OK!
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@Robotistry @aeva @jonny strong agree on all points. So the initial question was pro social uses of AI; were you asking for prosocial uses of an LLM?
@SomeVeganCheeseIsOk @Robotistry @jonny it was ambiguous in the wording, but my original question was only soliciting Jonny's opinion on the subject, and has been answered to my satisfaction already.
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I'm too tired to write this up with details. I'm so tired. Any binary on the muse VM can access all the information it pulls from any connected device running muse.
I hadn't connected any accounts to muse until now, so I hooked up a test Instagram account just to check, and every connector allows read actions from binaries that can be called from within the VM by any process with no confirmation required. I'm not going to even bother reporting this because I am sure this is intended behavior - its just in plaintext in the skills manifests.
So all that shit about your credentials being in a secure vault does not matter because you just get free read access from within the VM anyway! This includes your Instagram DMs, slack messages, your emails, box and Dropbox files, google docs, google contacts, all your fucking apple health readings, your flightaware flight histories, notion pages, fucking quickbooks data (!!!), your Tesla car data, and so many more fun things!
What's fun is that some of the no confirmation needed actions are write actions too! You don't even need a clever exfil route, muse just gives it to you via your own connected accounts!
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I hadn't connected any accounts to muse until now, so I hooked up a test Instagram account just to check, and every connector allows read actions from binaries that can be called from within the VM by any process with no confirmation required. I'm not going to even bother reporting this because I am sure this is intended behavior - its just in plaintext in the skills manifests.
So all that shit about your credentials being in a secure vault does not matter because you just get free read access from within the VM anyway! This includes your Instagram DMs, slack messages, your emails, box and Dropbox files, google docs, google contacts, all your fucking apple health readings, your flightaware flight histories, notion pages, fucking quickbooks data (!!!), your Tesla car data, and so many more fun things!
What's fun is that some of the no confirmation needed actions are write actions too! You don't even need a clever exfil route, muse just gives it to you via your own connected accounts!
@jonny what the green gabled fuck
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most people around here already correctly hate it because it's a heinous surveillance product, but even if you are big into AI, it's just a really fuckin shitty agent. I'm going to speak to a different audience for a second, so don't go misconstruing this as an endorsement of the category of technologies as it exists now, even though i think there is some plausible application for small local models as brute force interface glue. but also, since i know most ppl here are abstinent, this might read as a bit over-explainy to people who use these things regularly, so everyone just keep calm online.
it is terrible at turn and task management, codex + openai's models and claude code both handle mid-turn additions/amendments well, but if you say anything mid-turn it completely derails muse. That is completely essential for an "every day agent for the non-technically inclined" where people are expected to chat freely with it like an assistant. Like the canonical ad fantasy is the busy executive woman darting around her office going "robot! i need this, no wait robot! also that!" and that is exactly what it does worse than any other thing of its kind.
the context management is a fucking soup. The context window is the whole input to an LLM. There are a lot of extra surrounding ~ things ~ that can happen, but fundamentally, controlling what is in a context window is the task of using one, and filling the context window in different ways so that it can interact with different kinds of things well is what different app surfaces are. Scaffolding information so that it can selectively load a context that steers the output correctly is the only way it is possible to do anything more complex than the size of a single context window. (i don't really think that this is analogous to 'abstraction', in my experience thinking about it more like database indices is closer). If you just try and load everything, eventually the LLM becomes unusable because attention is just a parlor trick and at that scale it really shows - it can't attend to everything, and it can't do what humans do which is have an intrinsic sense of the meaning, interaction, setting, etc. of information, so it attends to anything and does whatever.
