Show HN: Prompt Guard–MitM proxy that blocks secrets before they reach AI APIs
The project presents a MitM-style proxy designed to block sensitive data from leaking into AI API calls. By filtering prompts and ensuring secrets stay out of the payloads that AI models consume, the tool aims to curb data exfiltration risks in environments where third-party AI services are used. This is particularly relevant for enterprises and developers integrating AI capabilities into critical workflows where data privacy and confidentiality are non-negotiable.
From a security engineering lens, the Prompt Guard concept reinforces the importance of “defense in depth” at the prompt boundary, adding a practical layer between application code and external AI services. It could drive best-practice patterns for data minimization, tokenized prompts, and whitelisting rules before any AI operation is executed. Adoption, of course, hinges on ease of integration, reliability, and the ability to avoid false positives that would otherwise disrupt legitimate AI usage.
Strategically, this kind of tooling demonstrates a maturing AI security market where bespoke hardening layers for AI workflows are common. It also invites a broader discussion about privacy-by-design in AI tooling and how organizations can balance rapid AI enablement with the need to protect sensitive information, especially in regulated sectors such as finance, healthcare, and government operations.