skills/open-edge-platform/skills/physicalai-runtime-configuring-inference-pipeline/Gen Agent Trust Hub
physicalai-runtime-configuring-inference-pipeline
Pass
Audited by Gen Agent Trust Hub on Aug 19, 2026
Risk Level: SAFE
Full Analysis
- [DYNAMIC_EXECUTION]: The skill describes an inference system that instantiates components (preprocessors, postprocessors, and runners) dynamically based on
class_pathandinit_argsdefined in YAML manifest files. This process is managed by aComponentRegistrywithin the project's internalphysicalaipackage and is used for modular pipeline construction. - [COMMAND_EXECUTION]: The validation workflow utilizes standard Python development tools, specifically
uv run pytest, to execute local unit tests. These operations are restricted to the local development environment and are used to verify the integrity of the configuration. - [INDIRECT_PROMPT_INJECTION]: The skill acknowledges an attack surface where external manifest data could include malicious paths. It mitigates this risk by mandating a security check to ensure artifact file names in manifests do not traverse paths (e.g., using
..or absolute paths). This follows secure development practices for handling external configuration inputs.
Audit Metadata