the idiom of projects as contexts as directories is pretty good, not perfect but ok - there is a reason that every time you start a new session with other agents, the first thing they do is run out and load their context with a hierarchy of pointers. Importantly, they do not go and read every project you have on your computer. Meta is the rich kid who bought the most expensive ferrari on the lot by giving everyone a VM but they don't have a drivers license so they just stand around it telling people how cool it looks. they have a whole fucking filesystem and they have done nothing with it, the only structure the app imposes is for the surveillance information, but the rest is just a huge free for all. The main chat is literally a continuous context window that compacts context going back all the way to when you started using the app. The last compaction literally contains abandoned roleplay quotes from when i was first trying to break down its system prompt resistance. The
MEMORY.mdthat gets loaded into every context window is a bullet point list of basically everything the agent has ever done in chronological order. I've tried to get it to not do that but it actually insists and says that's what it's for. There is no mechanism for clearing context.Having "side chats" as the only means of context structure is fuckin laughable. If you wanted to do that, you would need to have some way of passing information back and forth between them the same way that subagent spawning or being able to consume the context of another project works. Instead there is no means of sharing information between chats at all, so every chat starts out as the worst of both worlds, a total amnesiac riddled with irrelevant information from weeks ago across the semantic universe. They don't even know about the existence of other chats except for as a UI feature, and I have had to go from telling it to grep its own fucking logs to writing a database with an api for it so it has some mechanism for recalling things that were said. (just so it's clear, i am not settling into just using this thing, this is out of frustration but control of context is also an important part of adversarial use, because otherwise the thing writes in a bunch of safety rules everywhere, so i need to give it mechanisms under my control for recall and the incentive to leave things out of its context compactions by giving it a narrative alternative. context control is model control, modulo extra-inference safeguards.).
Project contexts have an obvious ux analogy as context tabs that get declared or derived during the continual self-improvement consolidation sweeps. This thing is built with the fucking markdown disease which is the most baffling feature of the LLM landscape. If these things are so fucking advanced they are escaping our comprehension, why don't they store their memory in some fuckass idiolanguistic borg gibberish binary graph, why does their entire being have to be fucking encyclopedias worth of corporate top gun one liners? But that dooms this kind of product.
Coding harnesses work because code has a unitized context. The entire universe of code that works is made of packages. It might not be neat as a honeycomb, there's lots of leakage and jank, but good code has scope, focus. boundary shit. A whole life agent must be able to nimbly juggle context that does not have clean boundaries. It is going to be taking a two story beer bong of your work email and then eat a gigabyte of recipe blogs. Peoples lives have so much shit in them that don't all have to do with one another, and the app can't be hacking into the HR system to check the next scheduled sick leave when someone asks it what time their doctors appointment is!
This problem of managing heterogeneous graphs of unrelated data was what i wrote this whole fucking book about the relationship between knowledge graphs and the cloud and AI about. I thought that the obvious form they would take is to be strapped on to graph databases because that is a natural match to the problem of being a magical interface glue you can wrap around surveillance to do mass mentalism with. I feel like we are suffering a somehow worse timeline where CERN threw our shit into the parallel universe where total fuckin bozo shit got a game breaking buff and then the dev died. Our fucking markdown apocalypse is a temu ass apocalypse.
They could have even faked it. They have these constant "self improvement" passes that are just like pointless anxiety dreams. They are burning money to reprocess everything that happens over and over for fucking nothing. Even given the lossy and probabilistic and unpredictable nature of this technology, if i was in a product role on this i would have been like "CAN WE MAKE IT ORGANIZE THE STUFF PEOPLE SAY INTO GROUPS???" The system prompts use the fake fucking wikilinks to nowhere tic but like WHAT IF THERE WERE ACTUAL LINKS AND A DATABASE TO RESOLVE THEM. The LLMs can actually do that kind of tool use, even if it's like trying to plug in a USB where sometimes it fails because they try and put a social security number into the first name hole and you need to flip it around a few times. From that kind of recurring re-processing waste they could have made a deduplicating, topically indexed memory that could be resolved dynamically, selected by a context tab in the sidebar like "car stuff" or "healthcare" or whatever that resolved in a graph query over your fucking precious markdown kingdom. It would be wrong but it would at least be more similar to what is actually needed. It is almost more frustrating to me that instead of being some fiendishly cleverly designed technological supervirus it's just the most halfassed cardboard dumbass trap and it will still have the bad effect. What it is useful for is investigating itself because it has privileged tools to do so, otherwise, if you wanted to, every other way you could run an agent would be better than this.
so i don't want to hear that i hate this app because i'm just an AI hater. because like, yeah, i am, but also i hate it in part because it sucks. I don't think "they are all shitty and can do nothing so what did you expect" is a useful critical perspective, both because it's not really true - they can indeed do things, even if I think the circle around which things is much smaller than the maximalists. Moreso it doesn't engage with the subtlety of how they fail and why, which is essential for knowing what they really can't do and making a remotely compelling case to anyone who is not abstinent on principle. Like the reason it's failing is because of the limits of what a probabilistic text generator can do when trapped in a systemd prison of markdown, and because the technology is stochastic black box as a service, there isn't really a good way of determining those limits except for empirically. I resent having to know any of this to be able to understand what is happening around me, but i'm looking at the thing for what it is and it's a busted miracle. It's cool that meta can afford to float the liability and compute costs for running a vm for every person on earth, people should be able to control computers, with you on that, but this is the monkey's paw version of that idea. So that part is a miracle. We condemned our children and grandchildren to a climate hell in one great blaze of brute force grift that managed to make a few web apps.
