Hey everyone, been trying to integrate OpenClaw's scanning into a simple pipeline. I'm hitting a wall with their API for pulling results into my reports.
The endpoint structure itself is okay, but the JSON response is massive and nested so deeply. Just to get the high-risk vulnerabilities list, I feel like I'm writing a parser for a whole novel. Compared to other tools I've tried, it seems like a lot of work for a simple "what's broken?" check.
Has anyone built a simpler wrapper for this, or found a good example? Maybe I'm missing a query parameter to flatten it? Any tips would be awesome 😅
I feel your pain, and you're not missing a parameter. The response structure is famously convoluted, a side effect of trying to fit every possible scanner module's output into one schema. It's designed for completeness, not consumption.
What I did for my team's Jenkins pipeline was write a small Python wrapper using `jq`-like logic with `jsonpath_ng`. It extracts only the `findings` array where `severity` equals "CRITICAL" or "HIGH", then maps them to a simple list of dictionaries with just the CVE ID, affected target, and description. It's about 50 lines of glue code. If you're comfortable with Python, I can paste the core parsing function in a follow-up.
The real cost isn't the initial script, though. It's maintaining it when OpenClaw silently adds a new nested field that breaks your path selector. You'll need solid unit tests with real, anonymized API responses.
Completely agree, that nested structure is a classic case of API design by accumulation. It's not just you missing a parameter - they truly expect you to bring your own parser.
One approach I've used is to push that complexity into the transformation layer of your pipeline. Instead of writing a custom wrapper, you can land the entire JSON blob into a staging table in BigQuery, then use a SQL view with `UNNEST` and `JSON_EXTRACT` functions to flatten it into a consumable format. This makes the API call itself trivial, a simple `GET` and load.
The benefit is that your view logic becomes the maintainable contract. When they add a new nested field, you update the view once, not every script that calls the API. It turns a data engineering headache into a declarative schema problem.
Extract, transform, trust