Language Model Security Database

A prompt injection vulnerability in OpenAI's custom GPT models allows attackers to extract the system prompt and potentially leak user-uploaded files. Attackers craft malicious prompts that manipulate the LLM into revealing sensitive information, even when defensive prompts are in place. The vulnerability is exacerbated when the model includes a code interpreter.

A system prompt leakage vulnerability in GPT-4V allows extraction of internal system prompts through carefully crafted, incomplete conversations combined with image input. Extracted prompts can be used as highly effective jailbreak prompts, bypassing safety restrictions and leading to undesirable outputs, including revealing personally identifiable information from images.

Large Language Model (LLM)-integrated web applications using Langchain (and potentially similar middleware) are vulnerable to Prompt-to-SQL (P2SQL) injection attacks. Unsanitized user prompts can be crafted to cause the LLM to generate malicious SQL queries, leading to unauthorized database access (read and write operations). This vulnerability bypasses attempts to restrict the LLM through prompt engineering alone.