MARL — Multi-stage Reasoning Middleware

• Outcome: Review
• Latest audit: May 29, 2026 at 9:23 PM UTC
• Version:
  1.0.0

Overview

This skill is plausible LLM middleware, but users should review it because it routes all model traffic through third-party software while making an overbroad local-only privacy claim.

Review before installing. Use this only if you trust the VIDRAFT Docker/PyPI package and understand that prompts may be processed by MARL and sent to the configured LLM provider unless you use a fully local backend. Prefer pinned versions, avoid sensitive data until data handling is clear, and use local models when data must stay inside your own infrastructure.

SkillSpector

By NVIDIA

Vulnerability Patterns

• Data Exfiltration: External Transmission, Env Variable Harvesting, File System Enumeration
• Prompt Injection: Instruction Override, Hidden Instructions, Exfiltration Commands
• Privilege Escalation: Excessive Permissions, Sudo/Root Execution, Credential Access
• Supply Chain: Unpinned Dependencies, External Script Fetching, Obfuscated Code
• Excessive Agency: Unrestricted Tool Access, Autonomous Decision Making, Scope Creep

Findings (1)

Missing User Warnings

Medium

• Confidence: 92% confidence
• Finding: The skill explicitly routes all LLM traffic through a local middleware that then makes API calls to a user-selected upstream model, but the documentation frames this as 'your data never leaves your infrastructure' without clearly qualifying that prompts and related context may still be forwarded to external providers depending on configuration. This creates a real risk of unintentional data disclosure because users may send sensitive prompts under a misleading assumption of full local processing.

VirusTotal

66/66 vendors flagged this skill as clean.