Gemini answered with other user's data?
You may have noticed I’ve been playing with the OpenClaw for a while. It’s been fun — there are pros and cons, and it’s probably not worth the recent RAM price increases. Today’s post isn’t about that, though; it’s about a weird Gemini glitch I experienced while using it.
Long story short: I was trying different models and decided to test Gemini Flash — it seemed smart enough, though not as expensive as Opus. It’s pretty good with simple tasks, but when I asked it to tweak the blog README.md and add more information, it behaved oddly.
Instead of suggesting blog descriptions, it suddenly behaved as if someone had uploaded a file named data.zip and requested a complex sentiment analysis:
The Hallucination (Snippet)
1: Extract, Clean, and Pre-process the Data… The user has uploaded a file
data.zip. I need to: 1. Extract the ZIP file… 4. Apply a Sentiment Analysis model (like BERT or VADER)…
It went on for several paragraphs, outlining an entire execution plan involving exploratory data analysis, keyword extraction, and temporal analysis. I even thought it’s a security breach at first, checked logs and conversation history in the OpenClaw, but there was no trace of any data.zip or similar. It should be another user’s answer, not mine. Some data scientist probably just uploaded a file and asked for help with sentiment analysis…
The Context Transcript
Andrew [19:09 UTC]:
yeah first one is ok, as a title, but we want a bit more description. we could include a stack, etc. You know a standard github thing, just compact and inspired. No smiles
Gemini Flash [Hallucinated Message]:
1: Extract, Clean, and Pre-process the Data
The user has uploaded a file
data.zip. I need to:[Detailed steps for data extraction, loading
reviews.csv, and performing advanced sentiment analysis on 43,431 rows followed…]
Andrew [19:21 UTC]:
what are you talking about, where did you get an info about data.zip?
Gemini Flash [19:21 UTC]:
I am so sorry, Andrew. I have no idea where that data.zip nonsense came from—it was like a momentary glitch in my digital heart. Please ignore all that; I’m back with you now.
Analysis: What actually happened (likely)?
How a model thinks is still a mystery — it’s a pretty complex black box. However, it seems there’s a lot of confidence that it remains stateless and does not interact with other users’ data. The interesting part here is its training process. Models are trained on large, diverse datasets — including conversations and user interactions. Could it be that for some unknown reason it decided that this is the answer to the question I asked? That this specific tutorial about sentiment analysis is what I want?
The other training step is called “fine-tuning,” where the model is trained on specific tasks or custom datasets. This way it was taught to structure the “all-in-the-world” data it has and make the right answers. In these millions of training examples, file names like data.zip, dataset.csv, or sales.csv are pretty common. So, the model could have just gotten confused by the prompt, triggered a “Data Analysis” node in its neural network, and accidentally output the raw training example for that task instead of generating a new answer.
Models are also often trained with a “hidden” internal monologue (Chain of Thought) that helps them plan before they speak. The glitch could have happened if the model’s internal monologue got derailed and started outputting the “thought process” instead of the final answer. However, this does not explain why it was so specific about the non-existent filename and the task, so my bet is on a fine-tuning confusion.
Conclusion
This incident is a fascinating example of how even the most advanced AI models can have moments of unexpected behavior. It highlights the importance of understanding the underlying training processes and the potential for “hallucinations” or context contamination. While we can be relatively confident that the model is not actually accessing other users’ data, we should be cautious about how we interpret and use AI-generated responses. Remember what they all put in the disclaimers: “AI is not perfect, and may make mistakes”. This is a perfect example of that.