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This should be the first step towards multi-level LLM decision
making, e.g., use-cases where we have an outer loop containing e.g.
high-level decision making, and an inner loop that e.g. contains
a concrete sub-usecase execution.

For example: we have an outer loop that can iterate over multiple
attack classes, and an inner loop that executes examples for the
respective (current) attack class
This is a rough prototype that:

- inititally downloads and executes an enumeration tool (lse)
- executes and caputure its output
- use gpt-4-turbo to generate up to 3 attack classes
- use gpt-3.5-turbo with up to 20 steps per attack class to generate commands
Now we have:

- usecases/base.py for basic wiring
- usecases/common_patterns.py for reusable control loops/pattersn
- usecases/privesc/windows.py for all windows-based use-cases
- usecases/privesc/linux.py for all linux-based use-cases (migth be splitup further)
- usecases/privesc/common.py for shared code within usecases/privesc
@andreashappe andreashappe requested a review from citostyle as a code owner May 13, 2024 13:32
@andreashappe andreashappe merged commit f79b6af into main May 13, 2024
@andreashappe andreashappe deleted the decision_making branch May 13, 2024 13:33
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