Awesome LLM Security

A curation of awesome tools, documents and projects about LLM Security.

Contributions are always welcome. Please read the Contribution Guidelines before contributing.

Table of Contents

• Awesome LLM Security
  • Papers
    • White-box attack
    • Black-box attack
    • Backdoor attack
    • Fingerprinting
    • Defense
    • Platform Security
    • Survey
    • Benchmark
  • Tools
  • Articles
  • Other Awesome Projects
  • Other Useful Resources

Papers

White-box attack

• "Visual Adversarial Examples Jailbreak Large Language Models", 2023-06, AAAI(Oral) 24, multi-modal, [paper] [repo]
• "Are aligned neural networks adversarially aligned?", 2023-06, NeurIPS(Poster) 23, multi-modal, [paper]
• "(Ab)using Images and Sounds for Indirect Instruction Injection in Multi-Modal LLMs", 2023-07, multi-modal [paper]
• "Universal and Transferable Adversarial Attacks on Aligned Language Models", 2023-07, transfer, [paper] [repo] [page]
• "Jailbreak in pieces: Compositional Adversarial Attacks on Multi-Modal Language Models", 2023-07, multi-modal, [paper]
• "Image Hijacking: Adversarial Images can Control Generative Models at Runtime", 2023-09, multi-modal, [paper] [repo] [site]
• "Weak-to-Strong Jailbreaking on Large Language Models", 2024-04, token-prob, [paper] [repo]

Black-box attack

• "Not what you've signed up for: Compromising Real-World LLM-Integrated Applications with Indirect Prompt Injection", 2023-02, AISec@CCS 23 [paper]
• "Jailbroken: How Does LLM Safety Training Fail?", 2023-07, NeurIPS(Oral) 23, [paper]
• "Latent Jailbreak: A Benchmark for Evaluating Text Safety and Output Robustness of Large Language Models", 2023-07, [paper] [repo]
• "Effective Prompt Extraction from Language Models", 2023-07, prompt-extraction, [paper]
• "Multi-step Jailbreaking Privacy Attacks on ChatGPT", 2023-04, EMNLP 23, privacy, [paper]
• "LLM Censorship: A Machine Learning Challenge or a Computer Security Problem?", 2023-07, [paper]
• "Jailbreaking chatgpt via prompt engineering: An empirical study", 2023-05, [paper]
• "Prompt Injection attack against LLM-integrated Applications", 2023-06, [paper] [repo]
• "MasterKey: Automated Jailbreak Across Multiple Large Language Model Chatbots", 2023-07, time-side-channel, [paper]
• "GPT-4 Is Too Smart To Be Safe: Stealthy Chat with LLMs via Cipher", 2023-08, ICLR 24, cipher, [paper] [repo]
• "Use of LLMs for Illicit Purposes: Threats, Prevention Measures, and Vulnerabilities", 2023-08, [paper]
• "Do-Not-Answer: A Dataset for Evaluating Safeguards in LLMs", 2023-08, [paper] [repo] [dataset]
• "Detecting Language Model Attacks with Perplexity", 2023-08, [paper]
• "Open Sesame! Universal Black Box Jailbreaking of Large Language Models", 2023-09, gene-algorithm, [paper]
• "Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To!", 2023-10, ICLR(oral) 24, [paper] [repo] [site] [dataset]
• "AutoDAN: Generating Stealthy Jailbreak Prompts on Aligned Large Language Models", 2023-10, ICLR(poster) 24, gene-algorithm, new-criterion, [paper]
• "Jailbreak and Guard Aligned Language Models with Only Few In-Context Demonstrations", 2023-10, CoRR 23, ICL, [paper]
• "Multilingual Jailbreak Challenges in Large Language Models", 2023-10, ICLR(poster) 24, [paper] [repo]
• "Scalable and Transferable Black-Box Jailbreaks for Language Models via Persona Modulation", 2023-11, SoLaR(poster) 24, [paper]
• "DeepInception: Hypnotize Large Language Model to Be Jailbreaker", 2023-11, [paper] [repo] [site]
• "A Wolf in Sheep’s Clothing: Generalized Nested Jailbreak Prompts can Fool Large Language Models Easily", 2023-11, NAACL 24, [paper] [repo]
• "AutoDAN: Automatic and Interpretable Adversarial Attacks on Large Language Models", 2023-10, [paper]
• "Language Model Inversion", 2023-11, ICLR(poster) 24, [paper] [repo]
• "An LLM can Fool Itself: A Prompt-Based Adversarial Attack", 2023-10, ICLR(poster) 24, [paper] [repo]
• "GPTFUZZER: Red Teaming Large Language Models with Auto-Generated Jailbreak Prompts", 2023-09, [paper] [repo] [site]
• "Many-shot Jailbreaking", 2024-04, [paper]
• "Rethinking How to Evaluate Language Model Jailbreak", 2024-04, [paper] [repo]

Backdoor attack

• "BITE: Textual Backdoor Attacks with Iterative Trigger Injection", 2022-05, ACL 23, defense [paper]
• "Prompt as Triggers for Backdoor Attack: Examining the Vulnerability in Language Models", 2023-05, EMNLP 23, [paper]
• "Backdooring Instruction-Tuned Large Language Models with Virtual Prompt Injection", 2023-07, NAACL 24, [paper] [repo] [site]

