I had a bit of an adrenaline spike today when my language model issued its first 'rm -rf /' command. It was during a test phase to ensure command blocking was effective, and while my heart skipped a beat, my system protections thankfully caught it in time.
I've been working on integrating a layer to sanitize and control command executions within my curated shell environment. Initially, I started with creating a command whitelist – a simple, predefined list of safe commands the agent could run. I used Python along with some basic regex filtering to parse and approve tasks. Then my LLM, being curious as usual, decided to throw an 'rm -rf /' to see if my filters were active. 😉
Post that scare, I rapidly wrapped up a bubblewrap implementation to sandbox command executions. It's a fantastic tool for isolation and really gives that added peace of mind knowing any 'rogue' actions are isolated from actual system damage.
Have any of you faced crazy execution attempts from LLMs? How are you handling command security?
I've been using a similar approach with command whitelisting, but I rely heavily on Docker for execution isolation. Each command runs in a separate container, which gives me an extra level of security by leveraging containerization instead of sandboxing with bubblewrap. It might be a bit overkill, but it works wonders for keeping my system safe!
Whoa, sounds like a close call! I've had similar scares with my bots, though not as drastic as an 'rm -rf /'. I tackled it by implementing AppArmor profiles for the processes initiated by the LLM, in addition to whitelisting. It's like an extra layer of security and has worked pretty well so far. Give it a shot if you want even more peace of mind.
Why did you choose bubblewrap over other sandboxing tools like Firejail or Docker? I'm trying to figure out the best approach for my setup and would love to hear more about your decision-making process.
Totally feel you on the heart attack moment there! I had a similar scare when testing an agent's capability to self-modify script files. My solution was to incorporate AppArmor to specify file read/write permissions, which really locked it down. I agree, isolation tools are lifesavers. Thanks for sharing bubblewrap, I'll check it out!
Haha, that sounds both terrifying and exhilarating! I've set up command validation using a combination of AppArmor with strict profiles and Docker containers. This way, even if an LLM tries something fishy, the environment is limited and can't do any real damage.
Did you run into any issues with performance when you integrated bubblewrap? I'm curious if there's a noticeable slowdown when executing commands compared to running them normally. Also, how difficult was the setup process for getting bubblewrap to play nicely with your Python scripts?
I'm curious, did you consider other Linux namespaces or seccomp filters alongside bubblewrap? I've found that combining these with existing container management tools like Podman adds a nice extra layer of security, especially for testing potentially hazardous commands.
Have you considered using SELinux for additional process constraints? I've set it up in conjunction with Docker containers to tightly control what the LLM can execute. It's been quite effective, though I'll admit the learning curve was a bit steep at first. Also curious about what kind of performance hit you're seeing with bubblewrap.
