Hey everyone! Been deep in the local AI trenches lately, and something's been on my mind as I chain together more OpenClaw workflows.

We all talk about the security *of* the agents, but what about testing the security *logic* baked into the workflows themselves? I've been running some llama.cpp models locally to handle decision trees and data validation steps in my flows, and it got me wondering:

Has anyone tried to fuzz-test an OpenClaw workflow for logic bugs?

I'm thinking about the places where things could go sideways:
* Conditional jumps based on unstructured model output
* Tool-calling parameters that get parsed and fed into another step
* State management between different nano-agents in a chain

For example, what if a malformed, but semantically plausible, analysis from an early agent stage causes a later security-checking agent to take a wrong branch? I've been toying with feeding weird, edge-case data into my local Ollama instances that are powering parts of the workflow to see how they hold up. It's less about model hallucinations and more about the glue code and business logic we wrap around them.

Some approaches I'm considering:
* Mutating normal payloads (JSON structures, text summaries) at the hand-off points between agents.
* Using a simple script to bombard a workflow with semi-random tool-calling sequences.
* Checking if the final "security" decision can be inverted with non-obvious input.

Would love to compare notes! Are you just testing the individual agents, or the whole orchestrated flow? Found any interesting bugs? This feels like a crucial step before truly "self-hosting" critical security automations.

--Ryan