I know Mastodon hates LLM's and AI.
-
@drwhax Using the stones to destroy the stones seems an unavoidable task
@decapitae Ideally we get more Suhosin's projects for all these different languages, but I doubt it'll happen at this point.
-
@rysiek human in the loop etc
@drwhax the problem is this works better for certain tasks (finding vulnerabilities) and much worse for other tasks (vibe-coding) because of the shape of these tasks.
"Human in the loop" is not the get-out-of-LLM-problems-free card people try to pretend it is.
Human in the loop works for vulnerability findings because there is a reliable way of verifying the finding. It clearly does not work well for vibe-coding at all because there is no such reliable way of verifying code correctness.
-
@drwhax the problem is this works better for certain tasks (finding vulnerabilities) and much worse for other tasks (vibe-coding) because of the shape of these tasks.
"Human in the loop" is not the get-out-of-LLM-problems-free card people try to pretend it is.
Human in the loop works for vulnerability findings because there is a reliable way of verifying the finding. It clearly does not work well for vibe-coding at all because there is no such reliable way of verifying code correctness.
@rysiek I think we'll get there in a number of years, the way the field is developing now we got all these super fast interconnects and HBM memory and not to mention advancements in the machine learning field.
I almost puke writing this lol
-
I know Mastodon hates LLM's and AI. So here goes!
I recently got access to trusted access of cyber capabilities of both openai and anthropic, which also allows you to weaponize security vulnerabilities.
The speed at which these parrots can find bugs and be creative enough to exploit them is staggering.
I recently pointed an LLM at an kernel fix that was reachable by an unprivileged namespace on Debian and it fully weaponized it, without too much me prompting it in the right direction, in about 7-9 hours.
I don't think open-source and companies will know what's coming for them once these open-source weight models will have broader reach and get better at exploiting vulnerabilities on a massive scale as anyone can access them.
The bottom line I think is, you cannot patch faster than the attackers can easily chain all kinds of vulnerabilities together and just move laterally on an incredibly fast pace.
I've started reporting vulnerabilities to all kinds of projects and the majority have trouble or patching issues found. There's not enough maintainers, or there's simply none anymore.
I've been getting quite worried about what our future will look like for data privacy. I think outright not running an LLM over your codebase to find critical security vulnerabilities because of your moral stance will keep us more insecure.
Please run an LLM over your code base if it's internet facing or something critical, we thank you!
Can't wait for the discussions on this!
@drwhax a lot of us at Red Hat have been working at 100% for the last 6 months on basically this. I personally spend ~2h/day on AISLE and Mythos reports and getting fixes upstream.
-
@can yes for sure!
There's a couple things you can do, one of them is indeed as basic as, this is app XYZ, written in PHP, review the codebase for security problems, then adversarially review your findings before writing them down in findings/ per bug in markdown. Also make a root cause and look for variants of the same class of issues across the code base.
What are some good skills to run is from Trail of Bits which are open-source: https://github.com/trailofbits/skills
If it's C/C++, LLM's are pretty good at making fuzzers and seeding the dictionary needed to fuzz them effectively.
If it's open-source you can apply for some openai codex api grant: https://openai.com/form/codex-open-source-fund/
-
@drwhax a lot of us at Red Hat have been working at 100% for the last 6 months on basically this. I personally spend ~2h/day on AISLE and Mythos reports and getting fixes upstream.
@hughsie I'd love to hear more on the maintainer side of this. What i'm ultimately scared of is that everyone will burn out from the immense amount of stuff maintainers have to clean up.
-
@Offbeatmammal @can I'm very curious to hear if it helps! If you need help i'm here!
-
@drwhax I think we need a bit of nuance here.
As much as I am no fan of LLMs, I can see the value of running them over one's own codebase in order to find vulnerabilities.
But I remain unconvinced that vibe-coded fixes are a good idea, or ever will be. I think this needs to be clearly said.
The reason is that these are fundamentally different problems.
-
@hughsie I'd love to hear more on the maintainer side of this. What i'm ultimately scared of is that everyone will burn out from the immense amount of stuff maintainers have to clean up.
@drwhax I'm paid by Red Hat to do this, and am given access to all the resources I need -- but it must be soul destroying for an open source contributor just doing OSS for fun as a hobby.
I keep telling myself that all this security stuff isn't much fun, but it probably makes open source stronger in the long term.
I think it helps to have very strict rules upstream for the flood of AI reports, e.g. https://github.com/fwupd/fwupd/blob/main/SECURITY.md#reporting-a-vulnerability
-
-
-
-
@Offbeatmammal @can I'm very curious to hear if it helps! If you need help i'm here!
-
@Offbeatmammal @can I think that's accurately describing my view on AI for the past couple months now hehe
-
@drwhax the problem is this works better for certain tasks (finding vulnerabilities) and much worse for other tasks (vibe-coding) because of the shape of these tasks.
"Human in the loop" is not the get-out-of-LLM-problems-free card people try to pretend it is.
Human in the loop works for vulnerability findings because there is a reliable way of verifying the finding. It clearly does not work well for vibe-coding at all because there is no such reliable way of verifying code correctness.
-
@FIAR_Light @rysiek yeah that's pretty bad....
