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user43928today at 6:22 AM5 repliesview on HN

Why would the model not find the vulnerability during implementation or testing before release?

If it requires a lot of compute and trying, this is something that could be provided for common software.


Replies

wood_spirittoday at 6:36 AM

Sad that this could well be that the path to OpenAI and Anthropic profitability of this arms race between defending LLM white hatting a company’s website and the black hat LLMs attacking it?

So the whole thing is forcing the good guys to outspend on tokens to preemptively defend against the risk of the bad guys outspending them on tokens, rather than buying tokens to actually add features to the product etc.

So are they creating a market for the solution by helping create the problem? A kind of rent-seeking AI security-industrial complex!!

show 3 replies
xboxnolifestoday at 6:30 AM

Because it's far cheaper to to not spend the tokens finding the vulnerabilities, and software is now being created and released magnitudes faster than ever before. I could see the huge software companies maybe having fewer vulnerabilities, but I expect to see so much more in the smaller side of things.

imhoguytoday at 7:45 AM

The surface of potential issues is growing with complexity of all connected parts of the system. That applies to not only software. To prevent issues you either spend proportional amount (dollars, tokens, hours) on testing or reduce complexity of the system.

techpressiontoday at 6:56 AM

Because people need to spend time and money on that, which they won’t. The implementation is cheap, the review and follow-up is not (speaking from a pure LLM only workflow). My ratio is around 1:2 currently, so twice as much time spent fixing vs building.

philbotoday at 7:32 AM

> it requires a lot of compute

This is one reason

> and trying

and this is the other.