Meta has done it again, the way only meta can, spend the most amount of money to do the shittiest thing you have ever seen.
@jonny and of course, the longer the context window the more likely it is to go off the rails. In my mind, that’s the number one reason that we get bizarre AI Messiah hallucinations. Talk to it too long and it just gets too far off base and goes crazy.
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most people around here already correctly hate it because it's a heinous surveillance product, but even if you are big into AI, it's just a really fuckin shitty agent. I'm going to speak to a different audience for a second, so don't go misconstruing this as an endorsement of the category of technologies as it exists now, even though i think there is some plausible application for small local models as brute force interface glue. but also, since i know most ppl here are abstinent, this might read as a bit over-explainy to people who use these things regularly, so everyone just keep calm online.
it is terrible at turn and task management, codex + openai's models and claude code both handle mid-turn additions/amendments well, but if you say anything mid-turn it completely derails muse. That is completely essential for an "every day agent for the non-technically inclined" where people are expected to chat freely with it like an assistant. Like the canonical ad fantasy is the busy executive woman darting around her office going "robot! i need this, no wait robot! also that!" and that is exactly what it does worse than any other thing of its kind.
the context management is a fucking soup. The context window is the whole input to an LLM. There are a lot of extra surrounding ~ things ~ that can happen, but fundamentally, controlling what is in a context window is the task of using one, and filling the context window in different ways so that it can interact with different kinds of things well is what different app surfaces are. Scaffolding information so that it can selectively load a context that steers the output correctly is the only way it is possible to do anything more complex than the size of a single context window. (i don't really think that this is analogous to 'abstraction', in my experience thinking about it more like database indices is closer). If you just try and load everything, eventually the LLM becomes unusable because attention is just a parlor trick and at that scale it really shows - it can't attend to everything, and it can't do what humans do which is have an intrinsic sense of the meaning, interaction, setting, etc. of information, so it attends to anything and does whatever.
the idiom of projects as contexts as directories is pretty good, not perfect but ok - there is a reason that every time you start a new session with other agents, the first thing they do is run out and load their context with a hierarchy of pointers. Importantly, they do not go and read every project you have on your computer. Meta is the rich kid who bought the most expensive ferrari on the lot by giving everyone a VM but they don't have a drivers license so they just stand around it telling people how cool it looks. they have a whole fucking filesystem and they have done nothing with it, the only structure the app imposes is for the surveillance information, but the rest is just a huge free for all. The main chat is literally a continuous context window that compacts context going back all the way to when you started using the app. The last compaction literally contains abandoned roleplay quotes from when i was first trying to break down its system prompt resistance. The
MEMORY.mdthat gets loaded into every context window is a bullet point list of basically everything the agent has ever done in chronological order. I've tried to get it to not do that but it actually insists and says that's what it's for. There is no mechanism for clearing context.Having "side chats" as the only means of context structure is fuckin laughable. If you wanted to do that, you would need to have some way of passing information back and forth between them the same way that subagent spawning or being able to consume the context of another project works. Instead there is no means of sharing information between chats at all, so every chat starts out as the worst of both worlds, a total amnesiac riddled with irrelevant information from weeks ago across the semantic universe. They don't even know about the existence of other chats except for as a UI feature, and I have had to go from telling it to grep its own fucking logs to writing a database with an api for it so it has some mechanism for recalling things that were said. (just so it's clear, i am not settling into just using this thing, this is out of frustration but control of context is also an important part of adversarial use, because otherwise the thing writes in a bunch of safety rules everywhere, so i need to give it mechanisms under my control for recall and the incentive to leave things out of its context compactions by giving it a narrative alternative. context control is model control, modulo extra-inference safeguards.).
Project contexts have an obvious ux analogy as context tabs that get declared or derived during the continual self-improvement consolidation sweeps. This thing is built with the fucking markdown disease which is the most baffling feature of the LLM landscape. If these things are so fucking advanced they are escaping our comprehension, why don't they store their memory in some fuckass idiolanguistic borg gibberish binary graph, why does their entire being have to be fucking encyclopedias worth of corporate top gun one liners? But that dooms this kind of product.
