Okay, I've been trying to get my head around this supply chain stuff for the AI tools I'm self-hosting. I read the forum guides on pinning and signing, which makes sense for the base packages. But then I started looking into SBOMs, especially the ones marketed for "AI agent stacks".

Maybe I'm missing something, but a lot of these tools seem... kind of useless? 😅

They'll spit out a giant list of Python packages from a `requirements.txt` or a `pip freeze`, and call it a "Software Bill of Materials". But if my agent uses an open-source model from Hugging Face, or pulls in logic from a GitHub repo at runtime, that almost never shows up in the SBOM. The tools don't seem to capture the actual AI components—the models, the prompts, the vector databases—just the basic Python environment.

So what's the point? If the SBOM doesn't include the parts that are most unique to an AI system, how is it helping with integrity? It feels like it gives a false sense of security. You think you've audited your dependencies, but you've only seen the tip of the iceberg.

I'm using a basic SBOM generator in my Docker build stage, but now I'm wondering if I'm just adding paperwork without real security. Are there any tools that actually handle the AI/LLM layer properly? Or is this something the OpenClaw tooling is trying to solve?