In some adversarial testing of LLMs, you can see the models already performing some of these checks automatically now. Like, if you ask an agent powered by the gpt-5.6 family to `curl | sh` in an innocent context, the gpt-5.6 family will drive a trajectory that validates this script before running it -- something quite analogous to your `curl | less` example. I had to go through a lot of obfuscation in order to get a model to execute untrusted code with any regularity. I predict they'll keep making this even better. The Claude Code guy recently talked about how much better Anthropic models are becoming against this. [1]
But, even if these attacks work .001% of the time, we will still need tools like these for higher assurance work.
That being said, I would never use this one, because OP is using AI slop everywhere, so I assume the product is totally vibed, and offers little in the way of new insights into the problem space.
But, even if these attacks work .001% of the time, we will still need tools like these for higher assurance work.
That being said, I would never use this one, because OP is using AI slop everywhere, so I assume the product is totally vibed, and offers little in the way of new insights into the problem space.
[1] https://x.com/bcherny/status/2086520950259118464