@melaya/runner@1.1.33
Run Melaya AI pipelines locally with your own LM Studio or Ollama models
AI Security Review
scanned 2mo ago · by lpm-firewall-aiThe source establishes a real remote-code-execution and credential/session-handling capability, but it is activated through the package's explicit runner workflow rather than covert installation behavior. Static inspection does not establish a separate malicious endpoint or unconsented install hook.
Decision evidence
public snapshot- The runner downloads a server-supplied Python bundle and writes its files into a persistent user cache.
- A socket event accepts Python source, writes it to main.py, and starts it as a subprocess.
- The Luma flow saves browser session state, including authentication material, for later automated use.
- The package accesses local AI-provider credentials to query provider APIs.
- package.json has no install, preinstall, or postinstall hook; its only lifecycle script is prepublishOnly.
- The executable requires an explicit CLI invocation and runner token.
- Browser provisioning requires an explicit download option in its dedicated provisioner.
Source & flagged code
8 flaggedPackage source references child process execution.
dist/uvBootstrap.jsView on unpkg · L20Findings
Affected versions and remediation
This report applies to @melaya/runner@1.1.33.
See all versions of @melaya/runner for other recorded verdicts.
- Review the evidence and your use of @melaya/runner@1.1.33 before allowing it. Restrict the permissions described in this report.
- Choose an independently verified alternative or release. This report does not establish that other versions are safe.
Evidence last updated: .
Think this verdict is wrong? Dispute it on GitHub or read how reports are produced.