seaborn
Pass
Audited by Gen Agent Trust Hub on Apr 9, 2026
Risk Level: SAFE
Full Analysis
- [EXTERNAL_DOWNLOADS]: The skill demonstrates the use of
sns.load_dataset(), which programmatically fetches sample datasets from Seaborn's official public GitHub repository. This is a standard feature of the library used for educational and demonstration purposes. - [DATA_EXFILTRATION]: No patterns of unauthorized data exfiltration or credential harvesting were detected. The skill uses standard local file operations such as
pd.read_csv()andfig.savefig()to load and store data/visualizations within the project environment. - [COMMAND_EXECUTION]: There are no instructions or examples that involve arbitrary shell command execution, subprocess spawning, or system-level configuration changes.
- [PROMPT_INJECTION]: The content is strictly technical documentation and does not contain any instructions aimed at overriding agent behavior, bypassing safety filters, or extracting system prompts.
- [SAFE]: The skill relies on well-known, established Python packages including
seaborn,matplotlib,pandas,numpy, andscipy. All dependencies and external references are consistent with the skill's stated purpose of statistical visualization.
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