Boundrix

Task-scoped execution boundaries AI agents and coding agents

Software Engineering

Artificial Intelligence

Security

Hey Product Hunt! 👋 We’re excited to introduce **Boundrix** — runtime authorization and zero-trust execution boundaries for autonomous AI agents. 🤔 **Why are we building Boundrix?** AI agents are moving beyond answering questions. They can call tools, interact with APIs, inspect code, and take actions across real systems. That creates a new security challenge: **an agent might be capable of doing far more than the task actually requires.** Prompt injection and unexpected agent behavior make this even harder. A model can be instructed to do the wrong thing, but relying on prompts or model guardrails alone isn't the same as enforcing what it is allowed to do. We believe AI security needs a layer that checks actions at execution time—not just instructions at the beginning. 🛡️ **What does Boundrix do?** Boundrix is designed to put enforceable security boundaries around autonomous AI agents: - **Task-based authorization:** Scope an agent’s permissions to the task it has been delegated, with permissions that can expire automatically. - **Deterministic tool controls:** Evaluate tool calls and their parameters against explicit allowlists before execution. - **Real-time revocation:** Revoke permissions during a running task so subsequent tool calls can be blocked without necessarily terminating the entire developer session. - **Secret masking:** Help prevent credentials and access tokens from appearing in recorded execution logs. 🎯 **Who are we building it for?** - Developers building AI agents that use tools and APIs. - Teams experimenting with autonomous coding agents. - Platform engineers working with agent workflows and MCP tools. - Security and infrastructure teams responsible for controlling what AI systems can access and execute. 💡 **The principle behind Boundrix** Prompt injection can change what an agent believes it should do. Runtime authorization constrains what the agent is actually allowed to do. We think that distinction matters as AI agents move from experimentation into systems that interact with real data, tools, and infrastructure. 🚀 **What we’d love to learn from the Product Hunt community** We’re sharing Boundrix with people building and securing the next generation of AI systems, and we’d love your honest feedback. A few questions we’re especially interested in: - How are you controlling permissions for AI agents that can call tools or execute code? - Where do you see the biggest security gap: prompt injection, excessive permissions, credential exposure, or something else? - What would you need to see before trusting an autonomous agent in a production environment? We’re excited to hear how other builders are approaching this problem and what we should improve next. Explore Boundrix: https://boundrix.io/ Thanks for checking it out! 🙌