statsmodels

Pass

Audited by Gen Agent Trust Hub on Jul 14, 2026

Risk Level: SAFE
Full Analysis
  • [SAFE]: The skill is entirely informational, providing boilerplate code and best practices for the statsmodels library. There are no signs of malicious code, obfuscation, or data exfiltration patterns.
  • [EXTERNAL_DOWNLOADS]: The skill references official documentation at statsmodels.org, which is the legitimate domain for the project. No unexpected or suspicious external resources are downloaded or executed.
  • [COMMAND_EXECUTION]: Code examples use standard Python libraries (statsmodels, pandas, numpy, etc.) for data analysis. No dangerous system commands, subprocess calls, or unauthorized file system operations were found.
  • [DATA_EXFILTRATION]: No network exfiltration patterns or hardcoded credentials were detected. The code snippets operate on local data structures for statistical analysis.
  • [PROMPT_INJECTION]: The instructions do not contain any attempts to override system prompts or bypass safety guidelines.
Audit Metadata
Risk Level
SAFE
Analyzed
Jul 14, 2026, 10:58 AM
Security Audit — agent-trust-hub — statsmodels