duckdb

Pass

Audited by Gen Agent Trust Hub on Jul 31, 2026

Risk Level: SAFEEXTERNAL_DOWNLOADSREMOTE_CODE_EXECUTIONCREDENTIALS_UNSAFEPROMPT_INJECTION
Full Analysis
  • [REMOTE_CODE_EXECUTION]: The skill contains instructions for installing the DuckDB CLI using a shell command: curl -fsSL https://install.duckdb.org | sh. This pattern involves downloading a script from a remote server and executing it directly in the shell. The source domain belongs to the official DuckDB project.
  • [CREDENTIALS_UNSAFE]: The documentation includes several examples for configuring access to protected resources using credentials.
  • The PostgreSQL attachment example uses a password=secret parameter.
  • The S3 configuration example includes AWS credential placeholders such as KEY_ID 'AKIAIOSFODNN7EXAMPLE' and SECRET 'wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY'.
  • These are identified as standard documentation placeholders rather than actual hardcoded secrets.
  • [EXTERNAL_DOWNLOADS]: The skill provides instructions for installing third-party libraries and extensions.
  • Commands for installing Python packages duckdb, pandas, and pyarrow are included.
  • The skill demonstrates how to install DuckDB extensions such as httpfs, iceberg, delta, and postgres from their official registry.
  • [PROMPT_INJECTION]: The skill facilitates the ingestion of untrusted external data files (Parquet, CSV, JSON, Iceberg) which represents a surface for indirect prompt injection.
  • Ingestion points: Data is loaded into the agent context through functions like read_parquet(), read_csv(), and read_json() in SKILL.md.
  • Boundary markers: No explicit boundary markers or instructions to ignore embedded commands within the files are provided in the usage snippets.
  • Capability inventory: The skill provides capabilities for writing files (COPY TO), network operations through database extensions, and shell command execution for installation.
  • Sanitization: The Python API examples demonstrate the use of parameterized queries (using ? placeholders), which is a recommended practice for preventing SQL injection.
Audit Metadata
Risk Level
SAFE
Analyzed
Jul 31, 2026, 09:00 PM