 · wonderwallai.skintlabs.ai
- 16
- 17
- 18LC
2023 · github.com
- 19
Just stop jailbreaks & prompt hacks with one API call.
Sep 2025
- 20IM
2024 · github.com
- 21IB
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
- 22
- 23
- 24PI
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…
Feb 2026 · github.com
Ranked by how close each launch is in meaning, then by votes. Refine with a description →