Earlier quoted context omitted.
As someone on the company response side of the HackerOne brokenness, I can confirm that this effect is real but would also note that the difficulty of distinguishing is not as severe as all that, because the companies have access to the source code which the researchers do not typically have access to. This means that the token cost of verifying any given HackerOne report is dramatically lower than the token cost of…
The token cost of a report is lower bounded by the number of tokens in the report * price per token of the cheapest model. The token cost of a good report is much higher, but sifting out the good reports is the entire problem.
The ones we're seeing show clear evidence of being AI-generated, are often incorrect or duplicated, but they also show clear evidence of the AI having done its homework and spent a while crawling our API.
Even if we were getting reports at the lower bound you're describing, those would be even easier to triage: just add a quick step to check if the API in question even exists, then if it does that very cheap "where is this API" query becomes part of the input to the second-level triage that spends more tokens.