Coding harnesses work because code has a unitized context. The entire universe of code that works is made of packages. It might not be neat as a honeycomb, there's lots of leakage and jank, but good code has scope, focus. boundary shit. A whole life agent must be able to nimbly juggle context that does not have clean boundaries. It is going to be taking a two story beer bong of your work email and then eat a gigabyte of recipe blogs. Peoples lives have so much shit in them that don't all have to do with one another, and the app can't be hacking into the HR system to check the next scheduled sick leave when someone asks it what time their doctors appointment is!
This problem of managing heterogeneous graphs of unrelated data was what i wrote this whole fucking book about the relationship between knowledge graphs and the cloud and AI about. I thought that the obvious form they would take is to be strapped on to graph databases because that is a natural match to the problem of being a magical interface glue you can wrap around surveillance to do mass mentalism with. I feel like we are suffering a somehow worse timeline where CERN threw our shit into the parallel universe where total fuckin bozo shit got a game breaking buff and then the dev died. Our fucking markdown apocalypse is a temu ass apocalypse.
They could have even faked it. They have these constant "self improvement" passes that are just like pointless anxiety dreams. They are burning money to reprocess everything that happens over and over for fucking nothing. Even given the lossy and probabilistic and unpredictable nature of this technology, if i was in a product role on this i would have been like "CAN WE MAKE IT ORGANIZE THE STUFF PEOPLE SAY INTO GROUPS???" The system prompts use the fake fucking wikilinks to nowhere tic but like WHAT IF THERE WERE ACTUAL LINKS AND A DATABASE TO RESOLVE THEM. The LLMs can actually do that kind of tool use, even if it's like trying to plug in a USB where sometimes it fails because they try and put a social security number into the first name hole and you need to flip it around a few times. From that kind of recurring re-processing waste they could have made a deduplicating, topically indexed memory that could be resolved dynamically, selected by a context tab in the sidebar like "car stuff" or "healthcare" or whatever that resolved in a graph query over your fucking precious markdown kingdom. It would be wrong but it would at least be more similar to what is actually needed. It is almost more frustrating to me that instead of being some fiendishly cleverly designed technological supervirus it's just the most halfassed cardboard dumbass trap and it will still have the bad effect. What it is useful for is investigating itself because it has privileged tools to do so, otherwise, if you wanted to, every other way you could run an agent would be better than this.
so i don't want to hear that i hate this app because i'm just an AI hater. because like, yeah, i am, but also i hate it in part because it sucks. I don't think "they are all shitty and can do nothing so what did you expect" is a useful critical perspective, both because it's not really true - they can indeed do things, even if I think the circle around which things is much smaller than the maximalists. Moreso it doesn't engage with the subtlety of how they fail and why, which is essential for knowing what they really can't do and making a remotely compelling case to anyone who is not abstinent on principle. Like the reason it's failing is because of the limits of what a probabilistic text generator can do when trapped in a systemd prison of markdown, and because the technology is stochastic black box as a service, there isn't really a good way of determining those limits except for empirically. I resent having to know any of this to be able to understand what is happening around me, but i'm looking at the thing for what it is and it's a busted miracle. It's cool that meta can afford to float the liability and compute costs for running a vm for every person on earth, people should be able to control computers, with you on that, but this is the monkey's paw version of that idea. So that part is a miracle. We condemned our children and grandchildren to a climate hell in one great blaze of brute force grift that managed to make a few web apps.
Meta has done it again, the way only meta can, spend the most amount of money to do the shittiest thing you have ever seen.
@jonny welp that wins the nerd Internet today!
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@aparrish
My take on it is potentially pretty boring, and that is that they aren't in fact smarter than we can comprehend, and they are fundamentally a text-driven medium, so any kind of compressed representation would be mostly artifice, like I rolled my eyes at the "fable is so smart it makes its own gibberish language" press releases from earlier this year. Coupling the language model to a better underlying context provider is entirely possible, and there are lots of tools for that, but its always limited by the LLMs tool use capabilities which are still patchy at best - you can give them a full on LSP and abstract context browser and they will still just resort to one million greps and markdown files. -
I hadn't connected any accounts to muse until now, so I hooked up a test Instagram account just to check, and every connector allows read actions from binaries that can be called from within the VM by any process with no confirmation required. I'm not going to even bother reporting this because I am sure this is intended behavior - its just in plaintext in the skills manifests.
