Sounds like a hallucination unless proven otherwise, even the leading LLMs can do those from time to time, and they will always appear plausible like that. Also could be the session having a lot previous context, like 800K+, which (I think) makes hallucinations more likely.
Relevant comment from the OP which makes a hallucination more likely:
> There is one tool call result that includes a string that printed a pathname including minecraft.py because it was listing the files in a Python virtual environment and the Pygments package has a lexer called minecraft.py
I realize hallucination has no precise definition but this doesn’t sound at all like anything I’ve ever heard called hallucination. Hallucination is usually plausible wrong answers or made up info that ends up fitting the most likely response (like a manufactured citation) and comes from the way LLMs work at predicting tokens. This example demonstrates completely implausible output, it’s not something that fits with hallucination.
All that said, it doesn’t require cross session leakage, it could just be training data or like those nightingale (probably the wrong bird*) data generations where they just prompt an LLM with nothing and it starts spitting out conversations.
I see a bunch of downstream comments about caching, sounds like maybe there’s an error where it loads nothing instead of the cache and so starts spitting out random generations.
* edit: it’s magpie. Worth looking at the concept, I’m not sure people realize they LLMs generate random conversations when prompted with nothing, this seems at least as likely as sessions leaking: https://github.com/magpie-align/magpie
The person posting this claims to have reproduced in a separate context down the thread:
> Same thing just happened on a Claude Mobile session in same Enterprise account. Common theme in both is Sonnet 5, first response after more than 5 minutes (cache miss).
Not sure the relevance of this comment, but normally if someone built a classifier that bad they’d be fired. Anthropic obviously thinks they have some monopoly power they can use to foist garbage on consumers, I think they don’t.
Note the repro condition: first response after 5+ min, i.e. a cache miss. A cache leak would show up on hits (someone else's cached prefix), not on misses where everything is recomputed from your own tokens.
fwiw, this could be a bug but the submitters level of arrogance places this rather high on the dunning-kruger side of things. There are multiple other plausible explanations, but this person is probably vibe coder who believes anything an llm says (including explaining its own hallucinations)
it’s the wet dream of execs and pm types. however, i have not seen anything close to it in my life. I remember the UML days, lol. the issue is not the code, it’s the translation layer between business and code. maybe someday ai bridges that gap. history has shown probably not
The funny thing is at my current employer, they mentioned that "coding is increasingly becoming a solved problem" and in the same breath, mentioned that one project was too hard for anyone to do so they're not doing it and would rather sell existing features...
Sure but have you ever seen it actually play out in practice like it currently is? Whether or not it's true (of course it's not) people are currently behaving as if it is and firing/hiring accordingly.
Well, when was the last time you wrote machine code by hand?
... but then they went and changed what coding meant.
We've always been layering abstractions on top of abstractions. If we get to an abstraction that works well enough that you no longer have to dive down into the previous layer, we say we've solved coding, and change what coding means. Obviously LLMs aren't there yet.
I love that quote, especially considering the insane amount of bugs that are produced.
It’s as easy to debunk as someone claiming ”I can jump to the moon”.
Caching doesn’t work the way the bug reporter implies. Caches are shared (at least across the enterprise), but its key is always a function of the input before it.
We achieved significant savings simply by moving everything that varies across individuals out of the system prompt so every session starts from a cache point.
For example you never want your system prompt to start with the time that the session started. Move that to the first user message if needed.
Yeah there's quite a lot of potential bugs that could have this shape. If I were to guess it could be a buffer in a buffer pool not being sized and zeroed correctly, allowing stale data to bleed between sessions.
Hash functions necesarily have collisions. Also, it is perfectly possible to introduce bugs in the hash function (hash inputs, hash function itself) that allows cross account contamination.
0 evidence. If this were a real privacy leak, the author would ask their coworker if they talked about the unexpected topic instead of
>"Maybe my coworker was talking about this in another session?"
This would be a critical bug that would slash the market value of a T$ company significantly, go ask your coworker or close the ticket, why do you expect the devs to put an enormous amount of effort hunting a potentially inexistent if you can't make that minuscule debugging effort.
Interestingly I had an almost identical experience to this report in codex. It output a user memory file that looked awfully real and wasn't at all related to my work.
If I had to hazard a guess, doing anything in a multi-tenant way on a GPU is going to be hard mode compared to most SaaS due to lack of memory safe tooling. I've built multi-tenant SaaS systems, and I've done a little GPU programming (a long time ago), but I've never tried to combine the two disciplines.
What is the probability that two customers will have exactly the same tokens in cache? Wouldnt it require using the exact same CLAUDE.md, skills, MCPs and context? After that it is even worse since the nondeterminism of LLMs and humans
I suspect what GP is getting at is there will be a strong incentive to implement some structural sharing across tenants to avoid redundantly storing the same tokens over and over. At least I'd be tempted to do this if I was working with a very precious, constrained resource (e.g. VRAM). Doing this correctly seems.. very difficult. [edit] To answer your question directly: the probability that the entire cache is identical between two different users is very low, but the probability that there exists identical chunks of cache between two different users is very high. Exploiting those commonalities successfully will significantly compress the data.
Relevant comment from the OP which makes a hallucination more likely:
> There is one tool call result that includes a string that printed a pathname including minecraft.py because it was listing the files in a Python virtual environment and the Pygments package has a lexer called minecraft.py
All that said, it doesn’t require cross session leakage, it could just be training data or like those nightingale (probably the wrong bird*) data generations where they just prompt an LLM with nothing and it starts spitting out conversations.
I see a bunch of downstream comments about caching, sounds like maybe there’s an error where it loads nothing instead of the cache and so starts spitting out random generations.
* edit: it’s magpie. Worth looking at the concept, I’m not sure people realize they LLMs generate random conversations when prompted with nothing, this seems at least as likely as sessions leaking: https://github.com/magpie-align/magpie
> Same thing just happened on a Claude Mobile session in same Enterprise account. Common theme in both is Sonnet 5, first response after more than 5 minutes (cache miss).
It's unfortunate that there is so little transparency that even if they deny there was a leak we will never know for certain.
"Recipe for red-braised pork, I have pork shoulder"
"Write up a framework for MCP patterns I can give to claude code"
"explain the biomechanics of motion in c. elegans" (I get this one, I mostly did it to test and it's related to my hobby project)
Do we get an extra day of functional Fable 5 because it's down?
... but then they went and changed what coding meant.
We've always been layering abstractions on top of abstractions. If we get to an abstraction that works well enough that you no longer have to dive down into the previous layer, we say we've solved coding, and change what coding means. Obviously LLMs aren't there yet.
We achieved significant savings simply by moving everything that varies across individuals out of the system prompt so every session starts from a cache point.
For example you never want your system prompt to start with the time that the session started. Move that to the first user message if needed.
>"Maybe my coworker was talking about this in another session?"
This would be a critical bug that would slash the market value of a T$ company significantly, go ask your coworker or close the ticket, why do you expect the devs to put an enormous amount of effort hunting a potentially inexistent if you can't make that minuscule debugging effort.
I haven't had much issue with Codex, but seems Claude Code has major issues being reported nearly on the daily.
They also happen to be the most boastful about not reading or looking at the code.
LLMs are very capable, but not nearly to the level they seem to be messaging.
(We've actually moved on from vibe-coding to having the LLM vibe code itself in a loop)
The businesslatin name for this is Recursive Self-Improvement