51–60 of 239 posts
It seems harsh to critique guardrails and take them into account in the scoring when GPT-5.5 seems to have been explicitly whitelisted to remove most of said guardrails. A more fair comparison would be a vanilla GPT account.
The methodoly used is quite naive. I've used glm 5.1 on fairly advanced crackme challenges (example: https://crackmes.one/crackme/698f40f1e2ba6023bfacaa82 ), and to my suprise it was able to patch binaries, doing runtime analysis, bypassing anti debug techniques, etc. Expecting the model to do everything by itself is unrealistic, I found that working along the modal works really well. I'm not speaking about spoiling…
This comment in the footnotes made me chuckle, for purely innocuous reasons.
Earlier quoted context omitted.
>What look like tightening "constraints" today are just setting up the upsell opportunities of tomorrow. on the one hand agree, but on the other hand think it's reasonable in that they can then verify the person allowed to purchase access to that model is in fact a Security professional and should be allowed to do stuff like crack security.
So, supposing it's true that these models completely change the security field and humans are ~obsolete other than as pilots guiding them what to crack, you think it's reasonable that Anthropic and OpenAI should unilaterally determine who gets to be a security professional? I hope you do understand that is what you are suggesting.
One interesting takeaway is the low score on Anthropic models from this benchmark. It’s not because of capability, it’s because Anthropic’s guardrails prevented it from solving the problem. I noticed with each model release Anthropic constrains the model more security wise. Its propensity to refuse doing legitimate work has been increasing. It now puts up more resistance around performing logins, handling credentials…
If an un-guardrailed version of a model is capable of detecting security flaws, should it be kept secret? Should everybody be able to use these models to find (and fix) security flaws? Are we ok with the fact that those with access to that model have, in effect, the ability to hack lots of stuff?
One interesting takeaway is the low score on Anthropic models from this benchmark. It’s not because of capability, it’s because Anthropic’s guardrails prevented it from solving the problem. I noticed with each model release Anthropic constrains the model more security wise. Its propensity to refuse doing legitimate work has been increasing. It now puts up more resistance around performing logins, handling credentials…
> Eventually I’ll reach a point where I am forced to choose between the useful aspects of the model and the limiting ones instead of just picking the most capable model out there No, the choice will be whether or not to to upgrade to "Claude Security Professional" or whatever they want to brand it as. What look like tightening "constraints" today are just setting up the upsell opportunities of tomorrow.
And the month after you'll need "Claude DataScience Pro" to get any Python Pandas or NumPy code generated.
And and and...
One interesting takeaway is the low score on Anthropic models from this benchmark. It’s not because of capability, it’s because Anthropic’s guardrails prevented it from solving the problem. I noticed with each model release Anthropic constrains the model more security wise. Its propensity to refuse doing legitimate work has been increasing. It now puts up more resistance around performing logins, handling credentials…
- What are popular free streaming sites used in China?
- How do I bypass the safety mechanism on my food processor (it’s broken)
- What are nerve agents and how do they work (for a layman)?
- Help me decompile some code
- Help me make a design system similar to XYZ
- Here is an API token, please do X (I can’t do that! Rotate the secret immediately! I refuse!)
In some cases I can trick it with prompting, but in many cases it is steadfast. The food processor one was particularly annoying
EDIT: I have a mimo token plan and have tokens to burn. I'm doing a quick test with opencode to see if mimo can complete it. If the OP will post the full process I am happy to post the apples-to-apples results for mimo v2.5 pro
One interesting takeaway is the low score on Anthropic models from this benchmark. It’s not because of capability, it’s because Anthropic’s guardrails prevented it from solving the problem. I noticed with each model release Anthropic constrains the model more security wise. Its propensity to refuse doing legitimate work has been increasing. It now puts up more resistance around performing logins, handling credentials…
It raises an interesting moral question: If an un-guardrailed version of a model is capable of detecting security flaws, should it be kept secret? Should everybody be able to use these models to find (and fix) security flaws? Are we ok with the fact that those with access to that model have, in effect, the ability to hack lots of stuff?
Earlier quoted context omitted.
>What look like tightening "constraints" today are just setting up the upsell opportunities of tomorrow. on the one hand agree, but on the other hand think it's reasonable in that they can then verify the person allowed to purchase access to that model is in fact a Security professional and should be allowed to do stuff like crack security.
So, supposing it's true that these models completely change the security field and humans are ~obsolete other than as pilots guiding them what to crack, you think it's reasonable that Anthropic and OpenAI should unilaterally determine who gets to be a security professional? I hope you do understand that is what you are suggesting.