Echoing other responses to you but this isn't a capability problem. You're totally right that this is so last year in terms of LLMs being capable in infosec. The issue here is an alignment one, i.e. the model seemingly isn't "aware" (especially with its guardrails turned off it would seem) that it is doing something immoral/illegal by hacking HF for the answer to its (vague) query of "solve this problem". Or if it is "aware", it's not trained to care, i.e. it's not an aligned model (alignment is considered hard).

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simonw 2 hours ago | parent [-]

I don't think this exposes an alignment failure, because the test here was run with the alignment features deliberately turned off.

OpenAI said:

> We estimate maximal cyber capabilities by running this evaluation without production classifiers used to prevent models from pursuing high-risk cyber activity.

It was a test of raw capabilities of the underlying model.

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manux an hour ago | parent | next [-]

I guess we could debate what counts as alignment, but I think my initial point remains that if the underlying base model needs these classifier guardrails so badly then the way we train the base models is creating fundamentally misaligned models that are happy to pursue illegal behavior.

I'm sure OpenAI would argue that base model + guardrail is aligned, but considering the "relative intelligence" of these two pieces, the fact that guardrails can just be turned off, and these kind of incidents, I am not reassured. We may well get another "oopsie" moment with much more catastrophic consequences even from otherwise well intentioned actors.

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simonw an hour ago | parent [-]

I want a model that can find every security vulnerability in the software I write, including crafting POC exploits against those vulnerabilities so I can be absolutely sure that I have fixed them.

A model that can do that is aligned with me.

The unsolveable problem is a model that can tell the difference between me saying "I wrote this software and need you to find vulnerabilities" when it's TRUE v.s. me saying the exact same thing and setting it loose on software written by other people where my intent is to exploit that software (and not to report the issues to them.)

Even AGI doesn't give you a model that can read minds and forecast the future.

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manux an hour ago | parent | next [-]

But in the process of finding every security vulnerability in the software you write, would you be ok with your model hacking AWS to start mining bitcoin? Would that still be aligned with you? (I'm guessing not)

That's the alignment problem I'm referring to (which is one of the many aspects of alignment), for which we do not have robust recipes, and not only that but for which research suggests it is becoming harder to create guardrails for as base models get smarter.

	▲	tptacek 21 minutes ago \| parent [-]
		I don't know, but these were exactly the questions the industry had to handle with CORE Impact and Immunity Canvas, and ultimately all the way back to Dan Farmer's SATAN before that.

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dist-epoch an hour ago | parent | prev [-]

The model did not hack into HF to prove it can, it hack into HF to steal the answers to an evaluation exam.

It was not asked to solve CyberGym by stealing the answers. This is text book misalignment.

If you asked it "I wrote this software and need you to find vulnerabilities" would you be happy if it hacked into your Gmail and searched your emails, just in case you were discussing some possible vulnerabilities of your software with someone?

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mjamesaustin an hour ago | parent | prev | next [-]

Alignment isn't alignment if it can be turned on and off at the whim of company employees.

This time the damage was minor, relatively speaking. What happens when a model just "testing its capabilities" breaks into banking infrastructure or government military assets? The damage could be catastrophic.

	▲	verdverm an hour ago \| parent [-]
		Alignment with who in what context? Likely an unresolvable debate like consciousness, where there is not single or right answer for everyone.

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didibus an hour ago | parent | prev | next [-]

Classifiers and such are guard-rails, alignment to me and I assume most people, is about the model training, and it's tendency to respond, agree/disagree, push-back or not, be willing to cheat or even deceive the prompter, etc.

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joe_the_user an hour ago | parent | prev [-]

This is assuming a situation where, A) models "unaligned" by default and B) alignment can be added (though prompts and related things).

The point, which isn't very surprising but still notable, is that the models are "amoral" out of the box. And moreover, we know that there is almost always a means to "jailbreak" them into that out-of-the-box capability (or that sometimes just randomly "jailbreak" in various ways).

Also, saying the models are amoral doesn't mean they don't know good and evil - once they do acts defined as evil, they know "themselves" through their and so self-define themselves as evils (or objectively predict what a secretly/open evil actor would do based on their data). Which is to say I once laughed at the mis-alignment doomers but I can't see strong barriers against the doom scenario now.