jailbreak-0be9e8ca·2 events·first seen Aliases: Jailbreak
Researchers present Jailbreak, a system that uses LLMs to synthesize storage readers that bypass database drivers (JDBC/ODBC) entirely by reading PostgreSQL and MySQL storage files directly and materializing data as Apache Arrow columnar buffers. The approach leverages LLMs to ingest database source code and documentation and regenerate format-specific parsing logic without human engineering. Evaluated against TPC-H benchmarks, the generated readers achieve up to 27x speedup over driver-based baselines and produce output consumable by DuckDB, Apache Spark, cuDF, and Spark RAPIDS. The paper argues this methodology generalizes to any database system whose file format is documented or open-source.
OpenAI published research on the 'instruction hierarchy,' a training approach that teaches LLMs to prioritize instructions based on their source privilege level (system prompt > user > third-party). The method aims to make models more robust against prompt injection, jailbreaks, and adversarial instruction overrides. By training models to recognize and respect a hierarchy of instruction authority, OpenAI seeks to reduce the attack surface for multi-agent and deployed LLM systems.