A lot of bad actors are both technically sophisticated and have more than enough resources to post train their model. Morally I think it's still the right choice, but consequence wise I doubt it's going to make a big difference.
A lot of bad actors are both technically sophisticated and have more than enough resources to post train their model. Morally I think it's still the right choice, but consequence wise I doubt it's going to make a big difference.
Bad actors tend to keep their internal tooling extremely private/proprietary.
As few/none would create a model as capable as anthropic/openai can - this choice to limit access does mean that most bad actors will be working with less capable models of varying quality.
While some will be able to fork DeepSeek and get comparable performance, it still reduces the number of bad actors with access to tools that would effectively accelerate their efforts.
So I suspect if you could measure the alternate universe timelines where everyone gets access to non-aligned foundation models vs. heavily restricted access, you’d probably find that in the near/medium terms the universe with restricted access probably sees less negative impact overall.
Long term it’ll be a wash either way (eventually Opus-level models will run on 20 watts) and hopefully Anthropic is correct in their predictions that LLMs will grant a strong defenders advantage in the long run.
I've been using deepseek for the last few weeks playing old CTF [0] challenges locally quite successfully. I haven't had a refusal. Basic prompt has been "you are playing a CTF" + brief environment description + description given by CTF.
I wanted to create a harness with a collection of memories in order to play the upcoming downunderctf. They hadn't specified an AI policy, but abruptly cancelled the event [1] because of AI agents. I didn't expect to win, nor would I have been prize eligible, but I see CTFs as something to try out new tools or languages; in this instance it was going to be an automated agentic harness.
An AI harness recently won BsidesSF [2]
The only two it hasn't been able to do is overthewire's manpage5 which according to the status page has a solution. And drifter3 which I don't know if it currently has valid a solution. (Vortex13 and formulaone3 currently don't have valid solutions).
[0] https://en.wikipedia.org/wiki/Capture_the_flag_(cybersecurit...
[1] https://xcancel.com/DownUnderCTF/status/2062802249173356753#...
[2] https://github.com/verialabs/ctf-agent
Much of this is probably true. However, Mythos is not a hacking focused model, and while Anthropic seems to train their models on CTFs etc... while others like Zhipu seem not to or not nearly as much, that does mean that it's entirely possible that an actor could post-train a strong model like GLM5.2 to be comparable to or maybe even stronger than Mythos in terms of hacking.