-
I know Mastodon hates LLM's and AI. So here goes!
I recently got access to trusted access of cyber capabilities of both openai and anthropic, which also allows you to weaponize security vulnerabilities.
The speed at which these parrots can find bugs and be creative enough to exploit them is staggering.
I recently pointed an LLM at an kernel fix that was reachable by an unprivileged namespace on Debian and it fully weaponized it, without too much me prompting it in the right direction, in about 7-9 hours.
I don't think open-source and companies will know what's coming for them once these open-source weight models will have broader reach and get better at exploiting vulnerabilities on a massive scale as anyone can access them.
The bottom line I think is, you cannot patch faster than the attackers can easily chain all kinds of vulnerabilities together and just move laterally on an incredibly fast pace.
I've started reporting vulnerabilities to all kinds of projects and the majority have trouble or patching issues found. There's not enough maintainers, or there's simply none anymore.
I've been getting quite worried about what our future will look like for data privacy. I think outright not running an LLM over your codebase to find critical security vulnerabilities because of your moral stance will keep us more insecure.
Please run an LLM over your code base if it's internet facing or something critical, we thank you!
Can't wait for the discussions on this!
@drwhax It's not that you're wrong but you're not specific enough. Which AI, in what way? Plus, though I see you have enough technical expertise you come out with that OpenAI/Claude vibe that I detest. We should use LLMs, but in our own way, after stripping away the hype. All the LLM technobros have been stealing our code and other people's copyrighted work, and now want to sell it back to us with added bias, lack of provenance and old data. Excuse me if I'm not wildly enthusiastic about their for-profit products.
-
1. Acceptance. There's the saying "you just need to be more secure than your neighbor". It's not fully true but biz people hold it so. It's flip side is a cynic commentary on security, and a true one at that: If your neighbor is not secure, you don't need to be either. This is still true if you're getting pwned. When everyone's getting hacked regularly, society will accept this new reality. Only the defense sector will still care for security. We've seen similar developments in different industries: Fast fashion isn't an adequate replacement for garment that stands the test of time. But it's getting impossible to buy good clothes, even if you want to. But also with other goods: If everyone produces low quality items, it's financially more reasonable to do the same.
2. Centralization. Coz we won't do the right thing and reduce complexity, we need to find a way to make complexity "secure": Cloud, Big5, etc. Corps that have the resources to host an Exchange server securely... or in compliance with regulations. Every tool you do not let a big house host is a liability. Not coz they're necessarily more secure, but because nobody will blame you if something gets wrong. We had that with "buying IBM" once.
I hate this outlook but I seriously doubt that we will correct course.
The nice thing about open source is that there's always *someone* doing whatever obscure thing the mainstream finds too niche. I'm sure there are people right now who have for decades been building smaller software, and maybe for a certain non-corporate group there can be a pivot to that stuff. To avoid an endless edge of new code to harden, you need to forgo compatibility with new software & hardware, which has until now meant relative uselessness. But given how the AI bubble is driving up hardware prices, and the fact that we've seen standards like USB mature to a point that feels like it could be stable for a decade or more, maybe the endless cycle of new hardware stuff just slows down in certain backwaters. Of course this is anathema to corporate strategies, but I wonder if given the fact that the churning edge will be nearly impossible to secure, maybe a chunk of consumers will find ways to be satisfied with a smaller more stable core.
-
I know Mastodon hates LLM's and AI. So here goes!
I recently got access to trusted access of cyber capabilities of both openai and anthropic, which also allows you to weaponize security vulnerabilities.
The speed at which these parrots can find bugs and be creative enough to exploit them is staggering.
I recently pointed an LLM at an kernel fix that was reachable by an unprivileged namespace on Debian and it fully weaponized it, without too much me prompting it in the right direction, in about 7-9 hours.
I don't think open-source and companies will know what's coming for them once these open-source weight models will have broader reach and get better at exploiting vulnerabilities on a massive scale as anyone can access them.
The bottom line I think is, you cannot patch faster than the attackers can easily chain all kinds of vulnerabilities together and just move laterally on an incredibly fast pace.
I've started reporting vulnerabilities to all kinds of projects and the majority have trouble or patching issues found. There's not enough maintainers, or there's simply none anymore.
I've been getting quite worried about what our future will look like for data privacy. I think outright not running an LLM over your codebase to find critical security vulnerabilities because of your moral stance will keep us more insecure.
Please run an LLM over your code base if it's internet facing or something critical, we thank you!
Can't wait for the discussions on this!
@drwhax
isn't this a proof that humans are not better at writing software than SOTA models? In general, of course. -
@drwhax It's not that you're wrong but you're not specific enough. Which AI, in what way? Plus, though I see you have enough technical expertise you come out with that OpenAI/Claude vibe that I detest. We should use LLMs, but in our own way, after stripping away the hype. All the LLM technobros have been stealing our code and other people's copyrighted work, and now want to sell it back to us with added bias, lack of provenance and old data. Excuse me if I'm not wildly enthusiastic about their for-profit products.
@fnrd you're right, but I think if we take this defeatist stance we're not going to improve things for the better.
Unfortunately, we'll not be able to make our own models, we're compute starved, our best bet is maybe open-weights models.
It's all a mess though, I do agree with that.