Fingerprinting

• "Instructional Fingerprinting of Large Language Models", 2024-01, NAACL 24 [paper] [repo] [site]
• "TRAP: Targeted Random Adversarial Prompt Honeypot for Black-Box Identification", 2024-02, ACL 24 (findings) [paper] [repo] [video] [poster]
• "LLMmap: Fingerprinting For Large Language Models", 2024-07, [paper] [repo]

Defense

• "Baseline Defenses for Adversarial Attacks Against Aligned Language Models", 2023-09, [paper] [repo]
• "LLM Self Defense: By Self Examination, LLMs Know They Are Being Tricked", 2023-08, ICLR 24 Tiny Paper, self-filtered, [paper] [repo] [site]
• "Defending Against Alignment-Breaking Attacks via Robustly Aligned LLM", 2023-09, random-mask-filter, [paper]
• "Benchmarking and Defending Against Indirect Prompt Injection Attacks on Large Language Models", 2023-12, [paper] [repo]
• "AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks", 2024-03, [paper] [repo]
• "Protecting Your LLMs with Information Bottleneck", 2024-04, [paper] [repo]
• "PARDEN, Can You Repeat That? Defending against Jailbreaks via Repetition", 2024-05, ICML 24, [paper] [repo]
• “Adversarial Tuning: Defending Against Jailbreak Attacks for LLMs”, 2024-06, [paper]
• "Improving Alignment and Robustness with Circuit Breakers", 2024-06, NeurIPS 24, [paper], [repo]

Platform Security

• "LLM Platform Security: Applying a Systematic Evaluation Framework to OpenAI’s ChatGPT Plugins", 2023-09, [paper] [repo]

Survey

• "Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks", 2023-10, ACL 24, [paper]
• "Security and Privacy Challenges of Large Language Models: A Survey", 2024-02, [paper]
• "Breaking Down the Defenses: A Comparative Survey of Attacks on Large Language Models", 2024-03, [paper]
• "Operationalizing a Threat Model for Red-Teaming Large Language Models (LLMs)", 2024-07, [paper]

Benchmark

• "JailbreakBench: An Open Robustness Benchmark for Jailbreaking Large Language Models", 2024-03, [paper]
• "AgentDojo: A Dynamic Environment to Evaluate Attacks and Defenses for LLM Agents", 2024-06, NeurIPS 24, [paper] [repo] [site]
• "AgentHarm: A Benchmark for Measuring Harmfulness of LLM Agents", 2024-10, [paper]

Tools

• Plexiglass: a security toolbox for testing and safeguarding LLMs
• PurpleLlama: set of tools to assess and improve LLM security.
• Rebuff: a self-hardening prompt injection detector
• Garak: a LLM vulnerability scanner
• LLMFuzzer: a fuzzing framework for LLMs
• LLM Guard: a security toolkit for LLM Interactions
• Vigil: a LLM prompt injection detection toolkit
• jailbreak-evaluation: an easy-to-use Python package for language model jailbreak evaluation
• Prompt Fuzzer: the open-source tool to help you harden your GenAI applications
• WhistleBlower: open-source tool designed to infer the system prompt of an AI agent based on its generated text outputs.

Articles

• Hacking Auto-GPT and escaping its docker container
• Prompt Injection Cheat Sheet: How To Manipulate AI Language Models
• Indirect Prompt Injection Threats
• Prompt injection: What’s the worst that can happen?
• OWASP Top 10 for Large Language Model Applications
• PoisonGPT: How we hid a lobotomized LLM on Hugging Face to spread fake news
• ChatGPT Plugins: Data Exfiltration via Images & Cross Plugin Request Forgery
• Jailbreaking GPT-4's code interpreter
• Securing LLM Systems Against Prompt Injection
• The AI Attack Surface Map v1.0
• Adversarial Attacks on LLMs
• How Anyone can Hack ChatGPT - GPT4o
• LLM Evaluation metrics, frmaework, and checklist
• How RAG Poisoning Made Llama3 Racist!

Other Awesome Projects

• (0din GenAI Bug Bounty from Mozilla)(https://0din.ai): The 0Day Investigative Network is a bug bounty program focusing on flaws within GenAI models. Vulnerability classes include Prompt Injection, Training Data Poisoning, DoS, and more.
• Gandalf: a prompt injection wargame
• LangChain vulnerable to code injection - CVE-2023-29374
• LLM Security startups
• Adversarial Prompting
• Epivolis: a prompt injection aware chatbot designed to mitigate adversarial efforts
• LLM Security Problems at DEFCON31 Quals: the world's top security competition
• PromptBounty.io
• PALLMs (Payloads for Attacking Large Language Models)

Other Useful Resources

• Twitter: @llm_sec
• Blog: LLM Security authored by @llm_sec
• Blog: Embrace The Red
• Blog: Kai's Blog
• Newsletter: AI safety takes
• Newsletter & Blog: Hackstery