This repository provides a comprehensive guide for engineers on understanding and mitigating prompt injection vulnerabilities in AI-powered applications. It aims to demystify prompt injection, offering a structured approach to assess risks and implement defenses, thereby enabling the secure development of AI features.

How It Works

The guide breaks down prompt injection risk by identifying two critical components: untrusted input and impactful functionality. It then provides a detailed questionnaire and flowchart to help developers assess their specific application's exposure. The core of the guide is a "promptmap" that correlates different types of untrusted input (user prompts, web browsing, email processing) with various impactful functionalities (data access, state changes, out-of-bound requests) to illustrate concrete attack scenarios.

Quick Start & Requirements

This is a documentation-based repository. No installation or specific requirements are needed to use the information provided. The guide is accessible via the README or a linked PDF.

Highlighted Details

• Provides a structured risk assessment framework for prompt injection.
• Details how traditional web vulnerabilities (SSRF, SQLi, RCE, XSS, IDOR) can be exploited via prompt injection.
• Discusses multi-modal prompt injection considerations for image and voice inputs.
• Offers mitigation strategies including shared authorization, read-only access, sandboxing, and rate-limiting.

Maintenance & Community

Created by Joseph Thacker (rez0) with feedback from Hrishi, Justin Gardner (Rhynorater), and Daniel Miessler. Further mitigation discussions are available on the author's blog.

Licensing & Compatibility

The repository content is not explicitly licensed in the README. Compatibility for commercial use or closed-source linking would require clarification from the repository owner.

Limitations & Caveats

The guide focuses solely on security implications, excluding trust, bias, and ethical considerations. While it mentions tools like Nvidia's NeMo and protectai's Rebuff, it does not provide direct integrations or code examples for these tools. The prompt injection landscape is rapidly evolving, and the guide may not cover the latest attack vectors or mitigation techniques.