It does help A LOT in the case of security research. Particularly.

For example, I tended to avoid pen testing freelance work before AI because I didn't enjoy the tedious work of reading tons of documentation about random platforms to try to understand how they worked and searching all over StackOverflow.

Now with LLMs, I can give it some random-looking error message and it can clearly and instantly tell me what the error means at a deep tech level, what engine was used, what version, what library/module... I can pen test platforms I have 0 familiarity with.

I just know a few platforms, engines, programming languages really well and I can use this existing knowledge to try to find parallels in other platforms I've never explored before.

The other day, on HackerOne, I found a pretty bad DoS vulnerability in a platform I'd never looked into before, using an engine and programming language I never used professionally; I found the issue within 1 hour of starting my search.

▲

saagarjha 2 days ago | parent [-]

Did you spend another hour confirming your understanding?

	▲	jongjong 2 days ago \| parent [-]
		Yes and at least 30 more minutes to write the report; with the help of LLM. So it still required my analysis skills but at least I was able to do it, relatively fast... Whereas I wouldn't even have considered doing this kind of stuff before due to the hassle associated with research... There are multiple factors which are pulling me into cybersecurity. Firstly, it requires less effort from me. Secondly, the amount of vulnerabilities seems to be growing exponentially... Possibly in part because of AI.