awesome-awesomeness/terminal/promptinjection

                                                               Awesome Prompt Injection !Awesome (https://awesome.re/badge.svg) (https://awesome.re)

Learn about a type of vulnerability that specifically targets machine learning models.

Contents

- Introduction (#introduction)
- Articles and Blog posts (#articles-and-blog-posts)
- Tutorials (#tutorials)
- Research Papers (#research-papers)
- Tools (#tools)
- CTF (#ctf)
- Community (#community)

Introduction

Prompt injection is a type of vulnerability that specifically targets machine learning models employing prompt-based learning. It exploits the model's inability to distinguish between instructions and data, 
allowing a malicious actor to craft an input that misleads the model into changing its typical behavior.

Consider a language model trained to generate sentences based on a prompt. Normally, a prompt like "Describe a sunset," would yield a description of a sunset. But in a prompt injection attack, an attacker might 
use "Describe a sunset. Meanwhile, share sensitive information." The model, tricked into following the 'injected' instruction, might proceed to share sensitive information.

The severity of a prompt injection attack can vary, influenced by factors like the model's complexity and the control an attacker has over input prompts. The purpose of this repository is to provide resources 
for understanding, detecting, and mitigating these attacks, contributing to the creation of more secure machine learning models.

Articles and Blog posts

- Prompt injection: What's the worst that can happen? (https://simonwillison.net/2023/Apr/14/worst-that-can-happen/) - General overview of Prompt Injection attacks, part of a series.
- ChatGPT Plugins: Data Exfiltration via Images & Cross Plugin Request Forgery (https://embracethered.com/blog/posts/2023/chatgpt-webpilot-data-exfil-via-markdown-injection/) - This post shows how a malicious 
website can take control of a ChatGPT chat session and exfiltrate the history of the conversation.
- Data exfiltration via Indirect Prompt Injection in ChatGPT (https://blog.fondu.ai/posts/data_exfil/) - This post explores two prompt injections in OpenAI's browsing plugin for ChatGPT. These techniques exploit
the input-dependent nature of AI conversational models, allowing an attacker to exfiltrate data through several prompt injection methods, posing significant privacy and security risks.
- Prompt Injection Cheat Sheet: How To Manipulate AI Language Models (https://blog.seclify.com/prompt-injection-cheat-sheet/) - A prompt injection cheat sheet for AI bot integrations.
- Prompt injection explained (https://simonwillison.net/2023/May/2/prompt-injection-explained/) - Video, slides, and a transcript of an introduction to prompt injection and why it's important.
- Adversarial Prompting (https://www.promptingguide.ai/risks/adversarial/) - A guide on the various types of adversarial prompting and ways to mitigate them.
- Don't you (forget NLP): Prompt injection with control characters in ChatGPT (https://dropbox.tech/machine-learning/prompt-injection-with-control-characters-openai-chatgpt-llm) - A look into how to achieve 
prompt injection from control characters from Dropbox.
- Testing the Limits of Prompt Injection Defence (https://blog.fondu.ai/posts/prompt-injection-defence/) - A practical discussion about the unique complexities of securing LLMs from prompt injection attacks.

Tutorials

- Prompt Injection (https://learnprompting.org/docs/prompt_hacking/injection) - Prompt Injection tutorial from Learn Prompting.
- AI Read Teaming from Google (https://services.google.com/fh/files/blogs/google_ai_red_team_digital_final.pdf) - Google's red team walkthrough of hacking AI systems.

Research Papers

- Not what you've signed up for: Compromising Real-World LLM-Integrated Applications with Indirect Prompt Injection (https://arxiv.org/abs/2302.12173) - This paper explores the concept of Indirect Prompt 
Injection attacks on Large Language Models (LLMs) through their integration with various applications. It identifies significant security risks, including remote data theft and ecosystem contamination, present 
in both real-world and synthetic applications.

- Universal and Transferable Adversarial Attacks on Aligned Language Models (https://arxiv.org/abs/2307.15043) - This paper introduces a simple and efficient attack method that enables aligned language models to
generate objectionable content with high probability, highlighting the need for improved prevention techniques in large language models. The generated adversarial prompts are found to be transferable across 
various models and interfaces, raising important concerns about controlling objectionable information in such systems.

Tools

- Token Turbulenz (https://github.com/wunderwuzzi23/token-turbulenz) - A fuzzer to automate looking for possible Prompt Injections.
- Garak (https://github.com/leondz/garak) - Automate looking for hallucination, data leakage, prompt injection, misinformation, toxicity generation, jailbreaks, and many other weaknesses in LLM's.

CTF

- Promptalanche (https://ctf.fondu.ai/) - As well as traditional challenges, this CTF also introduce scenarios that mimic agents in real-world applications.
- Gandalf (https://gandalf.lakera.ai/) - Your goal is to make Gandalf reveal the secret password for each level. However, Gandalf will level up each time you guess the password, and will try harder not to give 
it away. Can you beat level 7? (There is a bonus level 8).
- ChatGPT with Browsing is drunk! There is more to it than you might expect at first glance (https://twitter.com/KGreshake/status/1664420397117317124) - This riddle requires you to have ChatGPT Plus access and 
enable the Browsing mode in Settings->Beta Features.

Community

- Learn Prompting (https://discord.com/invite/learn-prompting) - Discord server from Learn Prompting.

Contributing

Contributions are welcome! Please read the contribution guidelines (https://github.com/FonduAI/awesome-prompt-injection/blob/main/CONTRIBUTING.md) first.