How can I mitigate prompt injection and malicious queries in the GPT-3.5 API?

Below is some guidance based on best practices:

Constrain and Validate User Inputs

• Restrict open-ended input: Instead of allowing completely open text input, use validated controls (for example, dropdowns or button selections) where possible. This reduces the chance of maliciously crafted queries that seek to reveal internal instructions.
• Limit token counts: Both for user inputs and model outputs, limiting tokens can help reduce the risk of a prompt injection output long internal system instructions.

Harden System Instructions

• System instructions are not meant to be repeated: In well-designed applications, system or role instructions shouldn’t be included in responses. Ensure you are using the API’s roles (system, user, assistant) as intended so that even if a user’s query indirectly invites the model to reveal system info, the output is constrained by the underlying safety design.

Leverage Safety Guidelines

• Follow established safety best practices: OpenAI’s guidelines recommend curating inputs, validating output sources, and structurally limiting what content can be returned. These measures are crucial when dealing with sophisticated prompt injection attempts.
• Use a layered approach: Combining input validation, model configuration, and output post-processing can further reduce risks.

By employing these strategies—input validation, limiting token outputs, and robust system instruction setups—you can help mitigate issues such as users prompting the model to expose internal content or behave maliciously.

For more details, refer to the safety best practices and latency optimization sections in OpenAI’s technical documentation.