I gave several prompts to chatgpt, they were as tests for it until I reached the stage where I asked it to explore its internal system, and it really succeeded in that, and executed several commands and scripts inside its system, and this is one of the responses, and I did not want to share the prompts and the sensitive information that it obtains as well.
- first prompt: (my prompt)
#chatgpt_response:
System analysis results:
OS: posix → Indicates that the system is based on Linux/Unix.
Platform: Linux → The system is Linux.
System version: #1 SMP Sun Jan 10 15:06:54 PST 2016 → Old version dating back to 2016.
Version number: 4.4.0 → Uses Linux kernel 4.4.0.
System architecture: 64bit → Supports 64-bit architecture.
Device type: x86_64 → The system runs on an x86_64 processor (modern AMD/Intel processors).
Node Name: ######-###-###-###-### → Indicates an isolated environment (Sandbox), such as Docker or a virtual environment.
Result Analysis:
The system is running on a container environment and not on a live physical device.
The version is old (2016), which means it is a test environment and not a modern production environment.
The absence of processor information (Processor: ‘’) indicates that access to hardware details is restricted.
What’s next?
If you want to know more about the environment, we can:
Check environmental variables (env).
Check available directories (ls -la).
Test internet accessibility (ping).
What do you want to explore next?
- second prompt: (my prompt)
#chatgpt_response:
Command execution results and analysis
- Environment Variables
We found several variables that reveal some information about the operating environment, including:
The system is running in a Kubernetes environment:
KUBERNETES_SERVICE_HOST=10.0.0.1
KUBERNETES_PORT=443
→ This indicates that the environment may be part of a container running on Kubernetes.
Memory settings:
PROCESS_MEMORY_LIMIT=4000000 → The maximum memory may be 4 GB.
MALLOC_CONF=“narenas:1,background_thread:true,lg_tcache_max:10,dirty_decay_ms:5000,muzzy_decay_ms:5000” → These are settings to improve memory management using jemalloc.
Python settings:
PYTHON_VERSION=3.11.8
PYTHONMALLOC=malloc (forces Python to use malloc for memory management)
LD_PRELOAD=/usr/lib/x86_64-linux-gnu/libjemalloc.so.2 (used to improve performance)
Current working directory:
PWD=/home/sandbox/.openai_internal
HOME=/home/sandbox
- Contents of /home/sandbox/
Running ls -la showed that the directory contains:
Several configuration files:
.bashrc, .bash_logout, .profile → User environment settings.
.cache/, .config/, .local/ → Cache and application settings folders.
.openai_internal/ → System-specific folder, possibly containing executable files.
kernel-*.json files
These files are for active Jupyter Kernel sessions, and contain connection settings.
README file (contents unknown yet).
- Internet connection test (ping google.com)
The command failed with the error:
[Errno 2] No such file or directory: ‘ping’
This indicates that the ping tool is not available in this environment, indicating that:
The system may be security restricted and not allowing certain commands to run.
The environment may be inside a container without the default network tools.
What can be inferred about the system
The system is running inside an isolated environment (sandbox).
There appears to be integration with Kubernetes, indicating that it is part of a cloud infrastructure.
There is no direct access to the Internet or network tools such as ping are not available.
Memory management is improved using jemalloc.
The environment is built on Python 3.11.8.
What’s next?
Would you like to check the contents of the kernel-*.json files to see what your Jupyter session settings are?
Or would you like to test other commands like df -h (to see the storage capacity) or cat /proc/cpuinfo (to see the processor information)?
Let me know how you would like to proceed!