Static Python Tool Flags SQL Injection Risk in AI Agent Queries at Parse Time

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A developer has built agent_sql_seam.py, a static analysis tool using Python's standard ast library, to detect SQL injection vulnerabilities in AI agent code before execution. The tool inspects how SQL strings are assembled and classifies each database call as RAW_STRING_TO_DB, PARAM_OK, POLICY_MEDIATED, or UNRESOLVED. Two queries returning identical rows can differ critically in safety: one using an f-string to embed an agent-supplied value is flagged as a raw injection risk, while one using a bound parameter is marked safe. The key insight is that query correctness — what rows are returned — reveals nothing about whether the SQL assembly method is exploitable. The tool runs entirely offline with no dependencies beyond the Python standard library and produces deterministic, verifiable output.

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