scikit-learn
Warn
Audited by Gen Agent Trust Hub on Sep 15, 2026
Risk Level: MEDIUMDYNAMIC_EXECUTIONINDIRECT_PROMPT_INJECTION
Full Analysis
- [DYNAMIC_EXECUTION]: The skill includes documentation and code examples for model persistence using the Python
pickleandjobliblibraries. - Evidence: Found in
references/model_evaluation.md, which provides patterns forjoblib.load('model.pkl')andpickle.load(f). - Security Concern: Both libraries are known to be insecure for loading data from untrusted sources, as they can execute arbitrary code during the deserialization process. Loading a malicious model file could result in system compromise.
- [INDIRECT_PROMPT_INJECTION]: The skill facilitates the ingestion of external datasets and provides the agent with capabilities to execute shell commands and write files.
- Ingestion points: Data loading via
pd.read_csv('data.csv')inreferences/common_workflows.mdand various dataset loading functions inscripts/classification_pipeline.pyandscripts/clustering_analysis.py. - Boundary markers: There are no explicit instructions or delimiters used to separate untrusted data from the agent's instruction context.
- Capability inventory: The skill metadata allows access to
Bash,Read,Write, andEdittools. - Sanitization: No evidence of input validation or sanitization for processed data files.
- Security Concern: A malicious actor could provide a data file containing hidden instructions designed to override the agent's behavior or exploit the environment once the data is processed.
Audit Metadata