azure-search-documents-py
Pass
Audited by Gen Agent Trust Hub on Sep 15, 2026
Risk Level: SAFEINDIRECT_PROMPT_INJECTION
Full Analysis
- [Secure Authentication Practices]: The skill recommends using modern identity-based authentication methods over static API keys. This approach enables secure, keyless authentication via managed identities and environment-based configuration, reducing the risk of credential exposure.
- [Proper Resource Lifecycle Management]: Code examples utilize context managers for client instances. This ensures that network transports and authentication caches are deterministically closed, preventing resource leaks.
- [Data Ingestion Surface]: The skill facilitates the retrieval of documents from an external search index, creating a surface where untrusted data enters the agent's context. This is the intended functionality for retrieval-augmented tasks but requires awareness of potential data poisoning.
- Ingestion points:
SearchClient.searchinSKILL.mdandKnowledgeBaseRetrievalClient.retrieveinreferences/agentic-retrieval.md. - Boundary markers: Code snippets focus on demonstrating library capabilities and do not explicitly include boundary delimiters or instructions to ignore embedded content.
- Capability inventory: The skill provides tools for search operations, index management, and document updates, without performing high-risk actions like arbitrary command execution based on retrieved data.
- Sanitization: The examples demonstrate processing and displaying search results without showing specific sanitization or validation logic for the content of the retrieved documents.
Audit Metadata