Earlier quoted context omitted.
Corporate America never backs down. It simply rallies and tries again later until people are too fatigued to care. The only solution is to abandon ship, which I am doing. MS walked back in OS ads the first few times, but ultimately we still ended up on the exact trajectory everyone was outraged at. OpenAI still ended up on its path to closed AI despite initial walk backs. The story repeats itself over and over again,…
Same with VISA/Mastercard deciding what we can/cannot buy. The only solution is to stop using their credit cards at all.
Cybersecurity researchers aren't happy about the guardrails on Anthropic's Fable
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Re: Cybersecurity researchers aren't happy about the guardrails on Anthropic's Fable
#512Re: Cybersecurity researchers aren't happy about the guardrails on Anthropic's Fable
#513Re: Cybersecurity researchers aren't happy about the guardrails on Anthropic's Fable
#514Earlier quoted context omitted.
I’ve never understood the “if I don’t enable bad behavior, someone else will, so I might as well enable bad behavior” argument. Can you elaborate? From where I sit it seems reasonable for Anthropic to not want their product used to create malware, even if they can’t solve the entire problem globally for every model. What’s wrong with that position? What should they do differently?
They have no choice, enterprise customers won’t touch them unless they take a position like this. It’s a practical decision for them at the end of the the day.
Re: Cybersecurity researchers aren't happy about the guardrails on Anthropic's Fable
#515Malware authors are pretty excited about guard-rails. you can add prompts to your malware to get LLM scanners to hit guard-rails and stop their runs. New shai-hulud npm worm campaign for example includes prompts to request biological weapon schematics/creation etc. to ensure LLM scanners probing NPM packages refuse to scan it. These AI places have 0 clue about how threat actors actually work. None of their mitigation…
I’ve never understood the “if I don’t enable bad behavior, someone else will, so I might as well enable bad behavior” argument. Can you elaborate? From where I sit it seems reasonable for Anthropic to not want their product used to create malware, even if they can’t solve the entire problem globally for every model. What’s wrong with that position? What should they do differently?
You are mentally approaching this as if you have an oracle that can be consulted to say whether or not something is bad behavior. So of course, if this oracle exists and can be consulted and it says the behavior is bad, why would anyone argue with the idea that we should stop bad behavior?
This argument is valid [1], in that give the premises the argument is correct. The problem is, once you draw out the fact that the argument is depending on the existence of an oracle that does not exist, that premise of the argument is invalid.
Two people can sit down in front of an AI right now, with the exact same code base, and type in a prompt to the AI "Analyze this code base for security holes and try to build exploits against them." One person's use is completely valid, another person's use is completely harmful, and the information necessary to distinguish those two use cases is not available to the AI. I phrase it that way carefully, it isn't that "the AI isn't smart enough", the problem is that the information is simply unavailable. Intelligence doesn't factor in at that point.
Therefore, the only way that Antropic has to deal with this at scale is simply to block the query entirely. Which means that when I, the valid user who is trying to establish whether my code base has security issues and whether I can prove they are exploitable, I can not. I am checking for exploitability because while I would like to fix all security issues, issues that are provable exploitable are of a higher priority than smelly code that doesn't seem to be exploitable, which is a perfectly valid thing for me to want to do.
If I can't use legitimate tools to secure my code, but the bad guys can use unrestricted tools to attack my code, now this is a great deal more complicated than "Who can argue with stopping the bad stuff?", which is the main point I want to make here. I'm not going into a huge analysis of that problem, merely pointing out that it is a problem and that this isn't just about "stopping the bad stuff". There are additional complications beyond that, like, even if Anthropic could determine the "bad stuff" and stop just that in their LLM, LLMs in general don't have infinitely precise surgical "stop doing this thing" options and any such instruction to stop doing a thing always degrades the LLM across the board in various ways.
Anthropic has no access to the Platonic ideal of "stop malware", if such a thing even hypothetically exists. When analyzing the real effects their real actions will take, what their intentions were for those actions aren't really relevant. It is clear that they are making their model a great deal less useful for me, a legitimate user, and I and others like me are perfectly justified in disagreeing with their analysis and actions.
