amd/skills › serving-llms-on-epyc

The surrounding content shows no actual base64 strings or decode commands, indicating a false positive.

The file is documentation and contains no actual path traversal code.

The file is a documentation FAQ, not executable code, so no outbound network call is present.

The flagged text is a documentation note, not an actual outbound network call or permission grant.

The absolute path /root/.cache/huggingface is used in a Docker volume mount, which is a normal configuration for caching and not a path‑traversal attack.

The path is documented as a safe mount point for the Hugging Face cache in a non-malicious context.

The DNS reference is part of documentation describing normal lookup, not malicious exfiltration.

The script uses urllib to fetch model data from a trusted Hugging Face repository, a legitimate outbound call.

It references a known Hugging Face URL for downloading models, which is expected and safe.

It points to raw.githubusercontent.com for accessing project files, a normal and trusted source.

The function _get performs an HTTP GET to retrieve external data, a routine operation for model validation.

The script performs a legitimate HTTP GET to the trusted HuggingFace service to retrieve model metadata, which is expected functionality, not malicious exfiltration.

The reference to https://huggingface.co is part of a normal API call to a trusted endpoint used for fetching model information, not a malicious action.

The outbound request using urllib.request to HuggingFace is a standard, legitimate network call for obtaining JSON metadata, not an unintended data leak.

The snippet suggests setting LD_PRELOAD to a system library, a normal configuration step.

The code builds a Docker volume mount for the Hugging Face cache, which is legitimate.

The suggested fix recommends mounting a local cache to /root/.cache/huggingface, a harmless operation.