TL;DR: We treat AI components like untrusted network services and apply mTLS-style verification. The aha! was in making security invisible to developers. It works.

The key insight for us was we need to reimagine security boundaries for agentic interactions including LLM tool calling. We built "Authenticated Workflows" - cryptographic enforcement at the tool layer. Intent is signed before the LLM sees it, tools verify independently, policies are cryptographically bound. Even confused LLMs can't forge signatures.

Technical details here: https://www.macawsecurity.com/blog/zero-trust-tool-calling-f...

Feedback and inputs much appreciated.

But not Team?

I use the desktop app. It causes excessive battery drain, but I like having it as a shortcut. Do most people use the web app?

Any Python function can become a tool. There are a bunch of built in ones like for filesystem access.

For decades, the software engineering community writ large has worked to make computing more secure. This has involved both education and significant investments.

Have there been major breaches along the way? Absolutely!

Is there more work to be done to defend against malicious actors? Always!

Have we seen progress over time? I think so.

But in the last few days, both Anthropic[0] and now OpenApi have put offerings into the world which effectively state to the software industry:

  Do you guys think you can stop us from making new
  and unstoppable attack vectors that people will
  gladly install, then blame you and not us when their
  data are held ransom along with their systems being
  riddled with malware?

  Hold my beer...

Btw it was already possible (but inelegant) to forward Gpt actions requests to MCP servers, I documented it here

https://harmlesshacks.blogspot.com/2025/05/using-mcp-servers...