There's still the question of access to the codebase. By all accounts, the best LLM cyber scanning approaches are really primitive - it's just a bash script that goes through every single file in the codebase and, for each one and runs a "find the vulns here" prompt. The attacker usually has even less access than this - in the beginning, they have network tools, an undocumented API, and maybe some binaries.

You can do a lot better efficiency-wise if you control the source end-to-end though - you already group logically related changes into PRs, so you can save on scanning by asking the LLM to only look over the files you've changed. If you're touching security-relevant code, you can ask it for more per-file effort than the attacker might put into their own scanning. You can even do the big bulk scans an attacker might on a fixed schedule - each attacker has to run their own scan while you only need to run your one scan to find everything they would have. There's a massive cost asymmetry between the "hardening" phase for the defender and the "discovering exploits" phase for the attacker.

Exploitability also isn't binary: even if the attacker is better-resourced than you, they need to find a whole chain of exploits in your system, while you only need to break the weakest link in that chain.

If you boil security down to just a contest of who can burn more tokens, defenders get efficiency advantages only the best-resourced attackers can overcome. On net, public access to mythos-tier models will make software more secure.