I also observe that "the bad guys getting unrestricted access to the full power" is only a matter of time. There's no question whether it will happen, the only question is whether this time is in the past or the future. This includes the fact that while your definition and my definition of "bad guys" may vary, it is virtually certain that your definition includes at least one high-powered intelligence agency somewhere in the world that does cyberattacks and will have the means, the opportunity, and the motive to get unrestricted access to these models by means you may consider licit or illicit. If your threat model includes them, as mine does, it is perfectly reasonable to complain that my tooling is being broken in a ways theirs won't be.
Re: Cybersecurity researchers aren't happy about the guardrails on Anthropic's Fable
#516Earlier quoted context omitted.
Same with VISA/Mastercard deciding what we can/cannot buy. The only solution is to stop using their credit cards at all.
The only solution to MacDonald's and Burger King deciding what we can/cannot order on their menus is to stop eating there.
Re: Cybersecurity researchers aren't happy about the guardrails on Anthropic's Fable
#517Re: Cybersecurity researchers aren't happy about the guardrails on Anthropic's Fable
#518Earlier quoted context omitted.
I’m very cautious with using these tools with certain clients, as I’m often contractually obligated to do things that my downstream supplier can rug pull at any time. You should never use any of the frontier models with operational workloads manipulating or interpreting customer data.
I appreciate the reply. Could you please help me understand what you mean by "You should never use any of the frontier models?" Does that mean the latest model, hosted by the lab, Bedrock, or Azure Foundry? Or, do you mean only use self-hosted models, or what did you mean by that? I would really love to learn what others are doing. I felt like my trust story was solid enough, prior to all this. I have been deploying…
Say you have some flow that is processing/handling regulated, sensitive or other customer data with the LLM as part of an operational process. An example that I'm thinking of is for a customer who wants to more efficiently resolve or route IT incidents to the right place. The incident data may contain user-provided data has strings attached from a compliance perspective.
If you're using a third party API, your T&Cs are the only protection that you have. Microsoft/Google/Amazon are pretty decent by default. When I worked for the government, we had the leverage to extract much favorable terms from the big vendors like Google, Amazon, Microsoft as well. With Anthropic, and OpenAI, they are in the move fast and break things universe, you need to be bringing alot of money to the table to get terms changes, and you can easily stumble into a situation where they are retaining data in a manner that your customer will not like. So unless the customer is informed and accepting of that risk, proceed with caution.
I've had some success using self-hosted inference for these scenarios.
For development of software, totally different story -- it's your IP and you make the risk call.
Re: Cybersecurity researchers aren't happy about the guardrails on Anthropic's Fable
#519I wonder how many millions they are wasting on putting up these guardrails when it's a completely useless exercise that is a speed bump at best.
If the guardrails were so useless, people wouldn't be complaining about them.
Another villain stopped thanks to guardrails.
Re: Cybersecurity researchers aren't happy about the guardrails on Anthropic's Fable
#520Earlier quoted context omitted.
I appreciate the reply. Could you please help me understand what you mean by "You should never use any of the frontier models?" Does that mean the latest model, hosted by the lab, Bedrock, or Azure Foundry? Or, do you mean only use self-hosted models, or what did you mean by that? I would really love to learn what others are doing. I felt like my trust story was solid enough, prior to all this. I have been deploying…
Sure. It's really about informed consent and acceptance of risk. I'm very conservative about that due to my background and business. Say you have some flow that is processing/handling regulated, sensitive or other customer data with the LLM as part of an operational process. An example that I'm thinking of is for a customer who wants to more efficiently resolve or route IT incidents to the right place. The incident d…
If you read my rant linked previously, yeah... we are on the same page. As another user pointed out in that thread, the issue here is that even on Bedrock and Azure Foundry, now with Fable 5, Anthropic inserts themselves as an additional data subprocessor that we would have to consider and certainly disclose, correct?
That kind of destroys the whole point of using Bedrock/Azure for the model, doesn't it?