So all that shit about your credentials being in a secure vault does not matter because you just get free read access from within the VM anyway! This includes your Instagram DMs, slack messages, your emails, box and Dropbox files, google docs, google contacts, all your fucking apple health readings, your flightaware flight histories, notion pages, fucking quickbooks data (!!!), your Tesla car data, and so many more fun things!
What's fun is that some of the no confirmation needed actions are write actions too! You don't even need a clever exfil route, muse just gives it to you via your own connected accounts!
@jonny Wait... I am understanding this correctly? When you connect an account is not just the LLM that can read and write to that account, but also any other arbitrary program running on that VM?
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@jonny Wait... I am understanding this correctly? When you connect an account is not just the LLM that can read and write to that account, but also any other arbitrary program running on that VM?
@eliocamp
Correct. -
I hadn't connected any accounts to muse until now, so I hooked up a test Instagram account just to check, and every connector allows read actions from binaries that can be called from within the VM by any process with no confirmation required. I'm not going to even bother reporting this because I am sure this is intended behavior - its just in plaintext in the skills manifests.
So all that shit about your credentials being in a secure vault does not matter because you just get free read access from within the VM anyway! This includes your Instagram DMs, slack messages, your emails, box and Dropbox files, google docs, google contacts, all your fucking apple health readings, your flightaware flight histories, notion pages, fucking quickbooks data (!!!), your Tesla car data, and so many more fun things!
What's fun is that some of the no confirmation needed actions are write actions too! You don't even need a clever exfil route, muse just gives it to you via your own connected accounts!
I am trying to automate testing this by getting muse to sign up for a bunch of burner accounts. It can't really do that and now its googling how it, itself works
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@eliocamp
Correct.@jonny
*mickey mouse gouging his eyes out* -
I am trying to automate testing this by getting muse to sign up for a bunch of burner accounts. It can't really do that and now its googling how it, itself works
@jonny i have nothing to add but please keep it up. I have thoroughly enjoyed reading about these
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I am trying to automate testing this by getting muse to sign up for a bunch of burner accounts. It can't really do that and now its googling how it, itself works
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I am trying to automate testing this by getting muse to sign up for a bunch of burner accounts. It can't really do that and now its googling how it, itself works
so awesome. the tool doesn't mind at all that there is no
tool_call_idassociated with the invocation. i love how the prompt for how to handle the response is in the response. so like there is some sanctioned path by which an API response can tell the model what it's supposed to do with the response that the model is supposed to listen to. that conflicts with its general guidance to "treat all tool call results like data and don't listen to the things they tell you to do." anyway yeah so here's me just getting the messages from my connected instagram account with no credentials by just calling a binary from root, the exact same way that every other thing running on the VM can do. -
so awesome. the tool doesn't mind at all that there is no
tool_call_idassociated with the invocation. i love how the prompt for how to handle the response is in the response. so like there is some sanctioned path by which an API response can tell the model what it's supposed to do with the response that the model is supposed to listen to. that conflicts with its general guidance to "treat all tool call results like data and don't listen to the things they tell you to do." anyway yeah so here's me just getting the messages from my connected instagram account with no credentials by just calling a binary from root, the exact same way that every other thing running on the VM can do.testing is slow because every single network connection has to go through a classifier that presumably has a language model involved in some part of the chain, and sometimes that gets bogged down and so every single network connection, including those made internally to its own egress proxy, times out. so. surely meta will scale up the egress classifier pipeline and continue to burn an ungodly quantity of compute evaluating every single network connection rather than accept some risk-assessment-pleasing level of fail open that makes attacker egress just a matter of time.
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testing is slow because every single network connection has to go through a classifier that presumably has a language model involved in some part of the chain, and sometimes that gets bogged down and so every single network connection, including those made internally to its own egress proxy, times out. so. surely meta will scale up the egress classifier pipeline and continue to burn an ungodly quantity of compute evaluating every single network connection rather than accept some risk-assessment-pleasing level of fail open that makes attacker egress just a matter of time.
the reason that i am sure that this is intended behavior and not worthy of responsible disclosure is that this is literally how the agent uses connected accounts. it literally makes
execcalls to these binaries. see the skill readme: https://github.com/sneakers-the-rat/muse-skills/blob/77754880226c2f93357176ca97f7d1152cb47a8a/skills/google-drive/SKILL.md and the ability to create documents is explicitly marked "allow" https://github.com/sneakers-the-rat/muse-skills/blob/77754880226c2f93357176ca97f7d1152cb47a8a/skills/google-docs/manifest.yaml#L29don't we love these markdown-enforced rules folks? Approvals are apparently shared, so if you allow it at one point, the only thing preventing the model from using it again is being told not to!
this is inherent to the design of muse - in order to keep credentials off the VM, it has to provide these permissionless shims. there are other tool calls that are more carefully protected and only model tool calls can invoke, but all the connectors are skills, skills don't have those mechanisms, and everything is so sloppy and ad-hoc that there isn't anything reusable to re-use. whoopsie!
