I have a set of tools which build prompts describing the environment and the output of vulnerability scans. The tool then requests a shell script to disable/fix/update the vulnerability. The script is submitted as a PR which has actions that run integration tests. Human intervention is sometimes needed, but the focus is on better engineering of prompts (and by proxy tooling).
Describing the environment relies heavily on my CMDB (Combodo’s iTop) so this is not a one-size-fits-all approach and this is functioning entirely in my personal lab of ~100 servers. That said, ChatGPT has given me the best results compared to locally run LLMs
I have a set of tools which build prompts describing the environment and the output of vulnerability scans. The tool then requests a shell script to disable/fix/update the vulnerability. The script is submitted as a PR which has actions that run integration tests. Human intervention is sometimes needed, but the focus is on better engineering of prompts (and by proxy tooling).
Describing the environment relies heavily on my CMDB (Combodo’s iTop) so this is not a one-size-fits-all approach and this is functioning entirely in my personal lab of ~100 servers. That said, ChatGPT has given me the best results compared to locally run LLMs