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_operatorcommand, creating a significant vector for running unverified code. - [EXTERNAL_DOWNLOADS]: The skill facilitates the installation of missing Python dependencies using
pip installtriggered 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 viapip install, and local application serving vialaunch_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