fiftyone-dataset-inference

Fail

Audited by Gen Agent Trust Hub on Sep 14, 2026

Risk Level: HIGHREMOTE_CODE_EXECUTIONEXTERNAL_DOWNLOADSCOMMAND_EXECUTIONDYNAMIC_EXECUTIONINDIRECT_PROMPT_INJECTION
Full Analysis
  • [REMOTE_CODE_EXECUTION]: The README.md file contains an installation instruction using curl -sL skil.sh | sh, which downloads and executes a remote script directly in the system shell without verification.
  • [DYNAMIC_EXECUTION]: The SKILL.md workflow includes Path C, which allows for the execution of models loaded from arbitrary remote GitHub repository URLs via the execute_operator command, creating a significant vector for running unverified code.
  • [EXTERNAL_DOWNLOADS]: The skill facilitates the installation of missing Python dependencies using pip install triggered by the agent's interaction with the FiftyOne environment.
  • [COMMAND_EXECUTION]: The skill involves direct execution of shell commands for system configuration and software package management.
  • [INDIRECT_PROMPT_INJECTION]: The skill is susceptible to indirect prompt injection through data processed from datasets or instructions embedded in remote model sources.
  • Ingestion points: Sample data from FiftyOne datasets and content from user-provided remote GitHub repository URLs.
  • Boundary markers: No explicit delimitations or safety warnings are implemented to isolate untrusted data or model code from the agent's core instruction set.
  • Capability inventory: Includes capabilities for code execution via execute_operator, software installation via pip install, and local application serving via launch_app.
  • Sanitization: There are no verification steps described for the integrity of external repositories or the content of the datasets being processed.
Recommendations
  • AI detected serious security threats
Audit Metadata
Risk Level
HIGH
Analyzed
Sep 14, 2026, 02:54 PM