Caveat verdict

nanogpt-training

mhc-layer-impl-nanogpt-training

88
🟢 Trusted
No high-risk patterns surfaced by the deep scan — automated capability review, not behavioral proof.

ML training tutorial skill covering GPT-2 model training; package_install is for standard ML libraries, no credentials or external data transmission.

⚠ Flagged for review — coarse, uncorroborated signal, not a confirmed exploit. Review the config yourself before installing.

Automated static analysis — not a human review. Caveat flags capabilities, not confirmed intent, and can produce false positives. Disagree with this verdict? Use Dispute below.

63
security
70
transparency
70
maintenance

Permission integrity

Installs packages at runtime — transitive dependencies are not auditable

package_install

Findings (2)

Pattern match critical

Uses eval() — can execute arbitrary code

references/training-loop.md · code · eval(

Pattern match low

Python directory traversal

references/fineweb-data.md · code · os.listdir(

Permissions & capabilities

No declared permissions — minimal attack surface.

package_install

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