hdf5-pde-data-loading
Patterns for loading PDE simulation datasets (PDEBench, PhiFlow, JAX-CFD) from HDF5 files. Handles layout detection (single tensor vs separate variables), spatial/temporal downsampling, multi-variable systems, HuggingFace and DaRUS data sources, and efficient PyTorch DataLoader creation. Use when preparing PDE data for neural operator training.
75
93%
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Low
Low-risk findings worth noting
Low
Low-risk findings.
1 low severity finding. Worth noting, but not necessarily harmful.
W011: Third-party content exposure detected (indirect prompt injection risk).
What this means
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
Why it was flagged
The required workflow includes runtime ingestion of outsider-authored free text because it fetches a CSV from `raw.githubusercontent.com` (public web content) and decodes it into strings (`urllib.request.urlopen(csv_url).read().decode()`), which is then split/used at runtime to determine dataset file identifiers/URLs.
- Repository
- synthetic-sciences/openscience
- Commit
52845c3
- Audited
- Security analysis
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