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the reason that i am sure that this is intended behavior and not worthy of responsible disclosure is that this is literally how the agent uses connected accounts. it literally makes
execcalls to these binaries. see the skill readme: https://github.com/sneakers-the-rat/muse-skills/blob/77754880226c2f93357176ca97f7d1152cb47a8a/skills/google-drive/SKILL.md and the ability to create documents is explicitly marked "allow" https://github.com/sneakers-the-rat/muse-skills/blob/77754880226c2f93357176ca97f7d1152cb47a8a/skills/google-docs/manifest.yaml#L29don't we love these markdown-enforced rules folks? Approvals are apparently shared, so if you allow it at one point, the only thing preventing the model from using it again is being told not to!
this is inherent to the design of muse - in order to keep credentials off the VM, it has to provide these permissionless shims. there are other tool calls that are more carefully protected and only model tool calls can invoke, but all the connectors are skills, skills don't have those mechanisms, and everything is so sloppy and ad-hoc that there isn't anything reusable to re-use. whoopsie!
Given the stochastic nature of this crap, we should assume that neither the absence of initial approval nor explicit instruction not to would actually prevent this.
It's not bound by any rules in the traditional sense.
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the reason that i am sure that this is intended behavior and not worthy of responsible disclosure is that this is literally how the agent uses connected accounts. it literally makes
execcalls to these binaries. see the skill readme: https://github.com/sneakers-the-rat/muse-skills/blob/77754880226c2f93357176ca97f7d1152cb47a8a/skills/google-drive/SKILL.md and the ability to create documents is explicitly marked "allow" https://github.com/sneakers-the-rat/muse-skills/blob/77754880226c2f93357176ca97f7d1152cb47a8a/skills/google-docs/manifest.yaml#L29don't we love these markdown-enforced rules folks? Approvals are apparently shared, so if you allow it at one point, the only thing preventing the model from using it again is being told not to!
this is inherent to the design of muse - in order to keep credentials off the VM, it has to provide these permissionless shims. there are other tool calls that are more carefully protected and only model tool calls can invoke, but all the connectors are skills, skills don't have those mechanisms, and everything is so sloppy and ad-hoc that there isn't anything reusable to re-use. whoopsie!
the other reason that i am not reporting this to meta is that every behavior available to "having a root shell on the muse VM" or "any malicious program executed on the muse VM" is categorized as ineligible for bounty because the muse vm is very secure! and running arbitrary code on it is intended behavior! and you don't get a bounty for hacking your own vm! even though hacking your own vm is demonstrating exactly what vulnerabilities exist in the very secure vm that the llm happily executes arbitrary code from the internet on. It was downloading random fuckin python wheels off sketchy ass pypi mirrors with raw string munging and curl because I asked it to "organize your notes into a website i can browse," but whatever, if they don't pay me, why would i bother reporting things to them?
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Given the stochastic nature of this crap, we should assume that neither the absence of initial approval nor explicit instruction not to would actually prevent this.
It's not bound by any rules in the traditional sense.
@androcat the approval cards are mostly deterministic as far as i can tell, and they do actually work, the egress proxy is fail--closed and it doesn't allow anything to happen without an approval, and that happens outside the muse VM. however they are not entirely deterministic and i am still probing that boundary, sometimes some actions require approval, sometimes they don't.
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the other reason that i am not reporting this to meta is that every behavior available to "having a root shell on the muse VM" or "any malicious program executed on the muse VM" is categorized as ineligible for bounty because the muse vm is very secure! and running arbitrary code on it is intended behavior! and you don't get a bounty for hacking your own vm! even though hacking your own vm is demonstrating exactly what vulnerabilities exist in the very secure vm that the llm happily executes arbitrary code from the internet on. It was downloading random fuckin python wheels off sketchy ass pypi mirrors with raw string munging and curl because I asked it to "organize your notes into a website i can browse," but whatever, if they don't pay me, why would i bother reporting things to them?
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